Showing 1,301 - 1,320 results of 5,752 for search '"neural networks"', query time: 0.08s Refine Results
  1. 1301

    Research on Ethanol Coupling to Prepare C4 Olefins Based on BP Neural Network and Cluster Analysis by Sheng-Mei Zhang, Wen-Li Zhan, Han Hu, Yu-Shu Liu, Jia-Ming Zhu

    Published 2022-01-01
    “…Finally, according to the three-dimensional spatial visualization analysis and using the BP neural network model training data, we obtain that under the conditions of using loading method I, catalyst combination type 200 mg 0.5 wt% Co/SiO2-200 mg HAP-ethanol concentration 0.9 ml/min and temperature 450°C, the yield of C4 olefins can reach the maximum. …”
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    Automatic Detection of Small Intestinal Hookworms in Capsule Endoscopy Images Based on a Convolutional Neural Network by Tao Gan, Yulin Yang, Shuaicheng Liu, Bing Zeng, Jinlin Yang, Kai Deng, Junchao Wu, Li Yang

    Published 2021-01-01
    “…We sought to develop an artificial intelligence system with a convolutional neural network (CNN) to automatically detect hookworms in CE images. …”
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    Detecting Unauthorized Movement of Radioactive Material Packages in Transport with an Adam-Optimized BP Neural Network Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Chaofeng Wang, Yu Mao, Zhenghai Liu

    Published 2023-01-01
    “…In the present study, an innovative Adam-optimized BP neural network model is developed for detecting unauthorized movements of radioactive material packages. …”
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    Rough Set Neural Network Feature Extraction and Pattern Recognition of Shaft Orbits Based on the Zernike Moment by Xinfeng Ge, Jing Zhang, Ye Zhou, Jianguo Cai, Hui Zhang, Hongchang Hua, Dong Chen, Ming Zhao, Jinqi Du, Yuan Zheng

    Published 2021-01-01
    “…In getting the feature extraction and pattern recognition of a shaft orbit, the Zernike moment is better than the Hu moment; it has the advantages of a small calculation error and a high recognition rate. A rough set neural network (RS-BP hybrid model) of shaft orbit recognition is established, which uses just 13 moment eigenvalues reserved by the rough set feature selection algorithm as input variables; it has the same calculation error and recognition rate and reduces the calculation time step. …”
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    Neural Networks Based Adaptive Consensus for a Class of Fractional-Order Uncertain Nonlinear Multiagent Systems by Jing Bai, Yongguang Yu

    Published 2018-01-01
    “…Due to the excellent approximation ability, the neural networks based control method is used to achieve adaptive consensus of the fractional-order uncertain nonlinear multiagent systems with external disturbance. …”
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