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Dissertations / Theses on the topic 'Interval valued fuzzy'
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Qiu, Yu. "Statistical Genetic Interval-Valued Type-2 Fuzzy System and its Application." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/22.
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In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system. In order to make the type-2 fuzzy logic system reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and a new probability type reduced reasoning method for the interval-valued fuzzy logic system are proposed in this thesis. In order to optimize this particle system’s performance, we adopt genetic algorithm (GA) to adjust parameters. The applications for the new system are performed and results have shown that the developed method is more accurate and robust to design a reliable fuzzy logic system than type-1 method and the computation of our proposed method is more efficient.
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Hamrawi, Hussam. "Type-2 fuzzy alpha-cuts." Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/5137.
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Systems that utilise type-2 fuzzy sets to handle uncertainty have not been implemented in real world applications unlike the astonishing number of applications involving standard fuzzy sets. The main reason behind this is the complex mathematical nature of type-2 fuzzy sets which is the source of two major problems. On one hand, it is difficult to mathematically manipulate type-2 fuzzy sets, and on the other, the computational cost of processing and performing operations using these sets is very high. Most of the current research carried out on type-2 fuzzy logic concentrates on finding mathematical means to overcome these obstacles. One way of accomplishing the first task is to develop a meaningful mathematical representation of type-2 fuzzy sets that allows functions and operations to be extended from well known mathematical forms to type-2 fuzzy sets. To this end, this thesis presents a novel alpha-cut representation theorem to be this meaningful mathematical representation. It is the decomposition of a type-2 fuzzy set in to a number of classical sets. The alpha-cut representation theorem is the main contribution of this thesis. This dissertation also presents a methodology to allow functions and operations to be extended directly from classical sets to type-2 fuzzy sets. A novel alpha-cut extension principle is presented in this thesis and used to define uncertainty measures and arithmetic operations for type-2 fuzzy sets. Throughout this investigation, a plethora of concepts and definitions have been developed for the first time in order to make the manipulation of type-2 fuzzy sets a simple and straight forward task. Worked examples are used to demonstrate the usefulness of these theorems and methods. Finally, the crisp alpha-cuts of this fundamental decomposition theorem are by definition independent of each other. This dissertation shows that operations on type-2 fuzzy sets using the alpha-cut extension principle can be processed in parallel. This feature is found to be extremely powerful, especially if performing computation on the massively parallel graphical processing units. This thesis explores this capability and shows through different experiments the achievement of significant reduction in processing time.
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Đukić, Marija. "Mrežno vrednosne intuicionističke preferencijske strukture i primene." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2018. https://www.cris.uns.ac.rs/record.jsf?recordId=107638&source=NDLTD&language=en.
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Intuicionistički rasplinuti skupovi su već proučavani i definisani u kontekstu mrežnovrednosnih struktura, ali svaka od postojećih definicija imala je odgovarajuće nedostatke. U ovom radu razvijena je definicija intuicionističkog poset-vrednosnog rasplinutog skupa, kojom se poset predstavlja kao podskup distributivne mreže. Na ovaj način možemo ispitivati funkcije pripadanja i nepripadanja i njihove odnose bez upotrebe komplementiranja na posetu. Takođe, u ovako postavljenim okvirima, svaki poset (a samim tim i mreža) može biti kodomen intuicionističkog rasplinutog skupa (čime se isključuje uslov ograničenosti poseta). Primenom uvedene definicije razmatrane su IP-vrednosne rasplinute relacije, x-blokovi ovih relacija i familijenjihovih nivoa.Razvijene su jake poset vrednosne relacije reciprociteta koje predstavljaju uopštenje relacija reciprociteta sa intervala [0,1]. Pokazano je da ovakve relacije imaju svojstva slična poset-vrednosnim relacijama preferencije. Međutim, postoje velika ograničenja za primenu ovakvih relacija jer su zahtevi dosta jaki.Uvedene su IP-vrednosne relacije reciprociteta koje se mogu definisati za veliku klasu poseta.Ovakve relacije pogodne su za opisivanje preferencija. Posmatrana je intuicionistička poset-vrednosna relacija preferencije, koja je refleksivna rasplinuta relacija, nad skupom alternativa. U samom procesu višekriterijumskog odlučivanjamože se pojaviti situacija kada alternative nisu međusobno uporedive u odnosu na relaciju preferencije, kao i nedovoljna određenost samih alternativa. Da bi se prevazišli ovakvi problemi uvodi se intuicionistička poset-vrednosna relacija preferencije kao intuicionistička rasplinuta relacija na skupu alternativa sa vrednostima u uređenom skupu. Analizirana su neka njena svojstva. Ovakav model pogodan je za upoređivanje alternativa koje nisu, nužno, u linearnom poretku. Dato je nekoliko opravdanja za uvodjenje oba tipa definisanih relacija. Jedna od mogućnosti jeste preko mreže intervala elemenata iz konačnog lanca S, a koji predstavljaju ocene određene alternative. Relacije preferencije mogu uzimati vrednosti sa ove mreže i time se može prevazići nedostatak informacija ili neodlučnost donosioca odluke.Intuitionistic fuzzy sets have already been explored in depth and defined in the context of lattice-valued intuitionistic fuzzy sets, however, every existing definition has certain drawbacks. In this thesis, a definition of poset-valued intuitionistic fuzzy sets is developed, which introduces a poset as a subset of a distributive lattice. In this manner, functions of membership and non-membership can be examined as well as their relations without using complement in the poset. Also, in such framework, each poset (and the lattice) can be a co-domain of an intuitionistic fuzzy set (which excludes the condition of the bounded poset). Introduced definition defines IP-valued fuzzy relations, x-blocks of these relations andfamilies of their levels. Strong IP-valued reciprocialy relations have been developed as a generalization of reciprocal relations from interval [0,1]. It has been shown that these relations have properties similar to the P-valued preferences relations. However, there are great constraints on the application of these relations because the requirements are quite strong.IP- valued reciprocial relations have been introduced, which can be defined for a large class of posets. Such relations are suitable for describing preferences.An intuitionistic poset-valued preference relation, which is a reflexive fuzzy relation, over the set of alternatives, has been examined. In the process of a multi-criteria decision making, a situation can occur that the alternatives cannot be compared by the preference relation, as well as insufficient determination of the mentioned alternatives. In order to overcome similar problems, we have introduced an intuitionistic poset-valued preference relation as an intuitionistic fuzzy set over the set of alternatives with values in a certain poset. We have analyzed some its performances. This model is suitable for comparing alternatives which are not necessarily linearly ordered. There are several justifications for the introduction of both types of defined relations. One of the possibilities is via the lattice of the intervals of elements from the finite chain S, which represent the preference of a particular alternative. Preferences relations can take values from this lattice and this can overcome the lack of informations or the decisiveness of the decision maker.
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Marijana, Gorjanac Ranitović. "Neke klase planarnih mreža i intervalno-vrednosni rasplinuti skupovi." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2015. https://www.cris.uns.ac.rs/record.jsf?recordId=93345&source=NDLTD&language=en.
