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浏览/检索结果: 共5条，第1-5条 帮助 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 Automatic Recognition of Sucker-Rod Pumping System Working Conditions Using Few-Shot Indicator Diagram Based on Meta-learning 会议论文 Chicago, May 26-28, 2021 作者:  He YP(贺云鹏);  Zang CZ(臧传治);  Zeng P(曾鹏);  Wang MX(王明新);  Wan GX(万广喜) 收藏  |  浏览/下载：31/0  |  提交时间：2021/08/21 Few-shot learning  Indicator diagram  Meta-learning  Sucker-rod pumping system  Working condition recognition   Automatic recognition of sucker-rod pumping system working conditions using dynamometer cards with transfer learning and svm 期刊论文 SENSORS, 2020, 卷号: 20, 期号: 19, 页码: 1-15 作者:  Cheng HB(程海波);  Yu HB(于海斌);  Zeng P(曾鹏);  Osipov, Evgeny;  Li SC(李世超) 收藏  |  浏览/下载：25/0  |  提交时间：2020/10/18 working condition recognition  sucker-rod pumping system  dynamometer card  convolutional neural network  transfer learning  support vector machine   On-Line Froth Depth Estimation for Sulphur Flotation Process With Multiple Working Conditions 期刊论文 IEEE ACCESS, 2019, 卷号: 7, 页码: 124774-124784 作者:  He, Mingfang;  Sun, Bei* 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/28 Deep froth features  non-contact estimation  working condition recognition   Working condition recognition based on an improved NGLDM and interval data-based classifier for the antimony roughing process 期刊论文 Minerals Engineering, 2016, 卷号: 86, 页码: 1-9 作者:  Peng, Xia;  Peng, Tao*;  Zhao, Lin;  Song, Yanpo;  Gui, Weihua 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/03 Working condition recognition  Improved NGLDM  Composite texture  Interval data  SVM  Antimony roughing   Recognition of flotation working conditions through froth image statistical modeling for performance monitoring 期刊论文 Minerals Engineering, 2016, 卷号: 86, 页码: 116-129 作者:  Zhang, Jin;  Tang, Zhaohui;  Liu, Jinping*;  Tan, Zhen;  Xu, Pengfei 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/03 Froth flotation process  Working condition recognition  Gabor wavelet transformation  t location-scale distribution  Gamma distribution