Table of Contents:
“...5.2.1 Introduction -- 5.2.2 Adaptive GA -- 5.2.3 Hybrid GA -- 5.2.4 Parallel GA -- 5.2.5 Messy GA -- 5.2.6 Real Coded GA -- 5.2.7 Summary -- 5.3 Genetic
Programming -- 5.3.1 Introduction -- 5.3.2 Characteristics of GP -- 5.3.2.1 Human-Competitive -- 5.3.2.2 High-Return -- 5.3.2.3 Routine -- 5.3.2.4 Machine Intelligence -- 5.3.3 Working of GP -- 5.3.3.1 Preparatory Steps of Genetic
Programming -- 5.3.3.2 Executional Steps of Genetic
Programming -- 5.3.3.3 Fitness Function -- 5.3.3.4 Functions and Terminals -- 5.3.3.5 Crossover Operation -- 5.3.3.6 Mutation -- 5.3.4
Data Representation -- 5.3.4.1 Biological Representations -- 5.3.4.2 Biomimetic Representations -- 5.3.4.3 Enzyme Genetic
Programming Representation -- 5.3.5 Summary -- Bibliography -- 6: Hybrid Systems -- 6.1 Introduction -- 6.1.1 Neural Expert Systems -- 6.1.2 Approximate Reasoning -- 6.1.3 Rule Extraction -- 6.2 Neuro-Fuzzy -- 6.2.1 Neuro-Fuzzy Systems -- 6.2.2 Learning the Neuro-Fuzzy System -- 6.2.3 Summary -- 6.3 Neuro Genetic -- 6.3.1 Neuro-Genetic (NGA) Approach -- 6.4 Fuzzy Genetic -- 6.4.1 Genetic Fuzzy Rule-
Based Systems -- 6.4.2 The Keys to the Tuning/Learning
Process -- 6.4.3 Tuning the Membership Functions -- 6.4.4 Shape of the Membership Functions -- 6.4.5 The Approximate Genetic Tuning
Process -- 6.5 Summary -- Bibliography -- 7:
Data Statistics and Analytics -- 7.1 Introduction -- 7.2
Data Analysis: Spatial and Temporal -- 7.2.1 Time Series Analysis -- 7.2.2 One-Way ANOVA -- 7.2.3 Autocorrelation -- 7.2.4 Rank von Neumann (RVN) Test -- 7.2.5 Seasonal Mann-Kendall Test -- 7.3
Data Pre-
Processing -- 7.3.1
Data Cleaning -- 7.3.2
Data Integration -- 7.3.3
Data Transformation -- 7.3.4
Data Reduction -- 7.3.5
Data Discretization -- 7.4 Presentation of
Data -- 7.4.1 Tabular Presentation -- 7.4.2 Graphical Presentation -- 7.4.3 Text Presentation -- 7.5 Summary -- Bibliography....
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