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U radu je ispitan sledeći problem: Pod kojim uslovima se može rekonstruisati (sintetisati) intervalno-vrednosni rasplinuti skup iz poznate familije nivo skupova.U tu svrhu su proučena svojstva mreža intervala za svaki od četiri izabrana mrežna uređenja: poredak po komponentama, neprecizni poredak (skupovna inkluzija), strogi i leksikografski poredak. Definisane su i-između i ili-između ravne mreže i ispitana njihova svojstva potrebna za rešavanje postavljenog problema sinteze za intervalno-vrednosne rasplinute skupove. Za i-između ravne mreže je dokazano da su, u svom konačnom slučaju, slim mreže i dualno, da su ili-između ravne mreže dualno-slim mreže.Data je karakterizacija kompletnih konačno prostornih i dualno konačno prostornih mreža. Određena je klasa mreža koje se mogu injektivno preslikati u direktan proizvod n kompletnih lanaca tako da su očuvani supremumi i dualno, određena je klasa mreža koje se mogu injektivno preslikati u direktan proizvod n lanaca tako da su očuvani infimumi. U rešavanju problema sinteze posmatrana su dva tipa nivo skupova - gornji i donji nivo skupovi. Potreban i dovoljan uslov za sintezu intervalno-vrednosnog rasplinutog skupa iz poznate familije nivo skupova određen je za mrežu intervala koja je uređena poretkom po komponentama, za oba tipa posmatranih nivo skupova.Za mrežu intervala uređenu nepreciznim poretkom, problem je rešen za donje nivo skupove, dok su za gornje nivo skupove određeni dovoljni uslovi.Za mrežu intervala koja je uređena leksikografskim poretkom, takođe su dati dovoljniuslovi i to za oba tipa nivo skupova. Za mrežu intervala uređenu strogim poretkom problem nije rešavan, jer izlazi izvan okvira ovog rada.Dobijeni rezultati su primenjeni za rešavanje sličnog problema sinteze za intervalno-vrednosne intuicionističke rasplinute skupove za mrežu intervala uređenu poretkom po komponentama. Rezultati ovog istraživanja su od teorijskog značaja u teoriji mreža i teoriji rasplinutih skupova, ali postoji mogućnost za primenu u matematičkoj morfologiji i obradi slika.In this thesis the following problem was investigated: Under which conditions an interval-valued fuzzy set can be reconstructed from the given family of cut sets.We consider interval-valued fuzzy sets as a special type of lattice-valued fuzzy sets and we studied properties of lattices of intervals using four different lattice order: componentwise ordering, imprecision ordering (inclusion of sets), strong and lexicographical ordering.We proposed new definitions of meet-between planar and join - between planar lattices, we investigated their properties and used them for solving problem of synthesis in interval-valued fuzzy sets.It has been proven that finite meet- between planar lattices and slim lattices are equivalent, and dually: finite join- between planar lattices and dually slim lattices are equivalent.Complete finitely spatial lattices and complete dually finitely spatial lattices are fully characterized in this setting. Next, we characterized lattices which can be orderembedded into a Cartesian product of n complete chains such that all suprema are preserved under the embedding.And dually, we characterized lattices which can be order embedded into a Cartesian product of n complete chains such that all infima are preserved under the embedding.We considered two types of cut sets – upper cuts and lower cuts.Solution of the problem of synthesis of interval-valued fuzzy sets are given for lattices of intervals under componentwise ordering for both types of cut sets. Solution of problem of synthesis of interval-valued fuzzy sets are given for lower cuts for lattices of intervals under imprecision ordering. Sufficient conditions are given for lattices of intervals under imprecision ordering and family of upper cuts.Sufficient conditions are also given for lattices of intervals under lexicographical ordering.The problem of synthesis of interval-valued fuzzy sets for lattices of intervals under strong ordering is beyond the scope of this thesis.A similar problem of synthesis of interval-valued intuitionistic fuzzy sets is solved for lattices of intervals under componentwise ordering.These results are mostly of theoretical importance in lattice theory and fuzzy sets theory, but also they could be applied in mathematical morphology and in image processing.
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Beisler, Matthias Werner. "Modelling of input data uncertainty based on random set theory for evaluation of the financial feasibility for hydropower projects." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2011. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-71564.
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The design of hydropower projects requires a comprehensive planning process in order to achieve the objective to maximise exploitation of the existing hydropower potential as well as future revenues of the plant. For this purpose and to satisfy approval requirements for a complex hydropower development, it is imperative at planning stage, that the conceptual development contemplates a wide range of influencing design factors and ensures appropriate consideration of all related aspects. Since the majority of technical and economical parameters that are required for detailed and final design cannot be precisely determined at early planning stages, crucial design parameters such as design discharge and hydraulic head have to be examined through an extensive optimisation process. One disadvantage inherent to commonly used deterministic analysis is the lack of objectivity for the selection of input parameters. Moreover, it cannot be ensured that the entire existing parameter ranges and all possible parameter combinations are covered. Probabilistic methods utilise discrete probability distributions or parameter input ranges to cover the entire range of uncertainties resulting from an information deficit during the planning phase and integrate them into the optimisation by means of an alternative calculation method. The investigated method assists with the mathematical assessment and integration of uncertainties into the rational economic appraisal of complex infrastructure projects. The assessment includes an exemplary verification to what extent the Random Set Theory can be utilised for the determination of input parameters that are relevant for the optimisation of hydropower projects and evaluates possible improvements with respect to accuracy and suitability of the calculated resultsDie Auslegung von Wasserkraftanlagen stellt einen komplexen Planungsablauf dar, mit dem Ziel das vorhandene Wasserkraftpotential möglichst vollständig zu nutzen und künftige, wirtschaftliche Erträge der Kraftanlage zu maximieren. Um dies zu erreichen und gleichzeitig die Genehmigungsfähigkeit eines komplexen Wasserkraftprojektes zu gewährleisten, besteht hierbei die zwingende Notwendigkeit eine Vielzahl für die Konzepterstellung relevanter Einflussfaktoren zu erfassen und in der Projektplanungsphase hinreichend zu berücksichtigen. In frühen Planungsstadien kann ein Großteil der für die Detailplanung entscheidenden, technischen und wirtschaftlichen Parameter meist nicht exakt bestimmt werden, wodurch maßgebende Designparameter der Wasserkraftanlage, wie Durchfluss und Fallhöhe, einen umfangreichen Optimierungsprozess durchlaufen müssen. Ein Nachteil gebräuchlicher, deterministischer Berechnungsansätze besteht in der zumeist unzureichenden Objektivität bei der Bestimmung der Eingangsparameter, sowie der Tatsache, dass die Erfassung der Parameter in ihrer gesamten Streubreite und sämtlichen, maßgeblichen Parameterkombinationen nicht sichergestellt werden kann. Probabilistische Verfahren verwenden Eingangsparameter in ihrer statistischen Verteilung bzw. in Form von Bandbreiten, mit dem Ziel, Unsicherheiten, die sich aus dem in der Planungsphase unausweichlichen Informationsdefizit ergeben, durch Anwendung einer alternativen Berechnungsmethode mathematisch zu erfassen und in die Berechnung einzubeziehen. Die untersuchte Vorgehensweise trägt dazu bei, aus einem Informationsdefizit resultierende Unschärfen bei der wirtschaftlichen Beurteilung komplexer Infrastrukturprojekte objektiv bzw. mathematisch zu erfassen und in den Planungsprozess einzubeziehen. Es erfolgt eine Beurteilung und beispielhafte Überprüfung, inwiefern die Random Set Methode bei Bestimmung der für den Optimierungsprozess von Wasserkraftanlagen relevanten Eingangsgrößen Anwendung finden kann und in wieweit sich hieraus Verbesserungen hinsichtlich Genauigkeit und Aussagekraft der Berechnungsergebnisse ergeben
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Han, Wen-Hsin, and 韓文欣. "Fuzzy Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Values, Interval-Valued Intuitionistic Fuzzy Weighted Averaging Operator, and Nonlinear Programming Methodology." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/y8vcyj.
