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Titlebook: Applications of Evolutionary Computing; EvoWorkshops 2008: E Mario Giacobini,Anthony Brabazon,Shengxiang Yang Conference proceedings 2008 S

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发表于 2025-3-21 18:41:15 | 显示全部楼层 |阅读模式
期刊全称Applications of Evolutionary Computing
期刊简称EvoWorkshops 2008: E
影响因子2023Mario Giacobini,Anthony Brabazon,Shengxiang Yang
视频videohttp://file.papertrans.cn/160/159414/159414.mp4
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Applications of Evolutionary Computing; EvoWorkshops 2008: E Mario Giacobini,Anthony Brabazon,Shengxiang Yang Conference proceedings 2008 S
影响因子Evolutionary computation (EC) techniques are e?cient, nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these me- ods can be used in the context of problem solving, optimization, and machine learning. A large and continuously increasing number of researchers and prof- sionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and - spire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoWorkshops 2008, which consisted of a range of workshops on application-oriented aspects of EC. Since 1998, EvoWorkshops has provided a unique opportunity for EC researchers to meet and discuss applicationaspectsofECandhasservedasanimportantlink between EC research and its application in a variety of domains. During these ten years new workshops have arisen,
Pindex Conference proceedings 2008
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Encyclopedia of Machine Learningrules are evolved using two different representations. The first is the classical single tree approach, while the second is a dual tree structure where evaluation is contingent on the current market position. Hence, buy and sell rules are co-evolved. Both methods are capable of discovering significant statistical arbitrage strategies.
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https://doi.org/10.1007/978-0-387-30164-8consists in optimizing the number and location of paging cells to find the lowest location management cost. There is a need to develop techniques capable of operating with this complexity and used to solve a wide range of location management scenarios. Nature inspired algorithms are useful in this c
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https://doi.org/10.1007/978-0-387-30164-8t, the limited resources and also new interferences constraints on transmitters. This new problem is public since the publication [1] with a set of 10 instances. The computing resources and the computing times are imposed. We tackle this problem with a method based on adaptive local search coming fr
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Adaptive Real-Time Dynamic Programmingathematical formulation in which the frequency plans are evaluated using accurate interference information coming from a real GSM network. We have developed an improved version of the scatter search (SS) algorithm in order to solve this problem. After accurately tuning this algorithm, it has been co
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