This book focuses on the main advancements made in the economics and social sciences field through the use of grey systems theory. As a result, it addresses both the state of the art and the applications of grey systems theory in economics and social sciences. The book is structured in eight main chapters, covering the following topics: the state of the art in the grey systems theory research in economics and social sciences, which includes a bibliometric analysis, a selection of the most well-cited papers in the field, and a selection of applications in which the grey systems theory is used in the areas of suppliers selection, risk assessment, public opinion assessment, linear programming, complex projects management, social media analysis, and natural language processing
Each chapter gives an overview of a particular economic or social sciences topic, providing an explanation on the main terms and methods used for solving the problem, including the notations, terminology, and the needed steps to solve it. A practical application is presented in most of the chapters, while in the others, a series of case studies are presented from the literature and discussed in depth in terms of methods used and advantages brought by each of these methods. The last chapter discusses the hybridization cases in which the grey systems theory has been or can be successfully used along with other artificial intelligence methods and techniques for a more advanced analysis in the economics and social sciences field.
The reasoning and the explanations used in the book are easy to understand for the interested persons who are not familiar to the field and want to learn more related on how the grey systems theory can be applied to economics and social sciences. As for the experts in this field, this book can be a good referral point for developing new areas of research by combining the advantages of the grey systems theory with other theories within the field.
Author(s): Camelia Delcea, Liviu-Adrian Cotfas
Series: Series on Grey System
Publisher: Springer
Year: 2023
Language: English
Pages: 339
City: Singapore
Contents
1 State of the Art in Grey Systems Research in Economics and Social Sciences
Introduction
Materials and Methods
Dataset Analysis
Dataset Overview
Sources
Authors
Papers’ Analysis
Mixed Analysis
Concluding Remarks
References
2 Grey Numbers for Sentiment Analysis and Natural Language Processing
Introduction
Sentiment Analysis Lexicons
Grey Numbers
Arithmetic of Grey Numbers
Basic Operations
Examples of Basic Operations
Comparison of Grey Numbers
Discrete Grey Numbers Comparison
Interval Grey Numbers Comparison
Sentiment Analysis Using Grey Numbers
Concluding Remarks
References
3 Supplier Selection Using Grey Systems Theory
Introduction
State of the Art in Supplier Selection Through Grey Systems Theory Approach
Bibliometric Analysis
Grey Supplier Selection
Application of Grey Numbers to Supplier Selection
Xie and Xin Approach to Supplier Selection Based on Grey Numbers
Practical Application on Supplier Selection
Concluding Remarks
Annex A: The Code for Determining the Probability P( otimesa leotimesb )
References
4 Risk Assessment and Transport Cost Reduction Based on Grey Clustering
Introduction
Literature Review
Literature Review on Airplane Boarding
Literature Review on Grey Clustering
Grey Clustering and Whitenization Weight Functions
Assumptions and Metrics
Assumptions on Social Distance Measures
Assumptions on Variations in Back-to-Front Boarding Method
Metrics
Agent-Based Model Implementation
Results
Simulation Results for the Considered Metrics
Grey Clustering of the Variations in Back-to-Front Boarding Method
Concluding Remarks
References
5 Public Opinion Assessment Through Grey Relational Analysis Approach
Introduction
Argument for the Public Opinion Assessment in the COVID-19 Vaccination Context
Literature Review
Literature Review on COVID-19 Vaccination
Literature Review on Grey Relational Analysis
Methodology
Dataset Collection
Classifier Selection
Stance Detection
Grey Relational Analysis
News Incidence Detection
Dataset Characteristics
Classifier Selection
Stance Detection
News Incidence on People’s Opinion
Concluding Remarks
References
6 Grey Systems Theory Approach to Linear Programming
Introduction
Brief Presentation of Linear Programming Basic Elements
Forms of the Linear Programming Problem
Feasible Solutions, Feasible Region and Optimal Solutions
Numerical Example
Grey Linear Programming
Literature Review on Grey Linear Programming
Theoretical Approach to Grey Linear Programming
Whitening Parameters Models
Liu and Lin’s Prediction Type Model
Lin and Liu’s Positioned Solution Model
Concluding Remarks
References
7 Complex Projects Management with Interval Grey Numbers
Introduction
Brief Presentation of Projects Management
Activities and the Precedence Relationships
Network Representation
Gantt Diagram
Literature Review on Grey Systems Theory in Projects Management
Theoretical and Practical Approach to Project Scheduling with Grey Numbers
Theoretical Approach to Project Scheduling with Grey Numbers
Practical Approach to Project Scheduling with Grey Numbers
Concluding Remarks
References
8 Hybrid Approaches Featuring Grey Systems Theory
Introduction
Grey-Fuzzy Approaches in Economics and Social Sciences
Dataset Overview
Sources
Authors
Papers’ Analysis
Mixed Analysis
Grey-Neural Networks Approaches in Economics and Social Sciences
Dataset Overview
Sources
Authors
Papers’ Analysis
Mixed Analysis
Grey-Genetic Algorithms Approaches in Economics and Social Sciences
Dataset Overview
Sources
Authors
Papers’ Analysis
Mixed Analysis
Grey-Rough Sets Approaches in Economics and Social Sciences
Dataset Overview
Sources
Authors
Papers’ Analysis
Mixed Analysis
Concluding Remarks
References
