Bio-Inspired Computation in Telecommunications
(Sprache: Englisch)
Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and...
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Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students.
Inhaltsverzeichnis zu „Bio-Inspired Computation in Telecommunications “
1. Bio-Inspired Computation and Optimization: An Overview 2. Bio-inspired Approaches in Telecommunications Firefly Algorithm in Telecommunications 3. A Survey of Intrusion Detection Systems Using Evolutionary Computation 4. VoIP Quality Prediction Model by Bio-inspired Methods, On the impact of Differential Evolution parameters solving the Survivable Virtual Topology Mapping Problem in IP-over-WDM Networks, Radio Resource Management by Evolutionary Algorithms for 4G LTE-Advanced Networks 5. Robust Transmission for Heterogeneous Networks with Cognitive Small Cells 6. Ecologically-inspired Resource Distribution Techniques for Sustainable Communication Networks 7. Multi-objective Optimization in Optical Networks 8. Cell Coverage Area Optimization based on Particle Swarm Optimization (PSO) for Green Macro Long-term Evolution (LTE) Cellular Network 9. Bio-Inspired Computation for Solving the Optimal Coverage Problem in Wireless Sensor Networks: A Binary Particle Swarm Optimization Approach 10. Clonal Selection based Minimum Interference Channel Assignment Algorithms for Multi-radio Wireless Mesh Networks
Autoren-Porträt von Xin-She Yang, Su Fong Chien, T.O. Ting
Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. He is currently a Reader at Middlesex University London, Adjunct Professor at Reykjavik University (Iceland) and Guest Professor at Xi'an Polytechnic University (China). He is an elected Bye-Fellow at Downing College, Cambridge University. He is also the IEEE CIS Chair for the Task Force on Business Intelligence and Knowledge Management, and the Editor-in-Chief of International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO). Chien Su Fong is an associate professor of Engineering & Technology at Multimedia University Malaysia where his research focuses in networking, wireless communications and optical switching technology. He is a frequent presenter at the IEEE International Conference on Communications and a member of the Optical Society of America (OSA). T.O. Ting is currently a Lecturer with the Department of Electrical and Electronic Engineering, Xian Jiaotong-Liverpool University. He obtained his Ph.D in Electrical Engineering from The Hong Kong Polytechnic University. His current research interests focus on the application of Computational Intelligence techniques in Engineering Optimization. He has recently presented his research as an invited speaker at the IEEE Asia Pacific Conference on Circuits and Systems and The Asia-Pacific Conference on Communications.
Bibliographische Angaben
- Autoren: Xin-She Yang , Su Fong Chien , T.O. Ting
- 2015, 348 Seiten, Maße: 23,7 x 18,9 cm, Kartoniert (TB), Englisch
- Verlag: Morgan Kaufmann
- ISBN-10: 0128015381
- ISBN-13: 9780128015384
- Erscheinungsdatum: 10.02.2015
Sprache:
Englisch
Pressezitat
"...reading this book will broaden your horizons with regard to how one could solve optimization problems by applying bio-inspired algorithms, with particular emphasis on telecommunications networks...It could be used for courses related to telecommunications, as well as for courses related to advanced algorithmics." --Computing Reviews
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