Relevant bibliographies by topics / Multi-Methods strategy

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Multi-Methods strategy'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Multi-Methods strategy"

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Čabala, Ján, and Ján Jadlovský. "Choosing the Optimal Production Strategy by Multi-Objective Optimization Methods." Acta Polytechnica Hungarica 17, no. 5 (2020): 7–26. http://dx.doi.org/10.12700/aph.17.5.2020.5.1.

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Li, Luoqing, Chuanwu Yang, and Qiwei Xie. "1D embedding multi-category classification methods." International Journal of Wavelets, Multiresolution and Information Processing 14, no. 02 (March 2016): 1640006. http://dx.doi.org/10.1142/s0219691316400063.

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In this paper, we propose a novel semi-supervised multi-category classification method based on one-dimensional (1D) multi-embedding. Based on the multiple 1D embedding based interpolation technique, we embed the high-dimensional data into several different 1D manifolds and perform binary classification firstly. Then we construct the multi-category classifiers by means of one-versus-rest and one-versus-one strategies separately. A weight strategy is employed in our algorithm for improving the classification performance. The proposed method shows promising results in the classification of handwritten digits and facial images.
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Wang, Mingshen, and Jenshou Yang. "A multi‐criterion experimental comparison of three multi‐attribute weight measurement methods." Journal of Multi‐Criteria Decision Analysis 7, no. 6 (November 1998): 340–50. http://dx.doi.org/10.1002/(sici)1099-1360(199811)7:6<340::aid-mcda206>3.0.co;2-s.

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Mozaffari, Ahmad. "Synchronous self-learning Pareto strategy." International Journal of Intelligent Computing and Cybernetics 11, no. 2 (June 11, 2018): 197–233. http://dx.doi.org/10.1108/ijicc-05-2017-0050.

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Purpose In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers to the essence of real-life engineering systems and complex natural mechanisms which are generally multi-modal, non-convex and multi-criterion. Until now, several deterministic and stochastic methods have been proposed to cope with such complex systems. Advanced soft computational methods such as evolutionary games (cooperative and non-cooperative), Pareto-based techniques, fuzzy evolutionary methods, cooperative bio-inspired algorithms and neuro-evolutionary systems have effectively come to the aid of researchers to build up efficient paradigms with application to vector optimization. The paper aims to discuss this issue. Design/methodology/approach A novel hybrid algorithm called synchronous self-learning Pareto strategy (SSLPS) is presented for the sake of vector optimization. The method is the ensemble of evolutionary algorithms (EA), swarm intelligence (SI), adaptive version of self-organizing map (CSOM) and a data shuffling mechanism. EA are powerful numerical optimization algorithms capable of finding a global extreme point over a wide exploration domain. SI techniques (the swarm of bees in our case) can improve both intensification and robustness of exploration. CSOM network is an unsupervised learning methodology which learns the characteristics of non-dominated solutions and, thus, enhances the quality of the Pareto front. Findings To prove the effectiveness of the proposed method, the authors engage a set of well-known benchmark functions and some well-known rival optimization methods. Additionally, SSLPS is employed for optimal design of shape memory alloy actuator as a nonlinear multi-modal real-world engineering problem. The experiments show the acceptable potential of SSLPS for handling both numerical and engineering multi-objective problems. Originality/value To the author’s best knowledge, the proposed algorithm is among the rare multi-objective methods which fosters the use of automated unsupervised learning for increasing the intensity of Pareto front (while preserving the diversity). Also, the research evaluates the power of hybridization of SI and EA for efficient search.
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Cahyaningsih, Elin, Dana Indra Sensuse, and Handrie Noprisson. "Multi Methods for Knowledge Management Strategy Roadmap of Government Human Capital Management." Procedia Computer Science 124 (2017): 496–503. http://dx.doi.org/10.1016/j.procs.2017.12.182.

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Lee, Sang-Hun, Sung-Geon Song, and Sung-Jun Park. "Low Frequency Multi-Level Switching Strategy Based on Phase-Shift Control Methods." Journal of international Conference on Electrical Machines and Systems 1, no. 3 (September 1, 2012): 366–71. http://dx.doi.org/10.11142/jicems.2012.1.3.366.

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Shu-sheng, Chen, Hua Yang, Cai Fang-jie, and Gao Zheng-hong. "Multi-dimensional dissipation strategy within advection upstream splitting methods in hypersonic flows." Journal of Physics: Conference Series 1786, no. 1 (February 1, 2021): 012050. http://dx.doi.org/10.1088/1742-6596/1786/1/012050.

