Fuzzy cognitive maps : advances in theory, methodologies, tools and applications
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Bibliographic Information
Fuzzy cognitive maps : advances in theory, methodologies, tools and applications
（Studies in fuzziness and soft computing, 247）
Springer, c2010
- hbk.
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This important edited volume is the first such book ever published on fuzzy cognitive maps (FCMs). Professor Michael Glykas has done an exceptional job in bringing together and editing its seventeen chapters. The volume appears nearly a quarter century after my original article "Fuzzy Cognitive Maps" appeared in the International Journal of Man-Machine Studies in 1986. The volume accordingly reflects many years of research effort in the development of FCM theory and applications-and portends many more decades of FCM research and applications to come. FCMs are fuzzy feedback models of causality. They combine aspects of fuzzy logic, neural networks, semantic networks, expert systems, and nonlinear dynamical systems. That rich structure endows FCMs with their own complexity and lets them apply to a wide range of problems in engineering and in the soft and hard sciences. Their partial edge connections allow a user to directly represent causality as a matter of degree and to learn new edge strengths from training data. Their directed graph structure allows forward or what-if inferencing. FCM cycles or feedback paths allow for complex nonlinear dynamics. Control of FCM nonlinear dynamics can in many cases let the user encode and decode concept patterns as fixed-point attractors or limit cycles or perhaps as more exotic dynamical equilibria. These global equilibrium patterns are often "hidden" in the nonlinear dynamics. The user will not likely see these global patterns by simply inspecting the local causal edges or nodes of large FCMs.
Table of Contents
Fuzzy Cognitive Maps: Basic Theories and Their Application to Complex Systems.- Expert-Based and Computational Methods for Developing Fuzzy Cognitive Maps.- A Novel Approach on Constructed Dynamic Fuzzy Cognitive Maps Using Fuzzified Decision Trees and Knowledge-Extraction Techniques.- The FCM Designer Tool.- Fuzzy Cognitive Networks: Adaptive Network Estimation and Control Paradigms.- Modeling of Operative Risk Using Fuzzy Expert Systems.- Fuzzy Cognitive Maps in Banking Business Process Performance Measurement.- Fuzzy Cognitive Maps-Based IT Projects Risks Scenarios.- Software Reliability Modelling Using Fuzzy Cognitive Maps.- Fuzzy Cognitive Networks for Maximum Power Point Tracking in Photovoltaic Arrays.- Fuzzy Cognitive Maps Applied to Computer Vision Tasks.- Classifying Patterns Using Fuzzy Cognitive Maps.- Dynamic Fuzzy Cognitive Maps for the Supervision of Multiagent Systems.- Soft Computing Technique of Fuzzy Cognitive Maps to Connect Yield Defining Parameters with Yield in Cotton Crop Production in Central Greece as a Basis for a Decision Support System for Precision Agriculture Application.- Analysis of Farmers' Concepts of Environmental Management Measures: An Application of Cognitive Maps and Cluster Analysis in Pursuit of Modelling Agents' Behaviour.- Using Fuzzy Cognitive Maps to Support the Analysis of Stakeholders' Views of Water Resource Use and Water Quality Policy.- Fuzzy Cognitive Map to Support Conflict Analysis in Drought Management.
by "Nielsen BookData"