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	A Two-layer Encoding Learning Swarm Optimizer based on Frequent Itemsets for Sparse Large-scale Multi-objective Optimization 期刊论文 OAI收割 IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1342-1357 作者: Sheng Qi; Rui Wang; Tao Zhang; Xu Yang; Ruiqing Sun \| 收藏 \| 浏览/下载：7/0 \| 提交时间：2024/05/22 Evolutionary algorithms learning swarm optimization sparse large-scale optimization sparse large-scale multi-objective problems two-layer encoding
	Supervised representation learning for multi-label classification 期刊论文 OAI收割 MACHINE LEARNING, 2019, 卷号: 108, 期号: 5, 页码: 747-763 作者: Niu, Zhengyu; Huang, Ming; Zhuang, Fuzhen; Zhang, Xiao; Ao, Xiang \| 收藏 \| 浏览/下载：66/0 \| 提交时间：2019/08/16 Representation learning Multi-label learning Two-encoding-layer autoencoder
	Study on color model conversion for camera with neural network based on the combination between second general revolving combination design and genetic algorithm (EI CONFERENCE) 会议论文 OAI收割 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Z.; Zhou F.; Wang C.; Li Z. 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and Lab* color model for camera. The color luminance meter and CCD camera synchronously measure the same color card XYZ value is gotten from the color luminance meter the training error is 0.000748566 it can show that the method combining second general revolving combination design with genetic algorithm can optimize the hidden-layer structure of neural network. Using the data of testing set to test this network and calculating the color difference between forecast value and true value the color picture captured from CCD camera is expressed for RGB value as the input of neural network and the Lab* value converted from XYZ value is regarded as the real color value of target card which the difference is not obvious comparing with forecast result the maximum is 5.6357 NBS namely the output of neural network. The neural network of two hidden-layers is considered the minimum is 0.5311 NBS so the second general revolving combination design is introduced into optimizing the structure of neural network and the average of color difference is 3.1744 NBS. which can carry optimization through unifying project design data processing and the precision of regression equation. Their mathematics model of encoding space is gained and the significance inspection shows the confidence degree of regression equation is 99%. The mathematics model is optimized by genetic algorithm optimization solution is gotten and function value of the goal is 0.0007168. The neural network of the optimization solution is trained
	遗传算法及其在机器人技术中的应用学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院自动化研究所, 1999 刘雁飞收藏 \| 浏览/下载：73/0 \| 提交时间：2015/09/02 遗传算法两层编码机械手控制路径规划 genetic algorithms two-layer encoding manipulator control robot path planning