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

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