Search Results - set theory~

Engineering risk assessment and design with subset simulation / by Au, Siu-Kui, Wang, Yu

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Set-theoretic fault-tolerant control in multisensor systems by Stoican, Florin

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Heat transfer virtual lab for students and engineers : theory and guide for setting up / by Fridman, Ella, Mahajan, Harshad S.

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Modem theory an introduction to telecommunications / by Blahut, Richard E.

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Apache Roller 4.0 beginner's guide a comprehensive, step-by-step guide on how to set up, customize, and market your blog using Apache Roller / by Romero, Alfonso V.

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Error-Correction Coding and Decoding Bounds, Codes, Decoders, Analysis and Applications / by Tomlinson, Martin, Tjhai, Cen Jung, Ambroze, Marcel A., Ahmed, Mohammed, Jibril, Mubarak

Table of Contents: “…Part I: Theoretical Performance of Error-Correcting Codes -- Bounds on Error Correction Coding Performance -- Soft and Hard Decision Decoding Performance -- Soft Decision and Quantised Soft Decision Decoding -- Part II: Code Construction -- Cyclotomic Cosets, The Mattson–Solomon Polynomial, Idempotents and Cyclic Codes -- Good Binary Linear Codes -- Lagrange Codes -- Extended BCH -- Reed–Solomon Codes -- Algebraic Geometry Codes -- Algebraic Quasi Cyclic Codes -- Convolutional Codes: A Historical Perspective -- Aalogue BCH Codes -- LDPC Codes -- Part III: Analysis of Codes -- True Search for Stopping Sets for LDPC Codes -- Part IV: Decoders -- Erasures and Error-Correcting Codes -- The Modified Dorsch Decoder -- A Concatenated Error-Correction System Using the |u|u+v| Code Construction -- Part V: Applications -- Combined Error Detection and Error Correction -- Password Correction and Confidential Information Access System -- Variations on the McEliece Public Key Encryption System -- Error-Correcting Codes and Dirty-Paper Coding.…”
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Multicriteria decision aid and artificial intelligence links, theory and applications / by Doumpos, Michael

Table of Contents: “…Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 1 Computational Intelligence Techniques for Multicriteria Decision Aiding: An Overview 1.1 Introduction 1.2 The MCDA Paradigm 1.2.1 Modeling Process 1.2.2 Methodological Approaches 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 Artificial Neural Networks for Intelligent Decision Support 2.4.2 Fuzzy Logic for Intelligent Decision Support 2.4.3 Expert Systems for Intelligent Decision Support 2.4.4 Evolutionary Computing for Intelligent Decision Support 2.4.5 Intelligent Agents for Intelligent Decision Support 2.5 Evaluating Intelligent Decision Support Systems 2.5.1 Determining Evaluation Criteria 2.5.2 Multi-Criteria Model for IDSS Assessment 2.6 Summary and Future Trends References Part Two Intelligent Technologies for Decision Support and Preference Modeling 3 Designing Distributed Multi-Criteria Decision Support Systems for Complex and Uncertain Situations 3.1 Introduction 3.2 Example Applications 3.3 Key Challenges 3.4 Making Trade-offs: Multi-criteria Decision Analysis 3.4.1 Multi-attribute Decision Support 3.4.2 Making Trade-offs Under Uncertainty 3.5 Exploring the Future: Scenario-based Reasoning 3.6 Making Robust Decisions: Combining MCDA and SBR 3.6.1 Decisions Under Uncertainty: The Concept of Robustness 3.6.2 Combining Scenarios and MCDA 3.6.3 Collecting, Sharing and Processing Information: A Distributed Approach 3.6.4 Keeping Track of Future Developments: Constructing Comparable Scenarios 3.6.5 Respecting Constraints and Requirements: Scenario Management 3.6.6 Assisting Evaluation: Assessing Large Numbers of Scenarios 3.7 Discussion 3.8 Conclusion References 4 Preference Representation with Ontologies 4.1 Introduction 4.1.1 Structure of the Chapter 4.2 Ontology-based Preference Models 4.3 Maintaining the User's Profile up to Date 4.4 Decision Making Methods Exploiting the Preference Information Stored in Ontologies 4.4.1 Recommendation Based on Aggregation 4.4.2 Recommendation Based on Similarities 4.4.3 Recommendation Based on Rules 4.5 Discussion and Open Questions References Part Three Decision Models 5 Neural Networks in Multicriteria Decision Support 5.1 Introduction 5.2 Basic Concepts of Neural Networks 5.2.1 Neural Networks for Intelligent Decision Support 5.3 Basics in Multicriteria Decision Aid 5.3.1 MCDM Problems 5.3.2 Solutions of MCDM Problems 5.4 Neural Networks and Multicriteria Decision Support 5.4.1 Review of Neural Network Applications to MCDM Problems 5.4.2 Discussion 5.5 Summary and Conclusions References 6 Rule-Based Approach to Multicriteria Ranking 6.1 Introduction 6.2 Problem Setting 6.3 Pairwise Comparison Table (PCT) 6.4 Rough Approximation of Outranking and Non-outranking Relations 6.5 Induction and Application of Decision Rules 6.6 Exploitation of Preference Graphs 6.7 Illustrative Example 6.8 Summary and Conclusions References 7 About the Application of Evidence Theory in MultiCriteria Decision Aid 7.1 Introduction 7.2 Evidence Theory: Some Concepts 7.2.1 Knowledge Model 7.2.2 Combination 7.2.3 Decision Making 7.3 New Concepts in Evidence Theory for MCDA 7.3.1 First Belief Dominance 7.3.2 RBBD Concept 7.4 Multicriteria Methods modeled by Evidence Theory 7.4.1 Evidential Reasoning Approach 7.4.2 DS/AHP 7.4.3 DISSET 7.4.4 A Choice Model Inspired by ELECTRE I 7.4.5 A Ranking Model Inspired by Xu et al.'…”
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Elements of algebraic coding systems / by Rocha, Valdemar C. da, 1947-

