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Titlebook: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV; International Confer Michael Emmerich,Andre

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21#
發(fā)表于 2025-3-25 06:23:14 | 只看該作者
Training Multilayer Perceptron by Conformal Geometric Evolutionary Algorithm,on spheres and scaling. The main operation of the algorithm is based on geometric inversions of points with respect to sphere. CGEOA is applied to train a Multilayer Perceptron (MLP) using several benchmark data sets. We present a comparison of our results with other proposals of the state of the art in Artificial Neural Networks (ANNs).
22#
發(fā)表于 2025-3-25 08:39:05 | 只看該作者
23#
發(fā)表于 2025-3-25 14:11:08 | 只看該作者
A Hybrid Algorithm for the Simple Cell Mapping Method in Multi-objective Optimization, numerical exmaples to demonstrate the effectiveness of the proposed hybrid algorithm. The examples include two simple geometric MOPs, an example with five design parameters, and a proportional-integral-derivative (PID) control design for a second order linear system.
24#
發(fā)表于 2025-3-25 17:53:42 | 只看該作者
25#
發(fā)表于 2025-3-25 22:28:49 | 只看該作者
26#
發(fā)表于 2025-3-26 02:10:58 | 只看該作者
Adsorption of Flotation Collectors,em at hand. Due to their global approach, these methods are well-suited for the thorough investigation of small problems, including the computation of the set of approximate solutions. We conclude this work with the presentation of three academic bi-objective optimization problems including a comparison to a related evolutionary approach.
27#
發(fā)表于 2025-3-26 06:54:18 | 只看該作者
28#
發(fā)表于 2025-3-26 10:01:12 | 只看該作者
29#
發(fā)表于 2025-3-26 15:51:09 | 只看該作者
,Le théorème de Sch?nflies pour S2,sted as an alternative to non-dominated sorting. Besides the asymptotical analysis, we discuss empirical results on several test problems and discuss the impact of the overhead caused by maintaining additional AVL tree data structures, including scalability studies with very large population size that will yield high resolution approximations.
30#
發(fā)表于 2025-3-26 20:45:33 | 只看該作者
Sewer Network Design Optimization Problem Using Ant Colony Optimization Algorithm and Tree Growing etermine the cover depths of the constructed layout. Proposed formulation is used to solve three test examples of different scales and the results are presented and compared with other existing methods. The results indicate the efficiency of the proposed method to optimally solve the problem of layout and size determination of sewer network.
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