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CHOUDHURY, B. B., and B. B. BISWAL. "ALTERNATIVE METHODS FOR MULTI-ROBOT TASK ALLOCATION." Journal of Advanced Manufacturing Systems 08, no. 02 (December 2009): 163–76. http://dx.doi.org/10.1142/s0219686709001717.

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One of the most important aspects in the design of multi-robot systems (MRS) is the allocation of tasks among the robots in a productive and efficient manner. This paper presents an empirical study on task allocation strategies in multirobot environment. In general, optimal solutions are found through an exhaustive search, but because there are n × m ways in which m tasks can be assigned to n robots, an exhaustive search is often not possible with increased number of tasks. Task allocation methodologies for multirobot systems are developed by considering their capability in terms of time and space. The present work adopts a two-phase methodology to allocate tasks optimally amongst the candidate robots. The allocation cost of the robots is determined during the first phase and alternate algorithms are used in the second phase for optimizing the allocation. The work considers systems of practical sizes and the results obtained through this are helpful in recommending appropriate techniques to the users of MRS for increasing producibility and robot utilization. Three different approaches using Linear programming, Hungarian Algorithm and Knapsack Algorithm are presented and their results are analyzed for the suitability of the methods for an allocation problem. Simulation results are presented and compared for the benefit of the users.
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Ture, Hasan, Seyyide Dogan, and Deniz Kocak. "Assessing Euro 2020 Strategy Using Multi-criteria Decision Making Methods: VIKOR and TOPSIS." Social Indicators Research 142, no. 2 (June 4, 2018): 645–65. http://dx.doi.org/10.1007/s11205-018-1938-8.

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Lieberman, Elliot R. "Soviet Multi-Objective Mathematical Programming Methods: An Overview." Management Science 37, no. 9 (September 1991): 1147–65. http://dx.doi.org/10.1287/mnsc.37.9.1147.

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Dissertations / Theses on the topic "Multi-Methods strategy"

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Jernbäcker, Axel, and Max Junestrand. "Search methods for Strategy Synthesis for Multi-Agent Games of Imperfect Information." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302433.

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Finding strategies for agents in multi-agent systems of imperfect information is a difficult and time-consuming endeavor. It is thus of interest to find ways of doing this more effectively. This study aims to improve the performance of a strategy synthesizer tool by testing two search techniques and evaluating their performance. In this context, strategy synthesizing is defined as finding orders of actions for the agents which result in a winning scenario. Multi-agent systems mean that more than one agent is involved, and imperfect information indicates that the agents cannot distinguish between certain game states. To test the search techniques, they are implemented in an existing strategy synthesizer tool by Westerlund and Lycken [1]. The implemented search techniques are backwards search and transition tables. The results showed a significant impact on the execution time of strategy synthesis. The backwards search had the highest performance in both of the games tested, with performance increasing between 19.9% and 30.9% from the existing exhaustive search. Transition table search was on average between 54.2% and 61.3% slower than the existing solution. The results indicate that backwards search is an algorithm that can be used effectively in strategy synthesis and is well-suited to the graphs produced by the MKBSC on multiplayer imperfect information games. Where MKBSC is the reduction tool used to generate solvable graphs.
Att hitta strategies för agenter i multi-agent system med ofullständig information är ett svårt och tidskrävande arbete. Det är därför av intresse att hitta sätt att göra detta mer effektivt. Denna studie har som mål att förbättra prestandan av ett verktyg för strategisyntes genom att testa två söktekniker och utvärdera dessas effektivitet. Här är strategisyntes definierat som att hitta en följd av handlingar för agenterna som resulterar i en vinst. Multi-agent system betyder att mer än en agent är inblandad och offulständig information betyder att agenterna inte kan skilja mellan vissa speltillstånd. För att testa sökteknikerna implementerades de i ett redan existerande verktyg för strategisyntes skapat av Westerlund och Lycken [1]. Sökteknikerna som implementeras är baklängessökning och översgånstabeller. Baklängessökningen hade högst effektivitet för båda av de testade spelen, med en effektivitetsökning mellan 19.9% och 30.9% i jämförelse med den existerande uttömmande sökalgoritmen. Sökning med översgånstabeller var i genomsnitt mellan 54.2% and 61.3% långsammare än den existerande lösningen. Resultaten indikerar att baklängessökning är en effektiv algoritm för strategi syntes och är väl anpassad till graferna som produceras av att applicera MKBSC på multi-agent spel med ofullständig information. Där MKBSC är ett reduceringsverktyg för att generera lösbara grafer.
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Pesaranghader, Ali. "A Reservoir of Adaptive Algorithms for Online Learning from Evolving Data Streams." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38190.

