By Witold Pedrycz, Athanasios Vasilakos
Telecommunications has developed and grown at an explosive cost lately and may certainly proceed to take action. As its services, purposes, and expertise develop, it turns into more and more complicated and tough, if now not most unlikely, to fulfill the calls for of a world community utilizing traditional computing applied sciences. Computational intelligence (CI) is the expertise of the future-and the long run is now. Computational Intelligence in Telecommunications Networks bargains an in-depth examine the fast development of CI expertise and exhibits its value in fixing the the most important difficulties of destiny telecommunications networks. It covers a huge diversity of subject matters, from name Admission keep an eye on, congestion keep watch over, and QoS-routing for ATM networks, to community layout and administration, optical, cellular, and energetic networks, and clever cellular Agents.Today's telecommunications execs want a operating wisdom of CI to use its strength to beat rising demanding situations. The CI group needs to turn into accustomed to these demanding situations to exploit the large possibilities the telecommunications box bargains. this article meets either these wishes, basically, concisely, and with a intensity bound to encourage additional theoretical and useful advances.
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Additional info for Computational intelligence in telecommunications networks
Delay and CLR). , the decision threshold) for all calls in the stream. fm Page 36 Tuesday, August 1, 2000 3:08 PM 36 Computational Intelligence in Telecommunications Networks to be compared with the relevant decision threshold before a call is accepted. , trained to learn 0 for accept and 1 for reject), the output is compared to a threshold such as 1/2. ) The choice of output influences which CAC problem is being modeled. Consider the case in which the output is a queue-related parameter, such as delay or loss.
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