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碩士國立臺灣科技大學
資訊工程系
106
In this thesis, we propose a new fuzzy multiattribute decision making method based on interval-valued intuitionistic fuzzy values, the interval-valued intuitionistic fuzzy weighted averaging operator, and the nonlinear programming methodology. Firstly, the proposed method calculates the largest ranges of interval-valued intuitionistic fuzzy weights of attributes and modifies unreasonable ranges of interval-valued intuitionistic fuzzy weights. Then, it gets the transformed decision matrix based on the score function of interval-valued intuitionistic fuzzy values and the decision matrix provided by the decision maker. Then, it constructs the nonlinear programming model based on the obtained transformed decision matrix and the obtained largest ranges of interval-valued intuitionistic fuzzy weights of attributes. Then, it gets the optimal weights of the attributes based on the obtained nonlinear programming model. Then, it calculates the weighted evaluating interval-valued intuitionistic fuzzy values of the alternatives based on the decision matrix, the obtained optimal weights of the attributes and the interval-valued intuitionistic fuzzy weighted averaging operator. Finally, it gets the preference order of the alternatives based on the score function, the accuracy function, the membership uncertainty index and the hesitation uncertainty index of interval-valued intuitionistic fuzzy values. The proposed fuzzy multiattribute decision making method can overcome the drawback of the existing methods. It provides us with a very useful way for fuzzy multiattribute decision making in interval-valued intuitionistic fuzzy environments.
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Wang, Ching-Nan, and 王景南. "T-transitive Interval-valued Fuzzy Clustering." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/88436650812066652504.
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博士中原大學
應用數學研究所
101
Fuzzy relation with its partitioned tree for obtaining an agglomerative hierarchical clustering has been widely studied and applied in recent years. Most fuzzy-relation-based clustering approaches are based on real-valued memberships. However, interval-valued memberships may be better than real-valued memberships to represent higher-order imprecision and vagueness for human perception. Thus, this dissertation first extends fuzzy relations to interval-valued fuzzy relations and then constructs a clustering algorithm based on the proposed T -transitive interval-valued fuzzy relations. There are two interesting examples, the characteristic beauty of Chinese characters and portraits of family member, to be applied in this dissertation to demonstrate the efficiency and usefulness of the proposed method. In practical application, we utilize the proposed clustering method to performance evaluations for academic departments of higher education by using actual engineering school data in Taiwan. The consequences of a hierarchical evaluation structure were thought to be more flexible and softer than the original one that the Taiwan Assessment and Evaluation Association (TWAEA) committee adopted. Demonstrating by examples and practical application, one who utilize the proposed clustering method in this dissertation to fuzzy data clustering may obtain better results.
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Yang, Yi Hsuan, and 楊以萱. "An Interval-Valued Intuitionistic Fuzzy LINMAP Method." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/87252408212978847643.
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碩士長庚大學
工商管理學系
101
Fuzzy theory had been developed the most effective solution to handle high uncertainty. The theory can avoid incomplete information, the individual subject judgment and the degree of preference which affect the result of decision estimation. The most part of decision preference information is from attribute, and the difference from the Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP) is reflecting the preference information for given alternatives. The LINMAP method applied in the interval-valued intuitionistic fuzzy sets (IVIFSs)had attracted research's attention recently. In the past, the researches of IVIFS were not using extra distance estimation to handle decision problem, so this paper presents a new linear programming model to solve by different distance estimation. In addition, I use the similarity instead of distance estimation to improve LINMAP method. This study presents two extended LINMAP method to improve the traditional LINMAP, redefining the consistency and inconsistency indices, and constructs new linear programming model, respectively. I implement the Simplex method to solve the model, and then rank all alternatives for decision maker according to an increasing order of their distance or similarity. The method 1 is used regular distance estimation to construct the consistency and inconsistency indices, and then solve via constructing new linear programming model. The method 2 is used the concept of similarity to construct the consistency and inconsistency indices. Because the similarity is represented the similar degree between two conception, the considering elements are more widely than distance estimation. In order to obtain the more accurate priority order of the alternatives, I use the effect between each attribute. Finally, I use method applying in the decision problem by graduate admission problem and investment decision problem. Our discussion focus on the decision effect by choosing different formulas, then analyze and compare with the final rank result. Because the solution data and method are entirely different comparing with the past researches, the results I obtain are complete different. The proposed methods are more complex and cover widely, therefore my methods are more complete. As mentioning above, the LINMAP approach to validate the effectiveness and distinguishability of the proposed methodology.
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Lin, Yi-Siou, and 林以修. "Fuzzy clusterwise regression model for interval-valued data." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/94384645660184547590.
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碩士國立宜蘭大學
電機工程學系碩士班
101
This paper presents a fuzzy clusterwise regression model algorithm for the uncertain nature of interval data. Comparing with the past clusterwise regression model algorithm, the fuzzy clusterwise model’s predict part adopts the input variables membership fuzzy operator for the input vector, furthermore the membership model parameters part is calculated by the least squares method. The study presents manual data and exchange rate data to verify the results show that the fuzzy clusterwise regression model algorithm has better effect.
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Chueh, Wei Chun, and 闕瑋群. "Interval-valued intuitionistic fuzzy TOPSIS method and experimental analysis." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/64003875575956561611.
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碩士長庚大學
工商管理學系
102
The purpose of the study is to extend the concept of TOPSIS method by interval-valued intuitionistic fuzzy sets (IVIFS). TOPSIS method measures the distances of each alternative from the ideal solution and negative ideal solution, and it usually calculates the separation measures by Euclidian distance. Most researches of the separation measures were only focus on exploring the influence of decision making results by using different distance measurements. In the past, the concept of TOPSIS method has expanded to under the intuitionistic fuzzy environment. IVIFS is an important expansion of fuzzy theory, but it is difficult to collect the IVIFS data and the accurate information for decision matrix. Therefore, this study tried to use experimental analysis to discuss the scenario analysis with incomplete information. This study is to extend the TOPSIS method for analyzing data by using separation measures under the IVIFS environment. It retains the advantage of TOPSIS method which is easy to calculate, and collect the formulas for similarity and association coefficient to represent separation measures. According to the experiment analysis, this study used the random number to develop various models, and compared the results of the separation measures in different models by consistency rate and Spearman correlation coefficients. The empirical results indicate that the number of alternatives would influence the consistency rate.
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Lin, Chih Ting, and 林致廷. "Group Decision Making Based on Interval-Valued Fuzzy Numbers." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/43647343520455128979.