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Continuous change and development are essential aspects of evolving environments and applications, including, but not limited to, smart cities, military, medicine, nuclear reactors, self-driving cars, aviation, and aerospace. That is, the fundamental characteristics of such environments may evolve, and so cause dangerous consequences, e.g., putting people lives at stake, if no reaction is adopted. Therefore, learning systems need to apply intelligent algorithms to monitor evolvement in their environments and update themselves effectively. Further, we may experience fluctuations regarding the performance of learning algorithms due to the nature of incoming data as it continuously evolves. That is, the current efficient learning approach may become deprecated after a change in data or environment. Hence, the question 'how to have an efficient learning algorithm over time against evolving data?' has to be addressed. In this thesis, we have made two contributions to settle the challenges described above. In the machine learning literature, the phenomenon of (distributional) change in data is known as concept drift. Concept drift may shift decision boundaries, and cause a decline in accuracy. Learning algorithms, indeed, have to detect concept drift in evolving data streams and replace their predictive models accordingly. To address this challenge, adaptive learners have been devised which may utilize drift detection methods to locate the drift points in dynamic and changing data streams. A drift detection method able to discover the drift points quickly, with the lowest false positive and false negative rates, is preferred. False positive refers to incorrectly alarming for concept drift, and false negative refers to not alarming for concept drift. In this thesis, we introduce three algorithms, called as the Fast Hoeffding Drift Detection Method (FHDDM), the Stacking Fast Hoeffding Drift Detection Method (FHDDMS), and the McDiarmid Drift Detection Methods (MDDMs), for detecting drift points with the minimum delay, false positive, and false negative rates. FHDDM is a sliding window-based algorithm and applies Hoeffding’s inequality (Hoeffding, 1963) to detect concept drift. FHDDM slides its window over the prediction results, which are either 1 (for a correct prediction) or 0 (for a wrong prediction). Meanwhile, it compares the mean of elements inside the window with the maximum mean observed so far; subsequently, a significant difference between the two means, upper-bounded by the Hoeffding inequality, indicates the occurrence of concept drift. The FHDDMS extends the FHDDM algorithm by sliding multiple windows over its entries for a better drift detection regarding the detection delay and false negative rate. In contrast to FHDDM/S, the MDDM variants assign weights to their entries, i.e., higher weights are associated with the most recent entries in the sliding window, for faster detection of concept drift. The rationale is that recent examples reflect the ongoing situation adequately. Then, by putting higher weights on the latest entries, we may detect concept drift quickly. An MDDM algorithm bounds the difference between the weighted mean of elements in the sliding window and the maximum weighted mean seen so far, using McDiarmid’s inequality (McDiarmid, 1989). Eventually, it alarms for concept drift once a significant difference is experienced. We experimentally show that FHDDM/S and MDDMs outperform the state-of-the-art by representing promising results in terms of the adaptation and classification measures. Due to the evolving nature of data streams, the performance of an adaptive learner, which is defined by the classification, adaptation, and resource consumption measures, may fluctuate over time. In fact, a learning algorithm, in the form of a (classifier, detector) pair, may present a significant performance before a concept drift point, but not after. We define this problem by the question 'how can we ensure that an efficient classifier-detector pair is present at any time in an evolving environment?' To answer this, we have developed the Tornado framework which runs various kinds of learning algorithms simultaneously against evolving data streams. Each algorithm incrementally and independently trains a predictive model and updates the statistics of its drift detector. Meanwhile, our framework monitors the (classifier, detector) pairs, and recommends the efficient one, concerning the classification, adaptation, and resource consumption performance, to the user. We further define the holistic CAR measure that integrates the classification, adaptation, and resource consumption measures for evaluating the performance of adaptive learning algorithms. Our experiments confirm that the most efficient algorithm may differ over time because of the developing and evolving nature of data streams.
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Vetschera, Rudolf. "Strategic manipulation of preference information in multi-criteria group decision methods." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2003. http://epub.wu.ac.at/1776/1/document.pdf.

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When group decisions involve the allocation of resources to group members, the members might have an incentive to strategically distort any information they provide to increase their share of resources. The paper compares several simple multi-criteria group decision methods with respect to this problem. We show, using a computational model, that strategic manipulation of preference information is possible in all of the methods, although to a different extent. Furthermore, when the true solution generated by this methods is not Pareto-optimal, manipulation attempts might even improve the efficiency of outcomes. (author's abstract)
Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
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Volpert, Thibault. "Étude d'un schéma différences finies haute précision et d'un modèle de fil mince oblique pour simuler les perturbations électromagnétiques sur véhicule aérospatial." Thesis, Toulouse, ISAE, 2014. http://www.theses.fr/2014ESAE0042/document.

