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Application of deep learning in ecological resource research: Theories, methods, and challenges 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1457-1474
作者:  Guo, Qinghua;  Jin, Shichao;  Li, Min;  Yang, Qiuli;  Xu, Kexin
收藏  |  浏览/下载：12/0  |  提交时间：2022/03/01
Machine learning and its applications in wireless communications 期刊论文
Lecture Notes in Electrical Engineering, 2019, 卷号: 463, 页码: 2429-2436
作者:  Lv, J.;  Na, Z.;  Liu, X.;  Deng, Z.
收藏  |  浏览/下载：28/0  |  提交时间：2019/12/02
Robustness Analysis and Robotic Application of Combined Function Activated RNN for Time-Varying Matrix Pseudo Inversion 期刊论文
IEEE Access, 2019, 卷号: Vol.7, 页码: 33434-33440
作者:  Zhiguo Tan;  Yueming Hu;  Lin Xiao;  Ke Chen
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/13
Real-Time Multilead Convolutional Neural Network for Myocardial Infarction Detection 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2018, 卷号: 22, 期号: 5
作者:  Liu, Wenhan;  Zhang, Mengxin;  Zhang, Yidan;  Liao, Yuan;  Huang, Qijun
收藏  |  浏览/下载：4/0  |  提交时间：2019/12/05
Establishment and analysis of performance prediction model for weight lifting athletes based on neural network 期刊论文
Agro Food Industry Hi-Tech, 2017, 卷号: 28, 期号: 3, 页码: 3637-3640
作者:  Peng, Xiaojing*
收藏  |  浏览/下载：2/0  |  提交时间：2019/12/28
Application research on foam glass kiln temperature control model and strategy 期刊论文
Information Technology Journal, 2013, 卷号: 12, 期号: 23, 页码: 7803-7808
作者:  Du, X.J.;  Shi, S.T.
收藏  |  浏览/下载：29/0  |  提交时间：2020/11/14
Development of PCNN research and its application in voice recognition 期刊论文
Journal of Convergence Information Technology, 2012, 卷号: 7, 期号: 20, 页码: 497-505
作者:  Nianyi, Wang;  Yide, Ma;  Kun, Zhan
收藏  |  浏览/下载：2/0  |  提交时间：2016/07/15
一种模糊推理过程神经网络及其应用研究 期刊论文
控制与决策, 2012
许少华; 庞跃武; 何新贵
收藏  |  浏览/下载：3/0  |  提交时间：2015/11/13
Double inverted pendulum control based on three-loop PID and improved BP neural network (EI CONFERENCE) 会议论文
2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China
Sang Y.; Fan Y.; Liu B.
收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25
To deal with the defects of BP neural networks used in balance control of inverted pendulum  such as longer train time and converging in partial minimum  this article reaLizes the control of double inverted pendulum with improved BP algorithm of artificial neural networks(ANN)  builds up a training model of test simulation and the BP network is 6-10-1 structure. Tansig function is used in hidden layer and PureLin function is used in output layer  LM is used in training algorithm. The training data is acquried by three-loop PID algorithm. The model is learned and trained with Matlab calculating software  and the simuLink simulation experiment results prove that improved BP algorithm for inverted pendulum control has higher precision  better astringency and lower calculation. This algorithm has wide appLication on nonLinear control and robust control field in particular. 2011 IEEE.  
Application of general regression neural network to vibration trend prediction of rotating machinery 会议论文
Advances in Neural Networks - ISNN 2004. International Symposium on Neural Networks. Proceedings (Lecture Notes in Comput. Sci. Vol.3174)), Advances in Neural Networks - ISNN 2004. International Symposium on Neural Networks. Proceedings, Dalian, China, INSPEC
Zhipeng Feng; Fulei Chu; Xigeng Song
收藏  |  浏览/下载：4/0

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