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碩士長庚大學
工商管理學系
99
Abstract Decision-making cause uncertain meaning in language is almost different from the real situation. Zadeh (1965) First proposed fuzzy theory to measure vague comments. In the complicated decision environment, single decision-maker is too subjective, We need experts comments with different professional backgrounds, group decision-making, consensus combined experts is much closer than real decision result, the purpose of this study presented a new group decision-making method based on interval-valued fuzzy numbers. The study focused on experts’ consensus, it based on TOPSIS used interval-valued fuzzy numbers proposed by Ashtiani et al. (2009), using similarity measures between interval-valued fuzzy numbers proposed by Chen and Chen (2009) to measuring distance of horizontal-axis, and similarity between X-axis and Y-axis, effectively handling information filtering problems based on interval-valued fuzzy numbers, revising the similarity measures method in Ashtiani et al. (2009), and interpreting by a numerical case. Today employees are important assets of companies and enterprises, especially Hi-tect R&D personnel, human recruiting of pre-work can not be ignored. In empirical study, asking the directors’perspective in the department of human resource, the provider of wireless broadband soluations in Hisnchu，using seven criteria to comment overall performance of the engineers from various recruitment channels, proofing the practicality using the method of this study. The results of the priority order, internal recommendation, alternative R&D, and internet human resource agency. With the weight of parameter to represent the importance of the directors, and comparing the valued of the six sets, there is no difference after changing the values, it means the directors’ comments is in agreement. The result shows the directors tend to choose the interviewee recommended by consultants, it also echoed the effectiveness of industry-university cooperation in recent years.
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Lee, Chan-Shal, and 李昌諧. "AN INTERVAL-VALUED FUZZY NUMBER APPROACH FOR SUPPLIER SELECTION." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/84080754614624137828.
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博士國立臺灣海洋大學
航運管理學系
104
Supplier assessment in supply chain management plays an important role in the business transaction. Many methods have been proposed to deal with the supplier selection problems. Some of them are based on fuzzy set theory. However, traditional fuzzy numbers can not precisely express the vagueness in the decision process. In this thesis, we are going to propose a new fuzzy multiple criteria decision making model based on interval-valued fuzzy numbers to tackle the supplier selection problem in the circumstances where uncertainty is introduced. Usually, fuzzy numbers are employed to express uncertainty. For a fuzzy number, the degree of the membership is a crisp number whereas the degree of the membership for an interval-valued fuzzy number is an interval. To grasp the vagueness more precisely, we employ interval-valued fuzzy numbers to represent the ratings and weights of the evaluation instead of traditional fuzzy numbers. The purpose of this thesis hopes to improve the quality of decision making by the application of the interval-valued fuzzy number approach. One of the merits of our method compared to the traditional fuzzy methods is that our method can express the uncertainty more precisely in the evaluation process. Beside, we propose a new ranking method for interval-valued fuzzy numbers.
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ZHANG, YU-GI, and 張玉琪. "Resolution of the compositie interval-valued fuzzy relation equations." Thesis, 1989. http://ndltd.ncl.edu.tw/handle/11237714159472057531.
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Li, Teng-shun, and 李登順. "Evaluating Students’ Answerscripts Based on Interval-Valued Intuitionistic Fuzzy Sets." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/64kp43.
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碩士國立臺灣科技大學
資訊工程系
100
In recent years, some methods have been presented for students’ answerscripts evaluation base on fuzzy sets. In this thesis, we present a new method for evaluating students’ answerscripts based on interval-valued intuitionistic fuzzy sets, where the fuzzy marks awarded to the answers of students’answerscripts are represented by interval-valued intuitionistic fuzzy sets. In the proposed method, we use two parameters to evaluate students’ answerscripts, where the one is the index of optimism determined by an evaluator indicating the degree of the optimistic of the evaluator. The larger the value of , the more the optimistic of the evaluator; the other one is the index of uncertainty denoting the degree of uncertainty of an interval-valued intuitionistic fuzzy mark. The larger the value of , the more the uncertainty of an interval-valued intuitionistic fuzzy mark. The proposed method can overcome the drawbacks of the existing methods for students’ answerscripts evaluation. Moreover, we also present a generalized method for students’ answerscripts evaluation using interval-valued intuitionistic fuzzy sets. The proposed methods can evaluate students’ answerscripts in a more flexible and more intelligent manner.
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Tzu-JungChen and 陳姿蓉. "Using Goal Programming to Establish Interval-valued Fuzzy Regression Models." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/61553681569026774027.
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Yang, Ming-wey, and 楊明煒. "New Methods for Fuzzy Multiple Attributes Group Decision Making Based on Ranking Interval Type-2 Fuzzy Sets and Multicriteria Fuzzy Decision Making Based on Ranking Interval-Valued Intuitionistic Fuzzy Values." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/86948971640696340099.
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碩士國立臺灣科技大學
資訊工程系
99
In recent years, some researchers proposed fuzzy multiple attributes group decision making methods based on ranking interval type-2 fuzzy sets. In this thesis, we present a new method for fuzzy multiple attributes group decision making based on ranking interval type-2 fuzzy sets. First, we present a new method for ranking interval type-2 fuzzy sets. Then, we present a new method for multiple attributes group decision making based on the proposed ranking method of interval type-2 fuzzy sets. In this thesis, we also present a new method for multicriteria fuzzy decision making based on ranking interval-valued intuitionistic fuzzy sets, where interval-valued intuitionistic fuzzy values are used to represent evaluating values of the decision-maker with respect to alternatives. First, we propose a new method for ranking interval-valued intuitionistic fuzzy values. Based on the proposed fuzzy ranking method of interval-valued intuitionistic fuzzy values, we propose a new method for multicriteria fuzzy decision making. The methods presented in this thesis provide us useful ways for dealing with fuzzy multiple attributes group decision making problems and multicriteria fuzzy decision making problems.
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Liao, Z.-Han, and 廖姿涵. "On similarity, inclusion and entropy measures between interval-valued fuzzy sets." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/88412490306171034612.
Full textAbstract:
碩士中原大學
應用數學研究所
103
Interval-valued fuzzy sets (IVFSs) are an extension of fuzzy sets. Since IVFSs present fuzzy sets with interval-valued memberships, they could have more widely for uncertainty modeling than fuzzy sets and are also easier to handle in practice than type-2 fuzzy sets. It is known that similarity, inclusion and entropy are the three important measures for fuzzy concepts. In this paper, we first propose new inclusion measures for IVFSs. We then derive similarity measures between IVFSs based on these inclusion measures. Furthermore, we take a weighted average of these two similarity measures between IVFSs and then construct new entropy measures for IVFSs. Some properties of these new similarity, inclusion and entropy measures between IVFSs are made. We also make numerical comparisons of the proposed measures with some existing measures. These comparison results show the superiority of the proposedmeasures.
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Lin, Chih-Chi, and 林芝騏. "A Study on Fuzzy Weights Regression Models for Interval-valued Data." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/50164801037850664804.
Full textAbstract:
碩士國立宜蘭大學
電機工程學系碩士班
103
This research plan presents a fuzzy weights regression model algorithm for the interval data which contain the uncertain nature and huge amount. Comparing with the past regression model algorithm, the fuzzy weights model’s predict part adopts fuzzy c-means method for interval data to cluster classification the input and output data of system, and use the input variables membership fuzzy operator for the input vector. Finally, combine fuzzy weights mechanism with triangular membership functions and regression model to produce outputs. The study uses artificial functional equations and real share price to verify the results shows that the fuzzy weights regression model algorithm has better effect.
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Tsao, Dun Chi, and 曹惇淇. "Assessing Objective and Integrated Weights Based on Interval-valued Fuzzy Sets." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/85946779276423040606.
