دانلود کتاب Handbook on Decision Making: Volume 3: Trends and Challenges in Intelligent Decision Support Systems

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Preface Acknowledgements Contents Contributors Part I Methods and Techniques 1 A Vertical Fragmentation Method for Multimedia Databases Considering Content-Based Queries 1.1 Introduction 1.2 Background 1.3 State of the Art 1.4 Design of CBRVF 1.4.1 CBRVF 1.4.2 Web Application Design 1.5 Results and Discussion 1.6 Conclusion and Future Work References 2 An Approach Based on Process Mining Techniques to Support Software Development 2.1 Introduction 2.2 Background 2.3 Related Work 2.4 Framework 2.4.1 Phase 1: Event Log Management 2.4.2 Phase 2: Process Model Discovery 2.4.3 Phase 3: Statistics 2.5 Results 2.5.1 Case of a Purchase Order Process 2.5.2 Case of an Air Quality Monitoring System Process 2.6 Conclusions References 3 Analysis of Canonical Heuristic Methods for the Optimization of an Investment Portfolio 3.1 Introduction 3.2 Evolutionary Algorithms 3.3 Investment Portfolio 3.4 Theoretical Scaffolding 3.5 Genetic Algorithm 3.6 Differential Evolution 3.7 Artificial Immunological System 3.8 Methodology 3.9 Results 3.10 Conclusions References 4 Design of a Dynamic Horizontal Fragmentation Method for Multimedia Databases 4.1 Introduction 4.2 Background 4.3 Related Works 4.4 Design of a Dynamic Horizontal Fragmentation Method for Multimedia Databases 4.5 Results and Discussion 4.6 Conclusion References 5 Efficient Archiving Method for Handling Preferences in Constrained Multi-objective Evolutionary Optimization 5.1 Introduction 5.2 Problem Statement 5.3 Multi-objective Evolutionary Algorithms 5.3.1 Algorithms of Multi-Objective Evolutionary Optimization 5.3.2 Preference-Based MOEAs 5.3.3 Assessing Performance 5.4 Proposal 5.4.1 Archiving Regions of Interest 5.5 Experimental Step 5.5.1 Problems to Be Solved 5.5.2 Algorithms for Comparison 5.5.3 Parameter Settings 5.6 Results and Discussion 5.6.1 Results on Unconstrained Problems (DTLZ) 5.6.2 Results on Constrained Problems (C-DTLZ) 5.6.3 Results on Real-World Multi-Objective Problems 5.7 Conclusions and Future Work References 6 Evaluation of Machine Learning Techniques for Malware Detection 6.1 Introduction 6.2 Related Work 6.3 Background 6.3.1 Machine Learning Techniques 6.3.2 Measurement 6.4 Methodology 6.4.1 Data Preprocessing 6.4.2 Data Representation 6.4.3 Model Training/Testing 6.5 Results 6.5.1 Data Sets 6.5.2 Performance 6.6 Conclusions References 7 Implementation of Reinforcement-Learning Algorithms in Autonomous Robot Navigation 7.1 Introduction 7.2 Systematic Review of the Literature 7.2.1 Heuristic Algorithms 7.2.2 Applications of Reinforcement Learning 7.2.3 Synthesis and Considerations 7.3 Characteristics of Reinforcement Learning Algorithms 7.4 Methodology 7.4.1 Reinforcement Learning Algorithms 7.4.2 System Structure 7.4.3 Experiment Description 7.5 Results 7.6 Conclusions References 8 Trends on Decision Support Systems: A Bibliometric Review 8.1 Introduction 8.2 Methodology 8.2.1 PRISMA Method 8.2.2 Analysis with VOSviewer 8.3 Results 8.3.1 General Data of the DSS Applied 8.3.2 Authors, Organizations, and Countries that Publish the Most 8.3.3 Most Used Keywords 8.3.4 Most Cited Papers, Journals, Authors, Organizations, and Countries 8.3.5 Evolutions and Trends 8.4 Conclusions References 9 Use of Special Cases of Ontologies for Big Data Analysis in Decision Making Systems 9.1 Introduction 9.2 Ontological Representation of Knowledge 9.3 Ontologies in Knowledge Organization Systems 9.4 Decision Making Models and External Knowledge 9.5 Semantization of Big Data Technology 9.6 Use of Big Data Analysis in DMS 9.7 Semantic Processing of Metadata for Big Data 9.8 Generation of Ontologies for DM 9.8.1 Wiki Ontologies 9.8.2 Task Thesauri 9.9 Practical Use of Proposed Approach 9.10 Conclusion References 10 Multicriteria Decision Making Methods—A Review and Case of Study 10.1 Introduction 10.2 Bibliometric Analysis of MCDM 10.2.1 The Timeline of Multicriteria Decision Models 10.2.2 Journals and Authors in MCDM 10.2.3 The Most Cited MCDM Documents and Their Keywords 10.2.4 The Application Areas of MCDM 10.2.5 Institutions and Countries that Publish the Most on MCDM 10.2.6 The Funding Sources in MCDM Research 10.3 Case Study 10.3.1 The Research Problem 