Possibilistic Data Analysis for Operations Research PDF Download
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Author: Hideo Tanaka
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 242
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Book Description
Introduction: possibility theory in operations research; Possibility models; Theory of possibilistic systems based on exponential possibility distributions; Identification of possibility distributions; Possibilistic regression analysis; Possibilistic portfolio selection problems; Discriminant analysis based on possibility distributions; Rough set analysis.
Author: Hideo Tanaka
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 242
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Book Description
Introduction: possibility theory in operations research; Possibility models; Theory of possibilistic systems based on exponential possibility distributions; Identification of possibility distributions; Possibilistic regression analysis; Possibilistic portfolio selection problems; Discriminant analysis based on possibility distributions; Rough set analysis.
Author: Roman Slowiński
Publisher: Springer Science & Business Media
ISBN: 1461556457
Category : Mathematics
Languages : en
Pages : 467
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Book Description
Fuzzy Sets in Decision Analysis, Operations Research and Statistics includes chapters on fuzzy preference modeling, multiple criteria analysis, ranking and sorting methods, group decision-making and fuzzy game theory. It also presents optimization techniques such as fuzzy linear and non-linear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy dynamic programming. In addition, the book also accounts for advances in fuzzy data analysis, fuzzy statistics, and applications to reliability analysis. These topics are covered within four parts: Decision Making, Mathematical Programming, Statistics and Data Analysis, and Reliability, Maintenance and Replacement. The scope and content of the book has resulted from multiple interactions between the editor of the volume, the series editors, the series advisory board, and experts in each chapter area. Each chapter was written by a well-known researcher on the topic and reviewed by other experts in the area. These expert reviewers sometimes became co-authors because of the extent of their contribution to the chapter. As a result, twenty-five authors from twelve countries and four continents were involved in the creation of the 13 chapters, which enhances the international character of the project and gives an idea of how carefully the Handbook has been developed.
Author: Jie Lu
Publisher: Springer Science & Business Media
ISBN: 3642257550
Category : Technology & Engineering
Languages : en
Pages : 457
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Book Description
This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.
Author: Giacomo Della Riccia
Publisher: Springer Science & Business Media
ISBN: 3211381678
Category : Mathematics
Languages : en
Pages : 203
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Book Description
The work presents a modern, unified view on decision support and planning by considering its basics like preferences, belief, possibility and probability as well as utilities. These features together are immanent for software agents to believe the user that the agents are "intelligent".
Author: Christian Borgelt
Publisher: Springer Science & Business Media
ISBN: 3642147461
Category : Technology & Engineering
Languages : en
Pages : 640
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Book Description
Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.
Author: Tsau Young Lin
Publisher: Physica
ISBN: 3790817910
Category : Computers
Languages : en
Pages : 538
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Book Description
During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing.
Author: Gwo-Hshiung Tzeng
Publisher: CRC Press
ISBN: 1466554622
Category : Business & Economics
Languages : en
Pages : 317
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Book Description
Multi-objective programming (MOP) can simultaneously optimize multi-objectives in mathematical programming models, but the optimization of multi-objectives triggers the issue of Pareto solutions and complicates the derived answers. To address these problems, researchers often incorporate the concepts of fuzzy sets and evolutionary algorithms into M
Author: Janusz Kacprzyk
Publisher: Springer
ISBN: 3662435055
Category : Technology & Engineering
Languages : en
Pages : 1637
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Book Description
The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
Author: Christian Borgelt
Publisher: Springer
ISBN: 3642302785
Category : Technology & Engineering
Languages : en
Pages : 378
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Book Description
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.
Author: Baoding Liu
Publisher: Springer Science & Business Media
ISBN: 3540894837
Category : Business & Economics
Languages : en
Pages : 205
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Book Description
This book provides comprehensive coverage of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, vehicle routing problem, and machine scheduling problem.