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Les travaux de cette thèse concerne l’étude d’une méthode élément finis d’ordre spatial élevé que l’on peut assimilé à une extension du schéma de Yee. On parle alors de méthode différences finies d’ordre élevé. Après avoir donné, dans un premier chapitre, un historique non exhaustif des principales méthodes utilisées pour résoudre les équations de Maxwell dans le cadre de problèmes de CEM et montré l’ intérêt de disposer d’un solveur de type "différences finies d’ ordre élevé", nous présentons dans un deuxième chapitre le principe de la méthode. Nous donnons pour cela les caractéristiques du schéma spatial et temporel en précisant les conditions de stabilité de la méthode. En outre, dans une étude purement numérique, nous étudions la convergence du schéma. On se focalise ensuite sur la possibilité d’utiliser des ordres spatiaux variable par cellules dans chaque direction de l’espace. Des comparaisons avec le schéma de Yee et un schéma de Galerkin Discontinu particulier sont ensuite effectuées pour montrer les gains en coûts calcul et mémoire et donc l’intérêt de notre approche par rapport aux deux autres. Dans un troisième chapitre, nous nous intéressons à l’étude de modèles physiques indispensable au traitement d’un problème de CEM. Pour cela, nous nous focalisons particulièrement sur un modèle de fil mince oblique, des modèles de matériaux volumiques et minces et enfin sur la prise en compte de sol parfaitement métallique dans une agression de type onde plane. Chaque modèle est détaillé et validé par comparaison avec des solutions analytiques ou résultant de la littérature, sur des exemples canoniques. Le quatrième chapitre est dédié à une technique d’hybridation entre notre méthode et une approche Galerkin Discontinu en vue de traiter des géométries possédant des courbures. Nous donnons pour cela une stratégie d’hybridation basée sur l’échange de flux qui garantie au niveau continue la conservation d’une énergie. Nous présentons ensuite quelques exemples montrant la validité de notre approche dans une stratégie multi-domaines/multi-méthodes que nous précisons. Enfin le dernier chapitre de cette thèse concerne l’exploitation de notre méthode sur des cas industriels en comparaisons avec d’autres méthodes ou des résultats expérimentaux
This thesis is about the study of a high spatial finite element method whichcan be assimilated at an extension of the Yee schema. In the next, this method is also called high order finite difference method. In the first chapter, we give a non exhaustive recall of the major methods used to treat EMC problems and we show the necessity to have this kind of schema to simulate efficiently some EMC configurations. In the second chapter, the principle of the numerical method is presented and a stability condition is given. A numerical study analysis of the schema convergence is also done. Next, we show the interest to have the possibility to use local spatial order by cell in each direction of the computational domain. Some canonic examples are given to show the advantages interms of CPU time and memory storage of the method by comparison with Yee’s scheme and DG approach. In the third chapter, we define and validate on several examples,some physical models as thin wire, materials and perfectly metallic ground in presence of a plane wave, to have the possibility to treat EMC problems. The fourth chapter is about a hybridization strategy between our high order FDTD method and a DG schema.We focalize our study on a hybrid method which provides an energy conservation of the continuous problem. A numerical example is given to validate the method. Finally, in the last chapter, we present some simulations on industrial problems to show the possibility of the method to treat realistic EMC problems
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Ufere, Nnaoke. "Systemic Corruption: A Multi-Theoretic, Multi-Level and Mixed Methods Analysis of the Interplay among Institutional Logics, Strategic Agency and Reward Expectancy." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1363165732.

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Warren, Scott Joseph. "A Multi-Methodology Study of the Historic Impact of Soft Systems Methodology and Its Associated Data Visualization Approach in the Context of Operations and Business Strategy." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404615/.

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The purpose of this three-essay dissertation was to expand knowledge and theory regarding soft systems methodologies (SSMs) and data visualization approaches in business, engineering, and other social sciences. The first essay depicts a bibliometric analysis study of the historic impacts of SSM from 1980-2018 on business, engineering, and other social sciences fields. This study found 285 articles that described or employed SSM for research and included outcomes such as top SSM authors, author citation impacts, common dissemination outlets, time-bound distribution of publications, and other relevant findings. This study provided a picture of who, what, why, when, and where SSM has had the greatest impact on academic thought and practice. The second essay presents research on the academic impact of Systemigrams, an associated data visualization approach, finding examples of conceptual or research development that employed Systemigrams to depict complex problem situations. Recommendations for improvement of designing these data visualizations to increase their field use resulted from this study. The final essay leverages a selection of the articles as use cases to produce a grounded theory study to identify phenomena that arose from the use of SSM for operations and firm strategy research. This study identified two broad themes including (i) scope, structure, and process challenges and (ii) performance and evaluation limitations. These themes were explained by six patterns that emerged from the publications. Each produced change recommendations for SSM process, practice, and reporting to support its continued viability and adoption in business and operations research.
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Scriffignano, Anthony James. "Strategic Asymmetric Multicultural Alliances in Business." Antioch University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1278017139.