Full textAbstract:
碩士長庚大學
工商管理學系
98
In Multiple Criteria Decision Making (MCDM), it is important to properly assess the attribute weight, because different weight result would often cause entirely different decision result. In the recent decades, IVFS was proposed and applied to the MCDM, allowing the decision maker to obtain a more accurate and realistic information. It is, nevertheless, often creating more uncertainty to the given information to some extent. Hence, to allow the decision maker to make an accurate and prompt judgment from the given information, the criteria weight based on the credibility of data has became very significant. However, there is only little investigation on MCDM with the credibility of data being explicitly taken into account in the past. In our research, we propose a new objective weight method by using IVFS entropy measures, in combination with the objective weight based on the discrete of data and subjective weight, to develop a novel integrated weigh. This new proposed model minimize, at least reduce, the inaccuracies that a decision maker may be encountered while evaluating, in the wider spectrum, the experiences of the decision maker as well as the information provided. This research, based on the IVFS, preformed a comprehensive screening among the four weights. The first category is to make use of the three formulas that has the most distinctive result from objective weight based on the credibility of data. Secondly, to employ the most frequent used Shannon’s Entropy Method and Standard Deviation Method from objective weight based on the discrete of data. Thirdly, to use of C-OWA that fits into IVFS features in our research. Lastly, to derive and propose a novel weight method according to the above mentioned methods, which is classified as forth group. In our research, we applied these four groups that have seven weights, into SAW and TOPSIS to evaluate the quality of the weight standard, as well as to assess the results derived from the former evaluation methods. Finally, our research assess the above mentioned seven weight formulas along with various decision matrix by performing Spearman correlation coefficients, it was shown that the formulas under the decision matrix conditions of various criteria and alternatives resulting in a similar tendency. These include Spearman correlation coefficients of the weight method of first and forth group and the Shannon’s Entropy Method from the second group, which can decrease as the criteria and alternatives increases. In the contrary, the weight methods from first and forth groups and the Standard Deviation Methods from second group rises as the coefficient increases. However, the third group and other weight methods have ambiguously tendency as the criteria and alternative increases.
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Wang, Cheng-Yi, and 王正一. "New Methods for Multiple Attribute Decision Making Based on Interval Type-2 Fuzzy Sets and Interval-Valued Intuitionistic Fuzzy Sets." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/p8h57q.
Full textAbstract:
博士國立臺灣科技大學
資訊工程系
105
Many multiple attribute decision making problems in the real-world become more uncertain and more complex. In recent years, multiple attribute decision making based on interval type-2 fuzzy sets and interval-valued intuitionistic fuzzy sets become important research topics. In this dissertation, we propose three new multiple attribute decision making methods based on interval type-2 fuzzy sets and interval-valued intuitionistic fuzzy sets, respectively, where (1) we propose a new multiple attribute decision making method based on ranking interval type-2 fuzzy sets and the -cuts of interval type-2 fuzzy sets, (2) we propose a new multiple attribute decision making method based on interval-valued intuitionistic fuzzy sets, the linear programming methodology and the extended technique for order preference by similarity to ideal solution (TOPSIS) method, where the ratings of the attributes of alternatives and the weights of attributes are represented by interval-valued intuitionistic fuzzy values and the linear programming methodology is used to obtain optimal weights of attributes, and (3) we propose an improved multiple attribute decision making method based on the proposed new score function of interval-valued intuitionistic fuzzy sets and the linear programming methodology. The experimental results show that the proposed multiple attribute decision making methods can overcome the drawbacks of the existing methods, where the existing methods have the drawbacks that they get unreasonable preference orders of the alternatives in some situations and they cannot get the preference order of the alternatives in some situations. The proposed methods provide us with a very useful way for multiple attribute decision making in interval type-2 fuzzy environments and interval-valued intuitionistic fuzzy environments, respectively.
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Huang, Zhi-Cheng, and 黃智呈. "Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Values and the Linear Programming Methodology." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/52333321606816666877.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
104
In recent years, some methods have been presented based on interval-valued intuitionistic fuzzy sets for multiattribute decision making. In this thesis, we propose a new multiattribute decision making method based on interval-valued intuitionistic fuzzy values and the linear programming methodology. The weights of attributes and the evaluating values of alternatives are represented by interval-valued intuitionistic fuzzy values. The proposed method has the advantage that it is simpler than the existing methods for multiattribute decision making in interval-valued intuitionistic fuzzy environments. The proposed method provides us with a very useful way for multiattribute decision making in interval-valued intuitionistic fuzzy environments.
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Tu, Chien-Cheng, and 涂謙誠. "Developing Measures and Interval-valued Ranking Functions based on Intuitionistic Fuzzy Sets." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/65411101817373918696.
Full textAbstract:
博士國立成功大學
工業與資訊管理學系
102
Measures of intuitionistic fuzzy sets (IFSs), such as subsethood, cardinality, distance, similarity, correlation, and evaluation functions, are often used in application problems. The interval-valued data used by IFSs can express the comprehensive uncertainty of IFSs. However, the ranking of interval-valued intuitionistic fuzzy sets (IvIFSs) is difficult since they include the interval values of membership and non-membership. This research investigates such measures of IFS and ranking functions for IvIFSs from various perspectives. Firstly, based on the relative relations of an IFS to other IFSs, four functions, namely superiority, non-inferiority, determinacy, and non-hesitancy, are constructed, which consist of dual bipolar scales, namely (superiority, non-inferiority) and (determinacy, non-hesitancy). Then, the proposed measures of IFSs are axiomatically defined using the dual bipolar scales. Geometrical demonstrations in general show consistency between the proposed measures and existing ones. Secondly, the proposed ranking functions consider the degree to which an IvIFS dominates and is not dominated by other IvIFSs. Based on the bivariate framework and the dominance concept, the functions incorporate not only the boundary values of membership and non-membership, but also the relative relations among IvIFSs in comparisons. The relationship for two IvIFSs that satisfy the dual couple is defined based on four proposed ranking functions. Importantly, the five proposed ranking functions can achieve a full ranking for all IvIFSs. Therefore, the proposed measures and ranking functions can highlight the significant features of IFSs and IvIFSs. In addition, the attitude of decision-makers is also implanted in measures of IFSs and ranking functions of IvIFSs to allocate the importance in the dual bipolar scales and the various kinds of dominance respectively. Four examples are used to demonstrate the applicability and performance of the proposed measures of IFSs and ranking functions of IvIFSs.
