Computational intelligence in telecommunications networks
Author(s)
Bibliographic Information
Computational intelligence in telecommunications networks
CRC Press, c2001
Available at 1 libraries
Note
Includes bibliographical references and index
Description and Table of Contents
Description
Telecommunications has evolved and grown at an explosive rate in recent years and will undoubtedly continue to do so. As its functions, applications, and technology grow, it becomes increasingly complex and difficult, if not impossible, to meet the demands of a global network using conventional computing technologies. Computational intelligence (CI) is the technology of the future-and the future is now.
Computational Intelligence in Telecommunications Networks offers an in-depth look at the rapid progress of CI technology and shows its importance in solving the crucial problems of future telecommunications networks. It covers a broad range of topics, from Call Admission Control, congestion control, and QoS-routing for ATM networks, to network design and management, optical, mobile, and active networks, and Intelligent Mobile Agents.
Today's telecommunications professionals need a working knowledge of CI to exploit its potential to overcome emerging challenges. The CI community must become acquainted with those challenges to take advantage of the enormous opportunities the telecommunications field offers. This text meets both those needs, clearly, concisely, and with a depth certain to inspire further theoretical and practical advances.
Table of Contents
Computational Intelligence: A Development for Telecommunications Networks. Neural Network Methods for the Call Admission Control. CaC and Computational Intelligence. Fuzzy Connection Admission Control for ATM Networks. Congestion Control. Fuzzy Queque for ERICA ATM Switch Controller. Fuzzy Rate Regulation with Feedback on Controllers. Applicability of Reinforcement Learning Algorithms to Usage Parameter Control. Networking Algorithms and Computational Intelligence. Qos-Based Hierarchical Routing in ATM Networks Using Reinforcement Learning Algorithms: A Methodology. Network Routing with the Use of Evolutionary Methods. Design and Use of Neural Network Applications in Telecommunications. Elements of Computational Intelligence for Network Management. Intelligent Monitoring for Network Fault Management. A Hybrid Genetic Approach for Channel Reuse in Multiple Access Telecommunications. Use of Computational Intelligence Techniques for Designing Optical Networks. Dynamic Channel Assignment Schemes Using Neural Networks. Mobile Profile Prediction Using Fuzzy Inference in Cellular Networks. Intelligent Agents in Telecommunications Networks.
by "Nielsen BookData"