Adaptive Business Intelligence

This is a preview of subscription content, log in via an institution to check access.

Access this book

Subscribe and save

Springer+ Basic €32.70 /Month

Buy Now

Price includes VAT (France)

Softcover Book EUR 49.57

Price includes VAT (France)

Hardcover Book EUR 68.56

Price includes VAT (France)

Tax calculation will be finalised at checkout

Other ways to access

About this book

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.

Similar content being viewed by others

An Introduction to Data Science and Its Applications

Chapter © 2020

Introduction to Optimization

Chapter © 2019

Theory and Practice of Application of Artificial Intelligence Methods

Article 01 March 2019

Keywords

Table of contents (13 chapters)

Front Matter

Pages I-XIII

Complex Business Problems

Front Matter

Introduction

Characteristics of Complex Business Problems

An Extended Example: Car Distribution

Pages 25-36

Adaptive Business Intelligence

Pages 37-46

Prediction and Optimization

Front Matter

Pages 47-47

Prediction Methods and Models

Pages 49-74

Modern Optimization Techniques

Pages 75-115

Fuzzy Logic

Pages 117-129

Artificial Neural Networks

Pages 131-149

Other Methods and Techniques

Pages 151-174

Adaptive Business Intelligence

Front Matter

Pages 175-175

Hybrid Systems and Adaptability

Pages 177-190

Car Distribution System

Pages 191-213

Applying Adaptive Business Intelligence

Pages 215-238

Conclusions

Pages 239-242

Back Matter

Pages 243-246

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)

Authors and Affiliations

School of Computer Science, University of Adelaide, Adelaide, Australia

SolveIT Software Pty Ltd, Adelaide, Australia

Bibliographic Information