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浏览/检索结果: 共6条，第1-6条 帮助 限定条件 专题：西安理工大学    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Deep-learning-based Wind Speed Forecasting Considering Spatial-temporal Correlations with Adjacent Wind Turbines 期刊论文 2019, 页码: 623-632 作者:  Shi, Xiaoyu;  Huang, Shengzhi;  Huang, Qiang;  Lei, Xuewen;  Li, Jiangfeng 收藏  |  浏览/下载：10/0  |  提交时间：2019/12/20 Wind speed prediction  spatial-temporal correlation  wavelet coherence transformation analysis  long short term memory   Line loss rate prediction method based on deep learning with long short term memory 会议论文 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019, 2 Huzhu Road, Xi'an, China, 2019-06-19 作者:  Jia, Hao;  Deng, Yaping;  Qiu, Xiaodong;  Tong, Xiangqian;  Li, Pengcheng 收藏  |  浏览/下载：7/0  |  提交时间：2019/12/20 Research Into the LSTM Neural Network-Based Crystal Growth Process Model Identification 期刊论文 2019, 卷号: 32, 页码: 220-225 作者:  Zhang, Jing;  Tang, Qinwei;  Liu, Ding 收藏  |  浏览/下载：9/0  |  提交时间：2019/12/20 Thermal field model  long short-term memory (LSTM) neural network  support vector machine (SVM)  model order   Predicting Remaining Useful Life of Industrial hquipment Based on Multivariable Monitoring Data Analysis 会议论文 2018 CHINESE AUTOMATION CONGRESS (CAC), 2018-01-01 作者:  Li, Xin;  Xie, Guo;  Liu, Han;  Wang, Wenqing 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/20 remaining useful life prediction  long short-term memory network  industrial equipment  multivariable   A Deep Learning Method based on Long Short Term Memory and Sliding Time Window for Type Recognition and Time Location of Power Quality Disturbance 会议论文 2018 CHINESE AUTOMATION CONGRESS (CAC), 2018-01-01 作者:  Deng, Yaping;  Jia, Hao;  Li, Pengcheng;  Tong, Xiangqian;  Li, Feng 收藏  |  浏览/下载：5/0  |  提交时间：2019/12/20 deep learning  sliding time window  power quality disturbance  type recognition  time location   Hourly Day-Ahead Wind Power Prediction Using the Hybrid Model of Variational Model Decomposition and Long Short-Term Memory 期刊论文 2018, 卷号: 11 作者:  Shi, Xiaoyu;  Lei, Xuewen;  Huang, Qiang;  Huang, Shengzhi;  Ren, Kun 收藏  |  浏览/下载：7/0  |  提交时间：2019/12/20 wind power prediction  long short term memory  variational model decomposition (VMD)  direct model  recursive model