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Floods in a changing climate by Simonovi�c, Slobodan P.

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Complex-valued matrix derivatives with applications in signal processing and communications / by Hj�rungnes, Are

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An introduction to lean work design. by Fredendall, Lawrence D., Th�urer, Matthias

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An introduction to lean work design. by Fredendall, Lawrence D., Th�urer, Matthias

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Advanced control of aircraft, rockets, and spacecraft by Tewari, Ashish

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Transients of modern power electronics by Bai, Hua, 1980-

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Characterization of tribological materials

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Electrical energy efficiency technologies and applications /

Table of Contents: “…References 2 - CABLES AND LINES Paola Pezzini and Andreas Sumper 2.1. Theory of heat transfer 2.1.1. Conduction 2.1.2. Convection 2.1.3. …”
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Evaluation of rail technology a practical human factors guide /

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The Future Internet Future Internet Assembly 2013: Validated Results and New Horizons /

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Transboundary water resources management : a multidisciplinary approach /

Table of Contents: “…McKinney -- 7.8.1.Introduction -- 7.8.2.The Water Demand Reduction Cooperative Game -- 7.8.3.Results -- 7.8.4.Conclusions -- References -- 7.9.Conflict Resolution in Transboundary Waters: Incorporating Water Quality in Negotiations / Yannis Mylopoulos -- 7.9.1.Introduction -- 7.9.2.Game Theory in Water Resources -- 7.9.3.Methodology -- 7.9.4.Results -- 7.9.5.Conclusions -- References -- 7.10.The Johnston Plan in a Negotiated Solution for the Jordan Basin / Julio Sanchez Choliz -- 7.10.1.Introduction -- 7.10.2.Key Elements of the Negotiation Game and Fairness Criteria -- 7.10.2.1.Utility or Payment Functions for Arabs and Israelis -- 7.10.2.2.Negotiation Set -- 7.10.2.3.Fairness Criteria -- 7.10.2.4.Johnston Plan (1953-1955) -- 7.10.3.Three Significant Game Solutions between Israel and the Arabs -- 7.10.3.1.Regular Nash Solution without Lateral Payments and Break-off at (0;0) -- 7.10.3.2.Nash Solution with Lateral Payments and Break-off at (0;0) -- 7.10.3.3.Raiffa-Kalai-Smorodinsky Solution with Break-off at (0;0) -- 7.10.3.4.Other Solutions -- 7.10.4.Conclusions -- References -- Further Reading -- pt. …”
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Tuning and control loop performance / by McMillan, Gregory K., 1946-

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