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Titlebook: Knowledge-Based and Intelligent Information and Engineering Systems, Part I; 15th International C Andreas K?nig,Andreas Dengel,Lakhmi C. Ja

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樓主: brachytherapy
51#
發(fā)表于 2025-3-30 09:07:10 | 只看該作者
A Trajectory Tracking FLC Tuned with PSO for Triga Mark-II Nuclear Research Reactorr successfully tracks the given trajectory and reaches the desired power level with the optimized weights of rules. As a result, PSO-TTFLC could control the system successfully under all conditions within the acceptable error tolerance.
52#
發(fā)表于 2025-3-30 14:20:55 | 只看該作者
A New Classifier Ensembles Framework the performance of proposed framework is evaluated on some real datasets of UCI repository. Achieved results show effectiveness of the algorithm compare to the original bagging and boosting algorithms.
53#
發(fā)表于 2025-3-30 18:52:22 | 只看該作者
Distributed BitTable Multi-Agent Association Rules Mining Algorithmstems and complies with global communication standard Foundation for Intelligent Physical Agents (FIPA). The distributed Multi-Agent based algorithm with its new data structure improves implementations reported in the literature that were based on Apriori. The algorithm has better performance over Apriori-like algorithms.
54#
發(fā)表于 2025-3-31 00:23:43 | 只看該作者
Andreas K?nig,Andreas Dengel,Lakhmi C. JainUp-to-date results.Fast track conference proceedings.State-of-the-art report
55#
發(fā)表于 2025-3-31 01:40:05 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/k/image/544231.jpg
56#
發(fā)表于 2025-3-31 06:46:59 | 只看該作者
57#
發(fā)表于 2025-3-31 09:27:03 | 只看該作者
58#
發(fā)表于 2025-3-31 13:32:31 | 只看該作者
Adaptive Recurrent Neuro-Fuzzy Networks Based on Takagi-Sugeno Inference for Nonlinear Identificatioation in mechatronic systems. The parameter optimization of the RFNN is achieved using a differential evolutionary algorithm. The experimental results are analyzed using a study cases modeled in Simulink: the linear power amplifier and the actuator.
59#
發(fā)表于 2025-3-31 19:09:50 | 只看該作者
Evolution of Iterative Formulas Using Cartesian Genetic Programmingo automatically design simple iterative algorithms from elementary functions. In particular, we demonstrated that Cartesian Genetic Programming can evolve various iterative formulas for tasks such as division or determining the greatest common divisor using a reasonable computational effort.
60#
發(fā)表于 2025-3-31 23:51:40 | 只看該作者
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