Adaptive Business Intelligence
 
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Book Info


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 decision-making 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.

The authors have also used Adaptive Business Intelligence methodologies to assist in the development of the rapidly expanding and successful software company SolveIT Software. SolveIT Software Pty Ltd is an Australian company specialising in supply & demand optimisation, predictive modelling and mining solutions. Our mining software applications cover mining exploration management, mining logistics, mining simulation and Mine planning. Their customers include Rio Tinto Iron Ore, Rio Tinto Simandou, Xstrata Coal, Xstrata Copper, Xstrata Zinc, BHP Billiton Iron Ore, BMA Coal, Fortescue Metals Group, and Pacific National Coal.

This 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 this field.