10.3.2 Methodology 10.4 Results from Case Study 10.4.1 Obtaining the Subjective Attribute Values 10.4.2 The Final Decision Matrix (FDM) 10.4.3 Normalizing the Alternatives 10.4.4 Obtaining the Weights for Attributes 10.4.5 Weighting the Normalized Matrix 10.4.6 Distance to Ideal Positive and Ideal Negative 10.4.7 Proximity Indexes 10.5 Conclusions References Part II Cases of Study 11 Bitcoin Price Forecasting Through Crypto Market Variables: Quantile Regression and Machine Learning Approaches 11.1 Introduction and Related Literature 11.2 Methodology 11.2.1 Quantile Regression Model 11.2.2 Machine Learning Approach 11.3 Data 11.3.1 Determining Data Set for Quantile Regression Model and Machine Learning 11.4 Empirical Results and Discussion 11.4.1 Quantile Regression Results 11.4.2 Machine Learning Results 11.5 Conclusions References 12 Crops Classification in Small Areas Using Unmanned Aerial Vehicles (UAV) and Deep Learning Pre-trained Models from Detectron2 12.1 Introduction 12.1.1 Technologies 4.0 for Crop Classification 12.1.2 Types of Images Obtained by UAVs 12.1.3 Artificial Intelligence Methods Applied in Agriculture 12.1.4 Methods for Object Detection with Deep Learning 12.1.5 Transfer Learning 12.2 Materials and Method 12.2.1 Study Area 12.2.2 Data Collection 12.2.3 Data Labeling 12.2.4 Data Description 12.2.5 Detectron2 12.2.6 Common Settings for COCO Models 12.2.7 ImageNet Pretrained Models 12.3 Results and Analysis 12.4 Conclusions 12.5 Future Work References 13 Design and Evaluation of Strategies to Mitigate the Impact of Dengue in Healthcare Institutions Through Dynamic Simulation 13.1 Introduction 13.2 State of the Art 13.3 Methodology 13.3.1 Conceptualization 13.3.2 Formulation 13.4 Results and Discussion 13.4.1 Test 13.4.2 Implementation 13.4.3 Sensitivity Analysis 13.5 Conclusion and Future Directions References 14 Detecting Arrhythmia Using the IoT Paradigm 14.1 Introduction 14.2 Related Work 14.3 Wearables for CVD Detection 14.4 A Web Application for AF Detection: Architecture and Functionality 14.5 Case Study: People Monitoring for Arrhythmia Detection 14.5.1 Application Features 14.5.2 Parameters and Rules for Arrhythmia Detection 14.5.3 Patient Monitoring 14.6 Conclusion and Future Directions References 15 Emotion Detection in Learning Environments Using Facial Expressions: A Brief Review 15.1 Introduction 15.2 State of the Art 15.3 API Analysis of Emotion Detection from Facial Expressions 15.4 Case Study: Emotions Recognition in a Learning Environment 15.5 Conclusion and Future Directions References 16 Face Recognition—Eigenfaces 16.1 Introduction 16.2 Background and Related Works 16.2.1 Eigenfaces 16.2.2 Linear Discriminant Analysis (LDA) 16.3 Datasets 16.4 Architecture, Models and Data Preparation 16.5 Results 16.5.1 Metrics Comparison and Outliers Detection 16.5.2 Eigenfaces 16.5.3 Face Space 16.5.4 Projection of an Image on the Face Space 16.5.5 Face Recognition 16.6 Conclusions References 17 Genetic Algorithm for the Optimization of the Unequal-Area Facility Layout Problem 17.1 Introduction 17.2 The Unequal-Area Facility Layout Problem 17.3 Genetic Algorithm for the Optimization of the UAFLP 17.3.1 Solution Encoding and Representation 17.3.2 Fitness Function 17.3.3 Selection Operator 17.3.4 Crossover and Mutation Operators 17.3.5 Validation of the GA for Optimizing the UAFLP 17.4 Results of the GA Optimization for the Case of the Garment Industry 17.5 Conclusions References 18 Microsimulation Calibration Integrating Synthetic Population Generation and Complex Interaction Clusters to Evaluate COVID-19 Spread 18.1 Introduction 18.2 Agent-Based Microsimulation and Its Application to Disease Spread 18.3 Synthetic Population Generation 18.4 Synthetic Population Generation Integrated with Complex Interaction Clusters 18.5 Application of the Proposed Synthetic Population Generation 18.6 Microsimulation of COVID-19 Spread 18.7 Conclusions References 19 A Decision Support System for Container Handling Operations at a Seaport Terminal with Disturbances: Design and Concepts 19.1 Introduction 19.2 Related Work 19.2.1 Yard Operations 19.2.2 DSS for Container Terminals 19.2.3 Disturbances in Container Terminals 19.3 Disturbances Characterization: Case Study of Chilean Ports 19.4 DSS Proposal and Concepts 19.5 Conclusion and Future Directions References