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Titlebook: Current Topics in Artificial Intelligence; 13th Conference of t Pedro Meseguer,Lawrence Mandow,Rafael M. Gasca Conference proceedings 2010

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楼主: microbe
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https://doi.org/10.1007/978-3-211-74420-8 engine that integrate a Perceptron Multilayer neural network during the re-use phase to classify incoming SOAP messages and reject those that are considered malicious. A prototype of the architecture was developed and the results obtained are presented in this study.
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Automated Constraint Selection for Semi-supervised Clustering Algorithmled data instances, from which constraints can be derived, ranks these instances on their usability and then derives constraints from the top-ranked instances only. Our experiments show that . chooses, respectively reduces, the set of candidate constraints without compromising the quality of the derived model.
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A Multiagent Solution to Adaptively Classify SOAP Message and Protect against DoS Attack engine that integrate a Perceptron Multilayer neural network during the re-use phase to classify incoming SOAP messages and reject those that are considered malicious. A prototype of the architecture was developed and the results obtained are presented in this study.
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Analyzing the Influence of Differential Constraints in Possible Conflict and ARR Computational Intelligence and Control Theory communities have provided different but complementary approaches. Recent works, known as BRIDGE proposal, provided a common framework for the integration of techniques for static systems..This work proposes the extension of the BRIDGE framework for a specific class
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On the Complexity of Program Debugging Using Constraints for Modeling the Program’s Syntax and Semanms of debugging accuracy is good. Unfortunately, most of the proposed models and techniques have very high computational needs. In this paper we focus on giving an explanation for the high computational needs of debugging. In particular, we propose a constraint representation of programs whose behav
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An Analysis of Particle Properties on a Multi-swarm PSO for Dynamic Optimization Problemsts best performing variants is the one based on the atomic model, with quantum and trajectory particles. However, there is no precise knowledge on how these particles contribute to the global behavior of the swarms during the optimization process. This work analyzes several aspects of each type of p
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