Adaptive Business Intelligence

by Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac

Overview

In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.

The authors have considerable academic research backgrounds in artificial intelligence and related fields, combined with years of practical consulting experience in businesses and industries worldwide. In this book they explain the science and application of numerous prediction and optimization techniques, as well as how these concepts can be used to develop adaptive systems. The techniques covered include 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.

This book is suitable for business and IT managers who make decisions in complex industrial and service environments, nonspecialists who want to understand the science behind better predictions and decisions, and students and researchers who need a quick introduction to this field.

Product Details

ISBN-13:	9783642069482
Publisher:	Springer Berlin Heidelberg
Publication date:	11/09/2010
Edition description:	Softcover reprint of hardcover 1st ed. 2006
Pages:	246
Product dimensions:	6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

Complex Business Problems.- Characteristics of Complex Business Problems.- An Extended Example: Car Distribution.- Adaptive Business Intelligence.- Prediction and Optimization.- Prediction Methods and Models.- Modern Optimization Techniques.- Fuzzy Logic.- Artificial Neural Networks.- Other Methods and Techniques.- Adaptive Business Intelligence.- Hybrid Systems and Adaptability.- Car Distribution System.- Applying Adaptive Business Intelligence.- Conclusions.

Editorial Reviews

From the reviews:

"In this book the authors explain the science and application of numerous prediction and optimization techniques as well as how these concepts can be used to develop adaptive decision-making systems. The book is suitable for business and IT managers who make decisions in complex industrial and service environments, non-specialists who want to understand the science behind better predictions and decisions, and students and researchers who need a quick introduction to the field." (OpenPR, December, 2006)

"The authors want to explain why the business intelligence industry can rely on systems that can make good decisions … . The second aim is to point out the principles behind many prediction methods and optimization techniques in simple terms, so that any business manager could grasp and apply them. … The authors third goal is to underscore the enormous applicability of ABI … . the main features, characteristic aspects, and useful arguments that make this book a novelty work and valuable textbook." (Neculai Curteanu, Zentralblatt MATH, Vol. 1122 (24), 2007)

"We believe that the authors have presented the selected material in a way that meets the interests of their targeted audience. ... These examples show the great potential of the approach that the book presents. ... If contemporary business managers read Adaptive Business Intelligence, we believe that they will become supporters of the proposed intelligent decision-making systems. We complete our review with the optimistic quotation from Chapter 13: "... the future of the business intelligence industry lies in systems that can predict, optimize, and adapt – put another way, the future of the industry lies in Adaptive Business Intelligence". Hopefully, this book will speed up our progress to such a future." (Antanas Zilinskas, Vilnius Pedagogical University, Interfaces – Int. J. of the Institute for Operations Research and the Management Sciences, 38(3)May–June 2008, pp. 212–220)

From the Publisher