Introduces CI in the framework of telecommunications and outlines the current trends in telecommunication networks

Focuses on the design of CI schemes with thorough explanations of how these models can be incorporated in any telecommunication architecture.

Presents contributions from an outstanding team of international experts

Includes numerous examples of in-depth analysis, comprehensive design schemes, detailed algorithms, and exercises

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.

Computational Intelligence: A Development Environment for Telecommunications Networks, W. Pedrycz and A. Vasilakos
Neural Network Methods for Call Admission Control, R.G. Ogier, and N. Taft-Plotkin
CaC and Computational Intelligence, R.G. Cheng and C.J. Chang
Fuzzy Connection Admission Control for ATM Networks, K. Uehara and K. Hirota
Congestion Control, A. Pitsillides and A. Sekercioglu
Fuzzy Queue for ERICA ATM Switch Controller, Y. Klein and A. Kandel
Fuzzy Rate Regulation with Feedback on Controllers in ATM Networks, C. Douligeris and Y.C. Liu
Applicability of Reinforcement Learning Algorithms to Usage Parameter Control, A. Atlasis and A. Vasilakosl
Networking Algorithms and Computational Intelligence, S. Ghosh, Q. Raxouqi, P. Seshasayi, T.S. Lee, and S.S. Joo
QoS-Based Hierarchical Routing in ATM Networks Using Reinforcement Learning Algorithms: A Methodology, M. Saltouros, A. Atlasis, A. Vailakos, and W. Pedrycz
Network Routing with the Use of Evolutionary Methods, M. Munetomo
Design and Use of Neural Network Applications in Telecommunications, R.J. Frank, N. Davey, and S.P. Hunt
Elements of Computational Intelligence for Network Management, P. Venkataram
Intelligent Monitoring for Network Fault Management, C.S. Hood and C. Ji
A Hybrid Genetic Approach for Channel Reuse in Multiple Access Telecommunication Networks, I. Kassotakis, M. Markaki, and A. Vasilakos
Use of Computational Intelligence Techniques for Designing Optical Networks, I. Chlamtac, A. Fumagalli, and L. Valcarenghi
Dynamic Channel Assignment Schemes Using Neural Networks, D. Tissainayagam, M. Palaniswami, and D. Everitt
Mobile Profile Prediction Using Fuzzy Inference in Cellular Networks, X. Shen and J.W. Mark
Intelligent Agents in Telecommunications Networks, C. Tsatsoulis and L.K. Soh

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