Systems Science: Methodological Approaches

Summary

By making use of the principles of systems science, the scientific community can explain many complicated matters of the world and shed new light on unsettled problems. Each real science has its own particular methodology for not only qualitative but also quantitative analyses, so it is important to understand the organic whole of systems research with operable mathematical methods. Systems Science: Methodological Approaches presents a mathematical explanation of systems science, giving readers a complete technical formulation of different systemic laws. It enables them to use a unified methodology to attack different problems that are hard, if not impossible, for modern science to handle.

Following a brief history of systems science, the book explores:

• Basic concepts, characteristics, properties, and classifications of general systems
• Nonlinear systems dynamics and the theory of catastrophe
• Dissipative structures and synergistics
• Studies of chaos, including logistic mapping, phase space reconstruction, Lyapunov exponents, and chaos of general single relation systems
• Different aspects and concepts of fractals, including a presentation of L systems analysis and design
• Complex systems and complexity, with a discussion of how the phenomena of "three" and complexity are related, and how various cellular automata can be constructed to generate useful simulations and figurative patterns
• Complex adaptive systems and open complex giant systems, with introduction of the yoyo model and practical applications
• Complex networks and related concepts and methods

The book concludes with several case studies that demonstrate how various concepts and the logic of systems can be practically applied to resolve real-life problems, such as the prediction of natural disasters. The book will be useful in directing future research and applications of systems science on a commonly accepted platform and playground.

Table of Contents

A Brief History of Systems Science
What Is Systems Science?
Development History of Systems Science
System of Modern Science and Technology
Disciplinary Characteristics of Systems Science
Some Philosophical Thoughts of Systems Science
Philosophical Significance of Systemic Epistemology
Some Unsettled Questions
Organization of This Book
Open-End Problems
Concepts, Characteristics, and Classifications of Systems
Fundamental Concepts
Properties of Systems
Dynamics and Time Systems
Classification of Systems
Systems Defined on Dynamic Sets
Open-End Problems
Nonlinear Systems Dynamics and Catastrophe
Mathematical Description of Systems Dynamics
Dynamic Systems Theory of Nonlinear Systems
Catastrophe Theory
Open-End Problems
Self-Organization: Dissipative Structures and Synergetics
Organization and Self-Organization
Dissipative Structures
Synergetics
Some Philosophical Thoughts
Open-End Problems
Chaos
Phenomena of Chaos
Definition of Chaos
Logistic Mapping—Chaos Model
Phase Space Reconstruction
Lyapunov Exponents
Case Studies and Fields of Applications
Some Philosophical Thoughts on Chaos
Chaos of General Single-Relation Systems
Open-End Problems
Fractals
Different Aspects of Fractals
L-Systems—Analysis and Design
Iterative Function Systems
Open-End Problems
Complex Systems and Complexity
Simple Giant Systems
Characteristic Analysis of Complex Systems
Complexity
Cases on Association of Complexity and Simplicity
Conservation Law of Informational Infrastructure
Open-End Problems
Complex Adaptive Systems
Basics of Complex Adaptive Systems
How an Agent Adapts and Learns
From Parts to Whole—The ECHO Model
Modeling CASs with ECHO
Swarm Simulation Platform
Open-End Problems
Open Complex Giant Systems
Classification of Giant Systems
Open Complex Giant Systems
Internet—An Open Complex Giant System
Significance of Studying Open Complex Giant Systems
Research Methods of Open Complex Giant Systems
Systemic Yoyos: Combined Qualitative and Quantitative Model
Examples of Applications
Open-End Problems
Complex Networks
Introduction
Complex Network Models
Generation Mechanism
Processes on Complex Networks
Network and Complexity
Open-End Problems
Case Studies
Systems Evaluation
Systems Scientific Analysis for Positioning Accuracy of Satellite
Navigation System
Temporal Analysis of Social Networks
Values of College Students in China
Bibliography
Index

Author(s) Bio

Dr. Yi Lin, also known as Jeffrey Yi-Lin Forrest, is a specially appointed professor in economics, finance, systems science, and mathematics at several major universities in China as well as tenured professor of mathematics at the Pennsylvania State System of Higher Education (Slippery Rock campus). His research interests are mainly in the area of systems research and applications in a wide-ranging number of disciplines of the traditional sciences, including mathematical modeling, foundations of mathematics, data analysis, theory and methods of predictions of disastrous natural events, economics and finance, management science, and philosophy of science.

Dr. Xiaojun Duan is a professor at the Department of Mathematics and System Sciences, College of Science, National University of Defense Technology, Changsha, China. Her research interests include general systems theory and applications, data analysis, and complex system test and evaluation.

Mr. Chengli Zhao is a lecturer at the Department of Mathematics and Systems Science of the National University of Defense Technology. Mr. Zhao’s scientific interests and publications cover studies of complex systems, massive data computing, and web data mining.