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Tsai, Wei-Hsiang, and 蔡瑋詳. "New Methods for Multiple Attribute Decision Making and Multiple Attribute Group Decision Making Based on Interval-Valued Intuitionistic Fuzzy Geometric Averaging Operators and Interval-Valued Intuitionistic Fuzzy Aggregation Operators." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/45295607437554629656.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
103
Multiple attribute decision making and multiple attribute group decision making based on interval-valued intuitionistic fuzzy sets are important research topic. In this thesis, we propose a new multiple attribute decision making method based on the proposed interval-valued intuitionistic fuzzy geometric averaging operators. First, we propose the interval-valued intuitionistic fuzzy weighted geometric averaging (IVIFWGA) operator, the interval-valued intuitionistic fuzzy ordered weighted geometric averaging (IVIFOWGA) operator and the interval-valued intuitionistic fuzzy hybrid geometric averaging (IVIFHGA) operator based on the proposed multiplication operator between interval-valued intuitionistic fuzzy values and the proposed power operator of an interval-valued intuitionistic fuzzy value. Based on the proposed IVIFWGA operator, IVIFOWGA operator and the IVIFHGA operator, we also propose a new method for multiple attribute decision making. The experimental results show that the proposed multiple attribute decision making method can overcome the drawbacks of the existing multiple attribute decision making methods. It provides us with a useful way for multiple attribute decision making in interval-valued intuitionistic fuzzy environments. Moreover, we propose the interval-valued intuitionistic fuzzy weighted averaging (IVIFWA) operator, the interval-valued intuitionistic fuzzy ordered weighted averaging (IVIFOWA) operator and the interval-valued intuitionistic fuzzy hybrid averaging (IVIFHA) operator based on the proposed addition operator between interval-valued intuitionistic fuzzy values. Based on the proposed IVIFWA operator, IVIFOWA operator and the IVIFHA operator, we also propose a new method for multiple attribute group decision making. The experimental results show that the proposed multiple attribute group decision making method can overcome the drawbacks of the existing methods. It provides us with a useful way for multiple attribute group decision making in interval-valued intuitionistic fuzzy environments.
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KUO, RICHARD, and 郭禮維. "New Methods for Autocratic Decision Making Using Group Recommendations Based on Interval Type-2 Fuzzy Sets and Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Values." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/4b6mf6.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
106
In this thesis, we propose a new method for multiattribute group decision making based on interval type-2 fuzzy sets and propose a new method for multiattribute decision making based on interval-valued intuitionistic fuzzy values. The proposed first method deals with autocratic decision making using group recommendations based on interval type-2 fuzzy sets, enhanced Karnik-Mendel algorithms and the ordered weighted aggregation operator, where both the evaluating matrices and the weighting vectors of the attributes given by the decision makers are evaluated by linguistic terms represented by interval type-2 fuzzy sets. It automatically modifies the weights of the decision makers until the group consensus degree is larger than or equal to a predefined consensus threshold value. It can overcome the shortcomings of the existing methods and can provide us with a very useful way for autocratic decision making using group recommendations in interval type-2 fuzzy environments. The proposed second method deals with multiattibute decision making based on interval-valued intuitionistic fuzzy values and the non-linear programming methodology with the hyperbolic tangent function, where both the decision matrix and the weights of the attributes are represented by interval-valued intuitionistic fuzzy values. First, it constructs the transformed decision matrix of the decision matrix. Then, it constructs a non-linear programming model with the hyperbolic tangent function to get the optimal weights of the attributes. Then, it uses the interval-valued intuitionistic fuzzy weighted averaging operator to calculate the weighted evaluating interval-valued intuitionistic fuzzy values of the alternatives. Finally, it compares the obtained weighted evaluating interval-valued intuitionistic fuzzy values to obtain the preference order of the alternatives. It can overcome the drawbacks of the existing multiattibute decision making method.
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Lai, Hung Lin, and 賴虹霖. "A decision support method of risk analysis based on interval-valued fuzzy numbers." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/15516040025142799974.
Full textAbstract:
博士長庚大學
企業管理研究所博士班
101
Risk analysis is a very important issue for an organization, especially in the decision-making process. However, there are many uncertainties in risk management. In uncertain and complex situations, making choices may be difficult for decision makers. For these reasons, in this dissertation, I analyze risks in linguistic terms and based on interval-valued fuzzy numbers (IVFNs), which may better address linguistic uncertainties in complex situations. I develop methods for solving decision-making problems in a fuzzy environment. To make organizational decisions based on multiple criteria, I develop a method that extends the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach by calculating degrees of similarity between the ideal and the negative ideal solutions simultaneously. Most studies related to TOPSIS based on fuzzy theory measure the distance between the alternatives and the positive/negative ideal solution. Rather than adopting this approach, in this dissertation, I develop a method to measure the similarity between the IVFNs of the alternatives and the positive ideal solution/negative ideal solution, which may lead to more intuitive results than measuring the distance. Based on applications in different types of organizations, I find that using the proposed method can make the decision-making process easier and more consistent for decision makers. Moreover, all of the calculations in the proposed method can be written into a decision support system that would simplify the decision-making process. The decision maker only has to input opinions in linguistic terms into the decision support system.
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Pan, Ying, and 潘穎. "The Extension of PROMETHEE Decision Making Method under Interval-Valued Intuitionistic Fuzzy Environment." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/02763895550890012604.
Full textAbstract:
碩士長庚大學
工商管理學系
101
In the past, research pertaining to the fuzzy preference ranking organization method for enrichment evaluation F-PROMETHEE, linguistic data has been chiefly transformed into triangular fuzzy numbers (TFNs). Different from a TFN, the interval-valued intuitionistic fuzzy (IVIF) number is able to more completely present its natural features. In addition, in specific contexts, we can also consider some uncertainty elements by using IVIF numbers. This study expresses the input data as IVIF sets which are applied within the framework of PROMETHEE. First, decision makers (DMs) need to evaluate the alternatives with respect to each criterion; then, these alternatives are switched from linguistic numbers into IVIF numbers. The weights of the criteria are also expressed as IVIF sets switched from a linguistic scale. The linguistic scales used in our study are modified from earlier works in the literature. Notably, the main spirit of PROMETHEE involves deviations among the alternatives. The parameters are taken from a pair-wise comparison of alternatives corresponding to the thresholds of the preference function. After integrating the weights of the criteria, we can obtain the final partial outranking by PROMETHEE I and a complete outranking by PROMOTHEE II. This study considers the opinions of the DMs, who provide data with respect to each alternative. With the use of IVIF linguistic scales, the intensities of the alternative weights can be described. In order to outrank the alternatives, an IVIF score function is used to avoid specific difficulties when comparing IVIF numbers. This study exemplifies two cases which both can be applied within the IVIF environment. Both cases investigate IVIF-weight and IVIF-PROMETHEE, respectively. Therefore, this study confirms that the cooperation of IVIF-weight and IVIF-PROMETHEE is feasible in this context.
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Chen, Jim-Ho, and 陳進和. "New Methods for Fuzzy Risk Analysis Based on Ranking Generalized Fuzzy Numbers and Similarity Measures between Interval-Valued." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/3h94qt.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
95
In this thesis, we present two methods for fuzzy risk analysis based on ranking generalized fuzzy numbers and similarity measures between interval-valued fuzzy numbers. First, we present a new method for ranking generalized fuzzy numbers for handling fuzzy risk analysis problems. The proposed method considers defuzzified values, the weight and the spreads of generalized fuzzy numbers. Moreover, we also apply the proposed method for ranking generalized fuzzy numbers to present a new method for dealing with fuzzy risk analysis problems. Then, we present a new similarity measure for interval-valued fuzzy numbers. The proposed similarity measure considers five factors, i.e., the degree of similarity on X-axis between the upper fuzzy numbers of the interval-valued fuzzy numbers, the degree of similarity about the weight of the upper fuzzy numbers of the interval-valued fuzzy numbers, the spread between the upper fuzzy numbers of the interval-valued fuzzy numbers, the degree of similarity on the X-axis between the interval-valued fuzzy numbers, and the degree of similarity on the Y-axis between the interval-valued fuzzy numbers. Moreover, we also present new interval-valued fuzzy numbers arithmetic operators and apply the proposed similarity measure to present a new method for dealing with fuzzy risk analysis problems based on interval-valued fuzzy numbers. The proposed fuzzy risk analysis methods provide us a useful way for handling fuzzy risk analysis problems.
