Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence explores elements of data mining, predictive modeling, forecasting, optimization, and adaptability. The book explains the application of numerous prediction and optimization techniques, and shows how these concepts can be used to develop adaptive systems. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling.
Preface
Part I : Complex Business Problems
Chapter 1 : Introduction
Chapter 2 : Characteristics of Complex Business Problems
Chapter 3 : An Extended Example : Car Distribution
Chapter 4 : Adaptive Business Intelligence
Part II : Prediction and Optimization
Chapter 5 : Prediction Methods and Models
Chapter 6 : Modern Optimization Techniques
Chapter 7 : Fuzzy Logic
Chapter 8 : Artificial Neural Networks
Chapter 9 : Other Methods and Techniques
Part III : Adaptive Business Intelligence
Chapter 10 : Hybrid Systems and Adaptability
Chapter 11 : Car Distribution System
Chapter 12 : Applying Adaptive Business Intelligence
Chapter 13 : Conclusion
Index
