Gent Intelligence Through Data Mining
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Agent Intelligence Through Data Mining
Author: Andreas L. Symeonidis
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-05-06
Knowledge, hidden in voluminous data repositories routinely created and maintained by today’s applications, can be extracted by data mining. The next step is to transform this discovered knowledge into the inference mechanisms or simply the behavior of agents and multi-agent systems. Agent Intelligence Through Data Mining addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. This book contains a methodology, tools and techniques, and several examples of agent-based applications developed with this approach. This volume focuses mainly on the use of data mining for smarter, more efficient agents. Agent Intelligence Through Data Mining is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.
Intelligent Manufacturing
This book introduces intelligent manufacturing system planning, design, and implementation, through the deep integration of the Internet, big data, artificial intelligence, and manufacturing process, to promote the transformation and upgrading of enterprises. This book shows the implementation of intelligent manufacturing process with 12 benchmarking enterprises, discusses the planning, implementation, and control of intelligent manufacturing system technology and method of theory, and analyzes the five hierarchies of intelligent manufacturing system, the five stages of life cycle, and five kinds of intelligent depth. The content can cultivate the reader's vocational ability to develop intelligent solutions and implementation based on complex, uncertain environment needs. This book will be interesting and useful to a wide readership in the various fields of management, information science, and engineering science.
Computational Intelligence in Intelligent Data Analysis
Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.