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Sanguansat, Kata, and 陳凱恬. "Handling Fuzzy Risk Analysis Based on A New Method for Ranking Generalized Fuzzy Numbers and A New Similarity Measure between Interval-Valued Fuzzy Numbers." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/44077683722827804598.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
97
In this thesis, we present two new methods for dealing with fuzzy risk analysis problems. We propose a fuzzy risk analysis algorithm based on a new method for ranking generalized fuzzy numbers and propose a fuzzy risk analysis algorithm based on a new similarity measure between interval-valued fuzzy numbers. First, we present a new method for ranking generalized fuzzy numbers. The proposed fuzzy ranking method considers the areas on the positive side, the areas on the negative side and the heights of the generalized fuzzy numbers to evaluate ranking scores of the generalized fuzzy numbers. We also prove the properties of the proposed fuzzy ranking method and show that it can overcome the drawbacks of the existing fuzzy ranking methods. Then, we apply the proposed method for ranking generalized fuzzy numbers to develop a new method for dealing with fuzzy risk analysis problems. Moreover, we also present a new similarity measure between interval-valued fuzzy numbers. The proposed method considers the degrees of closeness between interval-valued fuzzy numbers on the X-axis and the degrees of differences between the shapes of the interval-valued fuzzy numbers on the X-axis and the Y-axis, respectively. We also prove three properties of the proposed similarity measure and make an experiment to compare the experimental results of the proposed method with the existing similarity measures between interval-valued fuzzy numbers. Based on the proposed similarity measure between interval-valued fuzzy numbers, we present a new fuzzy risk analysis algorithm for dealing with fuzzy risk analysis problems. The proposed algorithm is more flexible than Chen and Chen’s method due to the fact that Chen and Chen’s method lacks the capability to let the evaluating values of the risk of each sub-component for fuzzy risk analysis to be represented by interval-valued fuzzy numbers.
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Lan, Chung Kai, and 藍宗凱. "Applying Continuous Ordered Weighted Averaging Operator to Hierarchical Decision Methods based on Interval-valued Fuzzy Preference Relations." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/84869608746806538941.
Full textAbstract:
碩士長庚大學
工商管理學系
98
Multiple criteria decision making often faced with inaccurate information and changing circumstances. Therefore, Zadeh and Sambuc developed interval-valued fuzzy sets in 1975; it can express the degree of membership in uncertainty. In addition, when we face the highly complexity and large-scale decision making problems, we often simplify the problem by using the hierarchical structure. Over the past literature on the hierarchy structure are based on multiple preference relations to express the preference of decision makers, and most of methods needed to satisfy the transitivity of preferences and consistency test. However, because of human subjective judgments often partical order in practical problems, so the consistency or transitivity of preferences does not exist frequently. Therefore, this study uses interval-valued additive preference relations as a basis for pairwise comparisons. It can solve preference inconsistency or independent of criteria in decision matrix. Operating the hierarchical structure or normal decision making methods, we often applied to the weighted averaging operator to obtain the priority vectors. Yager extends the OWA operator in 2004; introduce a continuous ordered weighted averaging (C-OWA) operator. C-OWA operator is focus on the interval data to derive the priority vector and ranks according to the priority vectors. This study develops four different type hierarchical structures: completely-connected, independenty criteria, partially-connected and hybrid-connected hierarchical structure. Using C-OWA operator give every type structure formula in easily and efficiency. This study use C-OWA operator to apply to portfolio investment evalution and supplier selection of practical examples. Using portfolio investment evalution example to describes completely-connected and partially-connected hierarchical structures, in addition, using supplier selection example to describes independenty criteria and hybrid-connected hierarchical structures. Finally, this study develops suitable structure to solve different type problems and verify the feasibility of this study.
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Lin, Kuan-Hung, and 林冠宏. "A Study of Feasibility Evaluation on Application Domain of Cloud Computing Service based on Interval-valued Fuzzy AHP." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/66467798859012856933.
Full textAbstract:
碩士國立聯合大學
管理碩士學位學程
98
Due to the rapid development of information and Internet technologies, the cloud computing which combined Internet architecture with high-speed computation ability is provided to meet the requirements of organizations. Recently, many enterprises consider to adjust traditional information services model gradually and transform into cloud computing services model because the benefits of cloud computing service. However, the application domains or industries need the cloud computing services are different from their characteristics. Therefore, the cloud computing suppliers should evaluate the feasibility for each application effectively before developed the services. From the viewpoint of service innovation and service value, many influence factors and indices are collected in this study to measure the feasibility of cloud computing service. The feasibility evaluation should consider both qualitative and quantitative factors simultaneously. In the evaluation process, decision makers are often can not provide the crisp evaluation because their judgments are always subjective and vagueness. Under this situation, interval-valued fuzzy sets are suitable used to represent the fuzziness of membership value of their opinions, and to reduce the uncertain and fuzziness in the evaluation process. Therefore, fuzzy interval linguistic variables and interval-valued fuzzy AHP are applied to construct the feasibility evaluation model of cloud computing service. According to the evaluation model, an interactive feasibility evaluation system is designed and developed on the Google App Engine cloud computing platform to enhance the practical value of the proposed model in this study. Using factor analysis, there are four dimensions and thirteen indices are included in the evaluation architecture. Additionally, four application domains such as the education industry, medical industry, financial industry, and logistics industry are evaluated and analyzed in this study. The results showed that the most important dimension is “system quality”, and the highest feasibility domain is “financial industry”.
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Chen, Ju Ling, and 陳茱玲. "Using Interval-valued Fuzzy Numbers and TOPSIS to Develop Group Decision-making Methods and Discussions on Linguistic Conversion Standards." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/43055618178073866912.
Full textAbstract:
碩士長庚大學
工商管理學系
99
With the fast development of times, how to rapidly acquire many decision-makers’ opimions of different evaluation criteria is a very important task. There are many criteria usually related to decision-maker’s personal feelings. Hence, how to convey different decision-makers’ feeling and opinions in detail at the same time is another important issue. In the past, mant scholars used linguistic variables to transfer decision-maker’s opinions and weights. However, different linguistic variables transformation standards usually showed differences decision makers’ opinions and data. Moreover, many transformation standards were generalized fuzzy numbers rather than interval-valued fuzzy numbers (IVFN). Therefore, this study would use TOPSIS, which is easy to calculate and which inclue many decision-maker’ opinions and weights. And using linguistic variables of IVFN to transfer decision-maker’s opinions of criteria and weights, which can express decision-maker’s opinions more detail and then making the decision-making problems more easily to be solved. This research will first review literatures about TOPSIS method, fuzzy TOPSIS method and group decision-making. And new linguistic variables of IVFN relying on literatures of linguistic variables are presented as well. After various decision-makers’ opinions and weights are transferred based on linguistic variables of IVFN, the matrix would be further normalized. By considering the difference importance of each criterion, the researcher constructs the weighted normalized fuzzy decision matrix. According to the distance of IVFN, the researcher calculates the distance between alternatives and the ideal (also negative-ideal) solutions. Then, with using closeness coefficient, the value of each alternative is finally ranked.Finally, we use other linguistic variables of general fuzzy number to transfer into linguistic variables of IVFN, and discuss the result with Spearman correlation coefficient. This research combines and discussion about group decision making, Fuzzy TOPSIS method and IVFN, and using the linguistic variable to converse another linguistic variable of IVFN with five-point scale. Then, with using the Spearman correlation coefficient comparison between the ranks of the alternatives, so that decision-makers in the complex environment for decision-making judgments of data can be more detailed, and they can get closer to the answers.