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Dávidová, Lucia. "Ocenenie doménového mena." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-114378.

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The main goal of this work is to evaluate the market value of the Internet domain, Fotečky.cz, at the 1st in January 2012, for the purpose of subsquent selling the domain on the market to the potential buyer. To correct evaluation, method of multi-period excess earnings and method of the license analogy are used.
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Shin-Dar, Chiou, and 邱信達. "A Study on Community Planning and Development Strategy of Fishing Villages in Taiwan－An Application of Fuzzy Multi-criteria Decision Methods." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/81061812304152353976.

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Kafilongo, Kindu Wa Mulumba. "The use of pair-programming to enhance the academic performance of tertiary level software development students." Thesis, 2016. http://hdl.handle.net/10352/285.

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M. Tech. (Information Technology, Faculty of Applied and Computer Sciences, Vaal University of Technology
The number of students passing computer programming modules at Higher Education Institutions (HEIs) in South Africa at first year level is low. Only with the second attempt do most students pass. This delay results in students completing their three-year undergraduate qualification in four or even five years. One potential contribution towards addressing this problem is the introduction of a collaborative (cooperative) pedagogical approach where students develop software in teams, known in the Information Technology (IT) sector as pair-programming. This study endeavoured to investigate the impact of pair-programming on the academic progress of students registered for the Information Technology qualification at HEIs in South Africa. The study warranted the selection of action research as the most appropriate research strategy. Multi-methods data collection was carried out over two consecutive semesters. The data collection methods included a semi-structured interview, observations and empirical assessment. The participants were students registered for the Information Systems module, which focuses on software development. Pair-programming was introduced to one group of software development students, while a second group continued with the normal solo-programming approach. Semi-structured interviews were held with the students before commencement and after completion of the pair-programming intervention, to establish a change, if any, in the academic performance, attitude and enjoyment level of students introduced to pair-programming compared to those who continued with solo-programming. Observations were conducted throughout the course of the practical sessions over both semesters. Empirical assessments were done by means of tests given to both groups of students during the practical sessions, three tests per semester. Data analysis techniques included t-tests and thematic analysis. The findings concluded that pair-programming had a significant positive impact on the academic progress of IT students, including an increase in the enjoyment level and a more positive attitude towards software development.
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Books on the topic "Multi-Methods strategy"

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Hernandez, John B. Evaluating a multi-hospital quality improvement strategy to implement clinical guidelines for radiographic contrast agents. Santa Monica, CA: Rand, 1998.

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Hernandez, John B. Evaluating a multi-hospital quality improvement strategy to implement clinical guidelines for radiographic contrast agents. Santa Monica, CA: Rand, 1998.

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Hernandez, John B. Evaluating a multi-hospital quality improvement strategy to implement clinical guidelines for radiographic contrast agents. Santa Monica, CA: Rand, 1998.

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Hernandez, John B. Evaluating a multi-hospital quality improvement strategy to implement clinical guidelines for radiographic contrast agents. Santa Monica, CA: Rand, 1998.

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Hernandez, John B. Evaluating a multi-hospital quality improvement strategy to implement clinical guidelines for radiographic contrast agents. Santa Monica, CA: Rand, 1998.

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Dansereau, Fred, and Francis J. Yammarino, eds. Multi-Level Issues in Strategy and Methods. Emerald Group Publishing Limited, 2005. http://dx.doi.org/10.1016/s1475-9144(2005)4.

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(Editor), Fred Dansereau, and Francis Yammarino (Editor), eds. Multi-Level Issues in Strategy and Methods (Research in Multi-Level Issues). JAI Press, 2005.

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Brooker, Paul, and Margaret Hayward. Intel: Grove’s Only the Paranoid Survive. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198825395.003.0006.

