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Relevant bibliographies by topics / Fuzzy rough sets / Dissertations / Theses

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Dissertations / Theses on the topic 'Fuzzy rough sets'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Jensen, Richard. "Combining rough and fuzzy sets for feature selection." Thesis, University of Edinburgh, 2004. http://hdl.handle.net/1842/24740.

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Feature selection (FS) refers to the problem of selecting those input attributes that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition and signal processing. Unlike other dimensionality reduction methods, feature selectors preserve the original meaning of the features after reduction. This has found application in tasks that involve datasets containing huge numbers of features (in the order of tens of thousands), which would be impossible to process further. Recent examples include text processing and web content classifi

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2

Vural, Hulya. "Comparison Of Rough Multi Layer Perceptron And Rough Radial Basis Function Networks Using Fuzzy Attributes." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605293/index.pdf.

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The hybridization of soft computing methods of Radial Basis Function (RBF) neural networks, Multi Layer Perceptron (MLP) neural networks with back-propagation learning, fuzzy sets and rough sets are studied in the scope of this thesis. Conventional MLP, conventional RBF, fuzzy MLP, fuzzy RBF, rough fuzzy MLP, and rough fuzzy RBF networks are compared. In the fuzzy neural networks implemented in this thesis, the input data and the desired outputs are given fuzzy membership values as the fuzzy properties &ldquo<br>low&rdquo<br>, &ldquo<br>medium&rdquo<br>and &ldquo<br>high&rdquo<br>. In the roug

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3

Ferone, A. "EXPLOITING HIGHER ORDER UNCERTAINTY IN IMAGE ANALYSIS." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155479.

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Soft computing is a group of methodologies that works synergistically to provide flexible information processing capability for handling real-life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability, robustness, and low-cost solutions. Soft computing methodologies (involving fuzzy sets, neural networks, genetic algorithms, and rough sets) have been successfully employed in various image processing tasks including image segmentation, enhancement and classification, both individually or

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4

Lee, Chang Su. "A framework of adaptive T-S type rough-fuzzy inference systems (ARFIS)." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0192.

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[Truncated abstract] Fuzzy inference systems (FIS) are information processing systems using fuzzy logic mechanism to represent the human reasoning process and to make decisions based on uncertain, imprecise environments in our daily lives. Since the introduction of fuzzy set theory, fuzzy inference systems have been widely used mainly for system modeling, industrial plant control for a variety of practical applications, and also other decisionmaking purposes; advanced data analysis in medical research, risk management in business, stock market prediction in finance, data analysis in bioinforma

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5

Khuman, Arjab Singh. "The quantification of perception based uncertainty using R-fuzzy sets and grey analysis." Thesis, De Montfort University, 2016. http://hdl.handle.net/2086/14225.

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The nature of uncertainty cannot be generically defined as it is domain and context specific. With that being the case, there have been several proposed models, all of which have their own associated benefits and shortcomings. From these models, it was decided that an R-fuzzy approach would provide for the most ideal foundation from which to enhance and expand upon. An R-fuzzy set can be seen as a relatively new model, one which itself is an extension to fuzzy set theory. It makes use of a lower and upper approximation bounding from rough set theory, which allows for the membership function of

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6

Oukbir, Karim. "Indiscernibility and Vagueness in Spatial Information Systems." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3634.

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<p>We investigate the use of the concept of indiscernibilityand vagueness in spatial information systems. To representindiscernibility and vagueness we use rough sets, respectivelyfuzzy sets. We introduce a theoretical model to supportapproximate queries in information systems and we show howthose queries can be used to perform uncertain classi.cations.We also explore how to assess quality of uncertainclassi.cations and ways to compare those classi.cations to eachother in order to assess accuracies. We implement the querylanguage in an SQL relational language to demonstrate thefeasibility of a

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7

Davault, Julius Mack III. "Resolving Quasi-Synonym Relationships in Automatic Thesaurus Construction using Fuzzy Rough Sets and an Inverse Term Frequency Similarity Function." NSUWorks, 2009. http://nsuworks.nova.edu/gscis_etd/129.

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One of the problems associated with automatic thesaurus construction is with determining the semantic relationship between word pairs. Quasi-synonyms provide a type of equivalence relationship: words are similar only for purposes of information retrieval. Determining such relationships in a thesaurus is hard to achieve automatically. The term vector space model and an inverse term frequency similarity function can provide a way to automatically determine the similarity between words in thesaurus. A thesaurus constructed using this method can also improve precision and recall in information ret

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8

Saltos, Atiencia Ramiro Javier. "Soft-clustering in static and dynamic environments." Tesis, Universidad de Chile, 2016. http://repositorio.uchile.cl/handle/2250/142058.

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Doctor en Sistemas de Ingeniería<br>En la actualidad, el entorno macro y micro económico en el cual op eran las empresas está cambiando constantemente y a gran velo cidad. Esto se deb e princip almente al auge de las nuevas tecnologías, la revolución de la información y la gran facilidad con la que ahora p o demos comu nicarnos con cualquier parte d el mundo. Debido a la gran canti dad de información que está siendo generada segundo tras segundo, junto con la facilidad con la que se puede acceder a ella, la minería de datos y la investigación de op eracion es se han convertido en una de l

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9

Keukelaar, J. H. D. "Topics in Soft Computing." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3294.

