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Titlebook: Intelligent Information Processing XI; 12th IFIP TC 12 Inte Zhongzhi Shi,Jean-Daniel Zucker,Bo An Conference proceedings 2022 IFIP Internat

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樓主: CILIA
31#
發(fā)表于 2025-3-26 20:59:03 | 只看該作者
32#
發(fā)表于 2025-3-27 02:47:09 | 只看該作者
33#
發(fā)表于 2025-3-27 05:47:53 | 只看該作者
nistrativer Hilfen. Obgleich bereichsspezifische Unterschiede hinsichtlich der Partizipation von Sozialklientelen existieren, ist die Sozialbürgerrolle im politisch-administrativen Kontext insgesamt gesehen nur gering verankert. Vertikal dominiert die Sicht “von oben”, der hierarchisch aufgebaute Be
34#
發(fā)表于 2025-3-27 10:00:35 | 只看該作者
35#
發(fā)表于 2025-3-27 14:21:29 | 只看該作者
Comparative Study of Chaos-Embedded Particle Swarm Optimizationer, like other evolutionary algorithms, PSO also suffers from premature convergence and entrapment into local optima when addressing complex multimodal problems. In this paper, we propose a chaos-embedded particle swarm optimization algorithm (CEPSO). In CEPSO, the chaos-based swarm initialization i
36#
發(fā)表于 2025-3-27 20:16:23 | 只看該作者
A Novel Feature Selection Algorithm Based on?Aquila Optimizer for?COVID-19 Classificationainst the epidemic. This paper is to perform feature selection on the CT image feature sets used for COVID-19 detection to improve the speed and accuracy of detection. In this work, the population-based intelligent optimization algorithm Aquila optimizer is used for feature selection. This feature s
37#
發(fā)表于 2025-3-28 00:06:14 | 只看該作者
38#
發(fā)表于 2025-3-28 02:58:49 | 只看該作者
39#
發(fā)表于 2025-3-28 06:48:56 | 只看該作者
A Hybrid Multi-objective Optimization Algorithm with?Improved Neighborhood Rough Sets for?Feature Setimal feature subset with smaller size and higher classification accuracy from high-dimensional data. In this paper, a new approach for feature selection using multi-objective optimization algorithm with improved neighborhood rough sets is proposed. Firstly, the improved neighborhood positive region
40#
發(fā)表于 2025-3-28 13:20:38 | 只看該作者
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