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Andy Grove enhanced the microprocessor manufacturer Intel in the 1980s–90s by learning to adapt to the crises that he later termed ‘strategic inflection points’. The first section describes how and what CEO Grove learnt from these ‘inflection point’ adaptive crises. The second section describes his three-stage adaptive framework for dealing with these adaptive crises. It includes rapid adaptation and two other rational methods, diverse and institutionalized deliberation, plus a pre-deliberation experimental process that ‘delivers’ new product ideas. The third section focuses on this experimentation process, so important for high-tech firms seeking product innovation and diversification. Packard’s memoir The HP Way described the Hewlett-Packard decentralized, multi-divisional, experimentation system that produced a long series of innovations and diversifications. The final section discusses Steve Jobs’s relatively top-down, hands-on approach to experimentation and diversification, which provided Apple with the iPod, iPhone, and iPad.
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Book chapters on the topic "Multi-Methods strategy"

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Okeya, Katsuyuki, and Kouichi Sakurai. "Fast Multi-scalar Multiplication Methods on Elliptic Curves with Precomputation Strategy Using Montgomery Trick." In Cryptographic Hardware and Embedded Systems - CHES 2002, 564–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36400-5_41.

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Hernes, Marcin, Adrianna Kozierkiewicz, and Marcin Pietranik. "The Agents’ Selection Methods for a Consensus-Based Investment Strategy in a Multi-agent Financial Decisions Support System." In Communications in Computer and Information Science, 60–67. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30278-8_8.

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McCarthy, Tracey, and Maria G. Tuohy. "A Multi-Step Chromatographic Strategy to Purify Three Fungal Endo-β-Glucanases." In Methods in Molecular Biology, 497–524. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-913-0_30.

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Glover, Fred. "Multi-Start and Strategic Oscillation Methods — Principles to Exploit Adaptive Memory." In Operations Research/Computer Science Interfaces Series, 1–23. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4567-5_1.

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Çalık, Ahmet. "Key Enablers Assessment to Implement Industry 4.0 Technologies in the Future for the Turkish Manufacturing Sector." In Advances in Business Strategy and Competitive Advantage, 243–65. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6632-9.ch012.

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Industry 4.0 (I4.0), which reshapes traditional production and operation methods and causes companies to be under digital transformation, is currently an evolving research topic. Although advanced technologies can be easily adopted by large companies. In particular, there are still challenges in the adoption and implementation of I4.0 technologies in small and medium-sized enterprises (SMEs). This study examines the readiness of companies in the machinery manufacturing industry to implement I4.0 technologies in the context of SMEs. To achieve this goal, a multi-criteria decision-making (MCDM) approach including the pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) and fuzzy VIKOR (FVIKOR) is proposed. First, existing readiness models linked to the implementation of I4.0 technologies have been studied to specify key enablers. Then, the PFAHP method is used to obtain weights of enablers on I4.0 technologies. Finally, FVIKOR is applied to obtain ranking for five companies. A case study is conducted to measure the level of readiness of five manufacturing companies in Konya.
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Hassanin, Mohamed F., Abdullah M. Shoeb, and Aboul Ella Hassanien. "Designing Multilayer Feedforward Neural Networks Using Multi-Verse Optimizer." In Handbook of Research on Machine Learning Innovations and Trends, 1076–93. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2229-4.ch048.

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Artificial neural network (ANN) models are involved in many applications because of its great computational capabilities. Training of multi-layer perceptron (MLP) is the most challenging problem during the network preparation. Many techniques have been introduced to alleviate this problem. Back-propagation algorithm is a powerful technique to train multilayer feedforward ANN. However, it suffers from the local minima drawback. Recently, meta-heuristic methods have introduced to train MLP like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Cuckoo Search (CS), Ant Colony Optimizer (ACO), Social Spider Optimization (SSO), Evolutionary Strategy (ES) and Grey Wolf Optimization (GWO). This chapter applied Multi-Verse Optimizer (MVO) for MLP training. Seven datasets are used to show MVO capabilities as a promising trainer for multilayer perceptron. Comparisons with PSO, GA, SSO, ES, ACO and GWO proved that MVO outperforms all these algorithms.
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Zheng, Haixia, Stale Navrud, and Shiran Shen. "What Price for Ecosystem Services in China?" In Advances in Business Strategy and Competitive Advantage, 176–98. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1886-0.ch010.

