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Titlebook: Data Mining and Big Data; 7th International Co Ying Tan,Yuhui Shi Conference proceedings 2022 The Editor(s) (if applicable) and The Author(

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樓主: Consonant
11#
發(fā)表于 2025-3-23 09:44:28 | 只看該作者
Knowledge Learning-Based Brain Storm Optimization Algorithm for?Multimodal Optimization. However, the existing studies fail to resolve the contradiction between the required solution accuracy and the number of solutions. In this paper, an improved brain storm optimization (BSO) algorithm based on knowledge learning (KLBSO) is proposed as a solution to the problem. The properties of th
12#
發(fā)表于 2025-3-23 16:29:55 | 只看該作者
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發(fā)表于 2025-3-23 18:56:43 | 只看該作者
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發(fā)表于 2025-3-24 00:22:39 | 只看該作者
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發(fā)表于 2025-3-24 02:51:17 | 只看該作者
https://doi.org/10.1007/978-981-19-8991-9artificial intelligence; computer hardware; computer networks; computer security; computer vision; correl
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發(fā)表于 2025-3-24 06:56:09 | 只看該作者
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發(fā)表于 2025-3-24 14:45:27 | 只看該作者
Communications in Computer and Information Sciencehttp://image.papertrans.cn/d/image/262920.jpg
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發(fā)表于 2025-3-24 17:42:20 | 只看該作者
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發(fā)表于 2025-3-24 21:48:33 | 只看該作者
Collineations and Conic Sectionsnal distributions of RBMs commonly produce effective features for the two tasks, building these expressive conditional distributions and sampling from the distributions are difficult for conventional RBMs. In this paper, a Complementary Convolutional Restricted Boltzmann Machine (CCRBM) is proposed.
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發(fā)表于 2025-3-25 02:38:20 | 只看該作者
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