Soft Computing: Developments, Methods and Applications

This book discusses developments, methods and applications of soft computing. Chapter One depicts the increasing efficiency of the soft computing algorithms and fuzzy information processing models by developing a library of universal analytic models for fuzzy arithmetic operations with asymmetrical triangular fuzzy numbers (TrFNs). Chapter Two examines the determination of stability number of layered slope using Adaptive Neuro-Fuzzy Inference System (ANFIS), Gaussian Process Regression (GPR), Relevance Vector Machine (RVM), Extreme Learning Machine (ELM). Chapter Three discusses the intensive developing of Soft Computing systems especially Wavelet-Neuro-Fuzzy Systems (WNFS) in Dynamic Data Mining tasks, when the data are fed sequentially to the processing in on-line mode.

Table of Contents

Chapter 1: REDUCED LIBRARY OF THE SOFT COMPUTING ANALYTIC MODELS FOR ARITHMETIC OPERATIONS WITH ASYMMETRICAL FUZZY NUMBERS
Chapter 2: DETERMINATION OF STABILITY NUMBER OF LAYERED SLOPE USING ANFIS, GPR, RVM AND ELM
Chapter 3: MULTILAYER WAVELET-NEURO-FUZZY SYSTEMS IN DYNAMIC DATA MINING TASKS