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10

Ahlqvist, Ola. "Context Sensitive Transformation of Geographic Information." Doctoral thesis, Stockholm : Univ, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-200.

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11

Chen, Ze-jin, and 陳澤金. "New Fuzzy Interpolative Reasoning Methods based on Piecewise Fuzzy Entropies of Fuzzy Sets, Piecewise Fuzzy Entropies of Rough-Fuzzy Sets and the Ratios of Fuzziness of Rough-Fuzzy Sets." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/70287632518485817267.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>102<br>Fuzzy interpolative reasoning is a very important research topic for sparse fuzzy rule-based systems. It can overcome the drawbacks of sparse fuzzy rule-based systems and can reduce the complexity of fuzzy rule bases for fuzzy rule-based systems. In this thesis, we propose two new fuzzy interpolative reasoning methods for sparse fuzzy rule-based systems based on type-1 fuzzy sets and rough-fuzzy sets, respectively. In the first method of our thesis, we propose a new method for weighted fuzzy interpolative reasoning based on piecewise fuzzy entropies of fuzzy s

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12

Chu, Hsiao-lan, and 朱筱嵐. "Applying Fuzzy Sets and Rough Sets Theories on Multi-Criteria Decision Making." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/81123517228237267059.

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碩士<br>義守大學<br>資訊管理學系碩士班<br>93<br>Decision-makers are often met with many decision-making problems which are complex and uncertain in daily life. Due to this, it is very difficult for them to make a proper selection or decision based on individual subjective judgement. With closer cooperation between the decision-makers and schemers, the actual demands of problems can be realized. Therefore, this study proposes a fuzzy decision-making method to evaluate non- quantitative fuzzy decision problems. First, when encountering decision-making problems of fuzzy multi-criteria, decision-makers evaluate

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13

Huang, Chun Chi, and 黃俊期. "Remote Manufacturing Process Diagnosis Using XML and Fuzzy Rough Sets." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/09408687646586938582.

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碩士<br>國立雲林科技大學<br>工業工程與管理研究所碩士班<br>90<br>With the advance of the technology and the high precision requirement of the product, the design of machines becomes more and more complicated, and their price is also expensive. When the machine is out of order, only the maintenance engineers of the original design company have ability to fix it up. In a modern factory, several sensors are mounted on a monitored machine to acquire the manufacturing parameters which are stored in a local database. It is inefficient that the maintenance engineers of the original design company must go to the shop floor o

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14

Correia, Artur Jorge da Silva. "O uso de metodologias baseadas em fuzzy sets e rough sets na recuperação de informação." Master's thesis, 2004. http://hdl.handle.net/10216/12988.

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Dissertação apresentada par obtenção parcial do grau de Mestre em Gestão da Informação, na Faculdade de Engenharia da Universidade do Porto, sob a orientação dos Professores Doutores Maria Cristina de Carvalho Alves Ribeiro e Manuel António Cerqueira da Costa Matos

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15

Correia, Artur Jorge da Silva. "O uso de metodologias baseadas em fuzzy sets e rough sets na recuperação de informação." Dissertação, 2004. http://hdl.handle.net/10216/12988.

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Dissertação apresentada par obtenção parcial do grau de Mestre em Gestão da Informação, na Faculdade de Engenharia da Universidade do Porto, sob a orientação dos Professores Doutores Maria Cristina de Carvalho Alves Ribeiro e Manuel António Cerqueira da Costa Matos

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16

Duan, Tong. "Towards a rough-fuzzy perception-based computing for vision-based indoor navigation." 2014. http://hdl.handle.net/1993/23689.

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An indoor environment could be defined by a complex layout in a compact space. Since mobile robots can be used as substitute for human beings to access harmful and inaccessible locations, the research of autonomous indoor navigation has attracted much interest. In general, a mobile robot navigates in an indoor environment where acquired data are limited. Furthermore, sensor measurements may contain errors in a number of situations. Therefore, the complexity of indoor environment and ability of sensors have determined that it is an insufficient to merely compute with data. This thesis presents

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17

Huang, Chun-lin, and 黃俊霖. "An Application of Rough Sets and Fuzzy Theorem to the Forecast of TX Fluctuation." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/33799352106455403972.

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碩士<br>國立臺灣科技大學<br>資訊管理系<br>92<br>After 1998 Taiwan Futures Exchange was established, and provided the futures transactions for compatriots. Now there are average 20,000~30,000 transactions on each trading day. This indicated that the futures market is in great demand. Besides, computer science and artificial intelligence can assist us to process mass information, especially decision support is very prevalent. This paper used rough sets theorem and fuzzy theorem to forecast the rank of TX price fluctuation. There are four methods of rough sets and fuzzy theorem adopted in

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