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	The neural network model to solve the pre-consolidation stress 会议论文 OAI收割 Guangzhou, PEOPLES R CHINA, JUN 24-25, 2017 作者: An, Ran; Kong, Ling-wei; Li, Cheng-sheng \| 收藏 \| 浏览/下载：46/0 \| 提交时间：2018/06/05 pre-consolidation stress BP artificial neural network e-p curves MATLAB
	An improved hyperspectral classification algorithm based on back-propagation neural networks (EI CONFERENCE) 会议论文 OAI收割 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China 作者: Yu P.; Yu P. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 In this paper a new method is proposed to improve the classification performance of hyperspectral images by combining the principal component analysis (PCA) genetic algorithm (GA) and artificial neural networks (ANNs). First some characteristics of the hyperspectral remotely sensed data such as high correlation high redundancy etc. are investigated. Based on the above analysis we propose to use the principal component analysis to capture the main information existing in the hyperspectral images and reduce its dimensionality consequently. Next we use neural networks to classify the reduced hyperspectral data. Since the back-propagation neural network we used is easy to suffer from the local minimum problem we adopt a genetic algorithm to optimize the BP network's weights and the threshold. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.
	Research of neural network algorithm based on factor analysis and cluster analysis 期刊论文 OAI收割 NEURAL COMPUTING & APPLICATIONS, 2011, 卷号: 20, 期号: 2, 页码: 297-302 作者: Ding, Shifei; Jia, Weikuan; Su, Chunyang; Zhang, Liwen; Liu, Lili \| 收藏 \| 浏览/下载：14/0 \| 提交时间：2019/12/16 Artificial neural network (ANN) Factor analysis (FA) Cluster analysis (CA) FA-CA-BP network
	Double inverted pendulum control based on three-loop PID and improved BP neural network (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China 作者: Fan Y. 收藏 \| 浏览/下载：42/0 \| 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.
	Quantitative research on soil erosion based on BP artificial neural network - art. no. 67901e 会议论文 OAI收割 Remote Sensing and Gis Data Processing and Applications; and Innovative Multispectral Technology and Applications, Pts 1 and 2, Bellingham Dong, Tingting; Zhang, Zengxiang; Zuo, Lijun 收藏 \| 浏览/下载：158/0 \| 提交时间：2014/12/07 soil erosion BP artificial neural network multi-factor orthogonal regression analysis simulative experiment