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Fan, Kang-Yun, and 范綱允. "Multiattribute Decision Making Based on Probability Density Functions and the Variances and Standard Deviations of Largest Ranges of Evaluating Interval-Valued Intuitionistic Fuzzy Values." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/fdk9sz.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
107
In this thesis, we propose a new multiattribute decision making method based on probability density functions and the variances and standard deviations of the largest ranges of evaluating interval-valued intuitionistic fuzzy values. First, the proposed method obtains the largest range of each evaluating interval-valued intuitionistic fuzzy value in the decision matrix provided by the decision maker. Then, it computes the average value of the largest ranges of each attribute. Then, it obtains the probability density function of the largest range of each evaluating interval-valued intuitionistic fuzzy value appearing in the decision matrix. Then, it computes the variance of each largest range and calculates the standard deviation of the largest ranges of each attribute. Then, it builds the z-score decision matrix based on the obtained largest range of each evaluating interval-valued intuitionistic fuzzy value appearing in the decision matrix, the obtained average value of the largest ranges of each attribute and the obtained standard deviation of the largest ranges of each attribute. Then, it gets the transformed weight of the interval-valued intuitionistic fuzzy weight of each attribute. Finally, it computes the weighted score of each alternative based on the obtained z-score decision matrix and the transformed weight of the interval-valued intuitionistic fuzzy weight of each attribute. The larger the value of the weighted score, the better the preference order of the alternative. The proposed multiattribute decision making method can conquer the shortcomings of the existing multiattribute decision making methods. It provides us with a very useful way for multiattribute decision making in interval-valued intuitionistic fuzzy environments.
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Kuo, Che-Ting, and 郭哲廷. "A Modified Water Flow-like Algorithm for TSK-type Interval-valued Neural Fuzzy System Design and Its Application in Blind Source Separation." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/36250888559703109908.
Full textAbstract:
碩士元智大學
電機工程學系
98
Based on the water flow-like algorithm (WFA), we propose a novel hybrid learning algorithm: the modified water flow-like algorithm (MWFA) for TSK-type interval-valued neural fuzzy system with asymmetric membership function (TIVNFS-A) design. The WFA is inspired from the natural behavior of the water flows. For finding the global optimum in the solution space, the splitting, moving, merging, evaporation, and precipitation operations have been adopted. The WFA has global search ability and has dynamic solution agents. However, the original WFA is not suited to the continuous solution space due to the strategies. Therefore, we propose the MWFA for the continuous solution space. We propose the novel moving strategies by applying the tabu search algorithm and BP to improve the performance and enhance the strategies in evaporation and precipitation operations. These enhanced strategies in evaporation and precipitation evaporation are more consistent with the natural behavior of water flows and increase the diversity of solution agents. Therefore, we use the MWFA to train the TIVNFS-A, identify the performance by the example of nonlinear system identification and design a novel approach for solving the blind source separation (BSS) problem.
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Beisler, Matthias Werner. "Modelling of input data uncertainty based on random set theory for evaluation of the financial feasibility for hydropower projects." Doctoral thesis, 2010. https://tubaf.qucosa.de/id/qucosa%3A22775.
Full textAbstract:
The design of hydropower projects requires a comprehensive planning process in order to achieve the objective to maximise exploitation of the existing hydropower potential as well as future revenues of the plant. For this purpose and to satisfy approval requirements for a complex hydropower development, it is imperative at planning stage, that the conceptual development contemplates a wide range of influencing design factors and ensures appropriate consideration of all related aspects.
Since the majority of technical and economical parameters that are required for detailed and final design cannot be precisely determined at early planning stages, crucial design parameters such as design discharge and hydraulic head have to be examined through an extensive optimisation process.
One disadvantage inherent to commonly used deterministic analysis is the lack of objectivity for the selection of input parameters. Moreover, it cannot be ensured that the entire existing parameter ranges and all possible parameter combinations are covered.
Probabilistic methods utilise discrete probability distributions or parameter input ranges to cover the entire range of uncertainties resulting from an information deficit during the planning phase and integrate them into the optimisation by means of an alternative calculation method.
The investigated method assists with the mathematical assessment and integration of uncertainties into the rational economic appraisal of complex infrastructure projects. The assessment includes an exemplary verification to what extent the Random Set Theory can be utilised for the determination of input parameters that are relevant for the optimisation of hydropower projects and evaluates possible improvements with respect to accuracy and suitability of the calculated results.Die Auslegung von Wasserkraftanlagen stellt einen komplexen Planungsablauf dar, mit dem Ziel das vorhandene Wasserkraftpotential möglichst vollständig zu nutzen und künftige, wirtschaftliche Erträge der Kraftanlage zu maximieren. Um dies zu erreichen und gleichzeitig die Genehmigungsfähigkeit eines komplexen Wasserkraftprojektes zu gewährleisten, besteht hierbei die zwingende Notwendigkeit eine Vielzahl für die Konzepterstellung relevanter Einflussfaktoren zu erfassen und in der Projektplanungsphase hinreichend zu berücksichtigen. In frühen Planungsstadien kann ein Großteil der für die Detailplanung entscheidenden, technischen und wirtschaftlichen Parameter meist nicht exakt bestimmt werden, wodurch maßgebende Designparameter der Wasserkraftanlage, wie Durchfluss und Fallhöhe, einen umfangreichen Optimierungsprozess durchlaufen müssen. Ein Nachteil gebräuchlicher, deterministischer Berechnungsansätze besteht in der zumeist unzureichenden Objektivität bei der Bestimmung der Eingangsparameter, sowie der Tatsache, dass die Erfassung der Parameter in ihrer gesamten Streubreite und sämtlichen, maßgeblichen Parameterkombinationen nicht sichergestellt werden kann. Probabilistische Verfahren verwenden Eingangsparameter in ihrer statistischen Verteilung bzw. in Form von Bandbreiten, mit dem Ziel, Unsicherheiten, die sich aus dem in der Planungsphase unausweichlichen Informationsdefizit ergeben, durch Anwendung einer alternativen Berechnungsmethode mathematisch zu erfassen und in die Berechnung einzubeziehen. Die untersuchte Vorgehensweise trägt dazu bei, aus einem Informationsdefizit resultierende Unschärfen bei der wirtschaftlichen Beurteilung komplexer Infrastrukturprojekte objektiv bzw. mathematisch zu erfassen und in den Planungsprozess einzubeziehen. Es erfolgt eine Beurteilung und beispielhafte Überprüfung, inwiefern die Random Set Methode bei Bestimmung der für den Optimierungsprozess von Wasserkraftanlagen relevanten Eingangsgrößen Anwendung finden kann und in wieweit sich hieraus Verbesserungen hinsichtlich Genauigkeit und Aussagekraft der Berechnungsergebnisse ergeben.