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Payment for Environmental Services (PES) in the watershed has been widely adopted as an important policy instrument to compensate upstream water users for providing water quality improvement for the whole river basin. In this paper, we use three independent valuation methods to determine the price of ecosystem service (ES), particularly water quality, in Miyun Reservoir, the main surface water source for Beijing. We find that the value of water quality is lowest using opportunity cost of limitation of development rights (OCLDR), highest with contingent valuation method (CVM), and water resources benefits assessment (WRBA) gives an in-between value. OCLDR determines the size of subsidies from those that benefit from water quality improvement from upstream. WRBA is a reference for compensation criteria to the upstream government and farmers when water resources are transferred across jurisdictional boundaries. CVM not only captures the direct value of water quality improvement, but also the indirect value of improvement in other ecosystem services as a result of improvement in water quality. Based on the results, we propose a multi-level ecological compensation system for the Miyun Reservoir river basin. We use OCLDR to determine subsides/ compensation to upstream farmers and other suppliers of the ES; WRBA set the price of water transfer; and CVM to figure out the size of payments for integrated water quality improvement.
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Çebi, Ferhan, İrem Otay, and Dilay Çelebi. "Fuzzy MCDM Approach for Make or Buy Decision Problem." In Encyclopedia of Business Analytics and Optimization, 978–95. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5202-6.ch090.

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Make or buy decision answers a fundamental question in the development of a manufacturing strategy. It requires consideration of both quantitative and qualitative factors diverging in a broad range. This study presents a two-stage decision model which incorporates fuzzy multi-criteria decision making methods to support make or buy decision of a company operating in the wood building products sector. The first stage comprises fuzzy SAW (Simple Additive Weighting) method to evaluate the decision on market entry, then the second stage integrates fuzzy SAW and fuzzy VIKOR (Multi-criteria optimization and compromise solution) methods to evaluate sourcing options. Proposed approach is demonstrated on an example invoked from a real-life problem. Then, sensitivity analysis is conducted to test the robustness of the models.
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El Haddadi, Anass, Bernard Dousset, and Ilham Berrada. "Discovering Patterns in Order to Detect Weak Signals and Define New Strategies." In Data Mining, 1647–63. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2455-9.ch086.

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Competitive intelligence activities rely on collecting and analyzing data in order to discover patterns from data using sequence data mining. The discovered patterns are used to help decision-makers considering innovation and defining the strategy for their business. In this chapter we present four methods for discovering patterns in the competitive intelligence process: “correspondence analysis,” “multiple correspondence analysis,” “evolutionary graph,” and “multi-term method.”
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El Haddadi, Anass, Bernard Dousset, and Ilham Berrada. "Discovering Patterns in Order to Detect Weak Signals and Define New Strategies." In Pattern Discovery Using Sequence Data Mining, 195–211. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-056-9.ch012.

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Competitive intelligence activities rely on collecting and analyzing data in order to discover patterns from data using sequence data mining. The discovered patterns are used to help decision-makers considering innovation and defining the strategy for their business. In this chapter we present four methods for discovering patterns in the competitive intelligence process: “correspondence analysis,” “multiple correspondence analysis,” “evolutionary graph,” and “multi-term method.”
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Conference papers on the topic "Multi-Methods strategy"

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Yang, Zuo, Chen Zhenghan, and Zhao Hua. "Automatic extraction of paper research methods based on multi-strategy." In ICCIP 2019: 2019 the 5th International Conference on Communication and Information Processing. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3369985.3370025.

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Kim, Chongam, and Jin Seok Park. "Multi-dimensional Limiting Strategy for Higher-order CFD Methods - Progress and Issue (Invited)." In 22nd AIAA Computational Fluid Dynamics Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-3199.

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Xu, Hongyi, Ching-Hung Chuang, and Ren-Jye Yang. "Mixed-Variable Metamodeling Methods for Designing Multi-Material Structures." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59176.

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To establish metamodels for the multi-material structure design problems, the material selection of each component is considered as a categorical design variable. One challenging task is to establish an accurate mixed-variable metamodel. It is critical to reduce the prediction error of the mixed-variable metamodel in order to achieve a feasible design with superior performance in the metamodel-based optimization. This paper investigates two different strategies of mixed-variable metamodeling: “feature separating” strategy and “all-in-one” strategy. A supervised learning-aided method is proposed to improve the “feature separating” metamodels. The proposed method is compared with several existing mixed-variable metamodeling methods on three engineering benchmark problems to understand their relative merits. These methods include Neural Network (NN) regression, Classification and Regression Tree (CART) and Gaussian Process (GP). A new Polynomial Coefficient Metric is developed to quantify the adequacy of training data. This study provides insight and guidance for establishing proper metamodels on multi-material structural design problems.
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Agarwal, Arvind, and Nathan Gnanasambandam. "Efficient Dynamic Methods for Predictive Action Strategy Optimization for Risk Driven Multi-channel Communication." In 2014 IEEE International Conference on Services Computing (SCC). IEEE, 2014. http://dx.doi.org/10.1109/scc.2014.78.

