Titlebook: Real-World Applications of Evolutionary Computing; EvoWorkshops 2000: E Stefano Cagnoni Conference proceedings 2000 Springer-Verlag Berlin

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Scene Interpretation using Semantic Nets and Evolutionary Computationan estimation of the nearness to an ideal solution or the distance from a default solution. In image scene interpretation, the solution takes the form of a set of labels corresponding to the components of an image and its fitness is difficult to conceptualize in terms of distance from a default or n

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Evolutionary Wavelet Bases in Signal Spacesevolutionary algorithms. An evolutionary algorithm to optimize signal representations by adaptively choosing a basis depending on the signal is presented. We show how evolutionary algorithms can be exploited to search larger waveform dictionaries for best basis selection than those considered in cur

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On the Scalability of Genetic Algorithms to Very Large-Scale Feature Selection carry out. Past studies therefore were rather limited in either the cardinality of the feature space or the number of patterns utilised to assess the feature subset performance..This study examines the scalability of Distributed Genetic Algorithms to very large-scale Feature Selection. As domain of

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Distributed Learning Control of Traffic Signalseffectively only one (low) level of control. Such strategy is aimed at incorporating computational intelligence techniques into the control system to increase the response time of the controller. The idea is implemented by employing learning classifier systems and TCP/IP based communication server,

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Time Series Prediction by Growing Lateral Delay Neural Networksowever, the design of these networks requires much experience and understanding to obtain useful results. In this paper, an evolutionary computing based innovative technique to grow network architecture is developed to simplify the task of time-series prediction. An efficient training algorithm for