Adaptive Business Intelligence
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In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization tools to assist decision makers in complex, rapidly changing environments. Such systems address the fundamental questions: What will happen next? What should I do about that?
The authors have considerable academic research backgrounds in AI and related fields, combined with years of practical consulting experience in businesses and industries worldwide. They explain the science and techniques of soft computing in a simple coherent manner, covering predictive data mining; modern optimization techniques such as genetic algorithms, simulated annealing, tabu searching, and ant systems; Monte Carlo simulations; agent-based systems; genetic programming; neural networks; and fuzzy systems.
This book will be suitable for nonspecialists such as managers who use tools based on soft computing in complex industrial and service environments and for researchers from other domains who need a quick introduction to this field.
The authors have considerable academic research backgrounds in AI and related fields, combined with years of practical consulting experience in businesses and industries worldwide. They explain the science and techniques of soft computing in a simple coherent manner, covering predictive data mining; modern optimization techniques such as genetic algorithms, simulated annealing, tabu searching, and ant systems; Monte Carlo simulations; agent-based systems; genetic programming; neural networks; and fuzzy systems.
This book will be suitable for nonspecialists such as managers who use tools based on soft computing in complex industrial and service environments and for researchers from other domains who need a quick introduction to this field.
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.
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.
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