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Caro, F., V. Darrigrand, E. Alberdi, and D. Pardo. "Goal-Oriented hp-Adaptive Finite Element Methods: A Painless Multi-level Automatic Coarsening Strategy." In 10th International Conference on Adaptative Modeling and Simulation. CIMNE, 2021. http://dx.doi.org/10.23967/admos.2021.044.

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De´pince´, Philippe, Se´bastien Rabeau, and Fouad Bennis. "Collaborative Optimization Strategy for Multi-Objective Design." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85054.

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The increasing economic competition of all industrial markets and growing complexity of engineering problems lead to a progressive specialization and distribution of expertise, tools and works. On the other hand, engineering products becomes more and more complex and the designer has to face with an increase design variables and design objectives. Besides multi-objective optimization (MOO) and multi-disciplinary design optimization (MDO) are more commonly used as methods to provide optimal solutions for complex design problems. The paper describes an innovative mixing between genetic algorithms (MOGA) and collaborative optimization (CO) as a tool to: 1) increase the convergence rate when a design problem can be broken up regarding design variables, and 2) provide an optimal set of design variables in case of multi-level design problem. This method gives multidisciplinary optimization the advantages AG has brought to multi-objective optimization. The method, tested on test functions, assures high optimization results containing CPU times.
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Lafond, Daniel, Michel B. DuCharme, Marie-Eve St-Louis, and Sebastien Tremblay. "Augmenting cognition in complex situation management: Projection of outcomes improves strategy efficiency." In 2011 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2011). IEEE, 2011. http://dx.doi.org/10.1109/cogsima.2011.5753462.

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Bollenbacher, J., and B. Rhein. "Optimal configuration and control strategy in a multi-carrier-energy system using reinforcement learning methods." In 2017 International Energy and Sustainability Conference (IESC). IEEE, 2017. http://dx.doi.org/10.1109/iesc.2017.8167476.

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Chen, Xiyang, Kewei Zhang, and Yucheng Peng. "Research on Multi Diagnosis Methods for Hydro-Generator Sets." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58163.

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Hydro-Generator Sets Condition Monitoring and Predictive Maintenance activity has increased dramatically over the past few years. The Fault Diagnostic System is the key technique for the Predictive Maintenance. This paper discusses the Fault Diagnostic System function structure, system design and inferential strategy of Multi-Fault Diagnostic System of the Hydro-Generator Sets. The developing of the power system to big unit requires the higher automation and reliability of the power station. Electrical power systems are constantly exposed to faults and disturbances. This may lead to damage or it may pose a threat to reliable power system operation if a faulty cannot be quickly isolated from the system operation. In accordance with diversity and complexity of Hydro-Generator Sets faults, this paper brings forward a type of fault diagnosis method based on Multi-Diagnosis methods. The Multi-Diagnosis system is constituted of two Sub-Diagnosis systems: one is On-Line Sub-Diagnosis system that based on Bayesian Network (BN) just for the modeling with Bayesian Network has been a powerful tool to solve many uncertainty problems and also with the ability of predicting the future diagnosis; the other is Off-Line Sub-Diagnosis System that based on Model of a hydraulic Turbine-Generator Rotor-Bearing. In order to apply the Bayesian Network model to the engineering fields, we have to solve the problem of constructing the Bayesian Network. Then it suggests a method of constructing Bayesian Network based on the Fault Trees that widely used by the engineers. Base on the construction method, we will construct the Bayesian Network quickly, and Bayesian Network is more suitable for Hydro-Generator Sets fault diagnosis. In accordance with the On-Line Diagnosis Sub-System, it adopts Case-Based Reasoning to make the decision of final diagnosis result or further diagnosis. However, the method mentioned above is limited because of its bottleneck of the knowledge acquisition. The model strategy of the Rotor-Bearing system of Hydro-Generator is discussed and a multi-degree-freedom nonlinear model is developed. It proposes the simulation in accordance with the three fields such as: waterpower, electric and machine. Mechanical, electrical and hydraulic forces acting on rotor externally can be taken into account during the model calculating process. The transient responses of the system are calculated by combined used the transfer matrix method. This paper brings forward a prototype of Hydro-Generator Sets Fault Diagnostic System in order to make a more efficient fault diagnostic decision.
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Aicha, Abid, Ben Hamed Mouna, and Sbita Lassaad. "Multi-model modeling methods based on novel clustering strategy and comparative study: Application to induction machines." In 2015 12th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2015. http://dx.doi.org/10.1109/ssd.2015.7348160.

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