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浏览/检索结果: 共335条，第1-10条 帮助 限定条件 发表日期：2018    专题：山东大学    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 INTELLIGENT, FLEXIBLE PROTECTION DEVICE FOR STEEL ARCH IN CASE OF TUNNEL ROCKFALL COLLAPSE 专利 申请日期: 2018-11-29, 公开日期: 2018-11-29 作者:  Li SC(李术才);  Xu ZH(许振浩);  Wang XT(王欣桐);  Huang X(黄鑫);  Lin CJ(林春金) 收藏  |  浏览/下载：2/0  |  提交时间：2020/01/04 INTELLIGENT NUMERICALLY-CONTROLLED EXTRA-HIGH PRESSURE TRUE THREE-DIMENSIONAL NON-UNIFORM LOADING AND UNLOADING AND PRESSURE REGULATING MODEL TEST SYSTEM 专利 申请日期: 2018-11-01, 公开日期: 2018-11-01 作者:  Zhang QY(张强勇);  Li SC(李术才);  Liu CC(刘传成);  Wang HP(王汉鹏);  Wu D(吴冬) 收藏  |  浏览/下载：3/0  |  提交时间：2020/01/04 Exploring a novel ceramic (Ti,W)(3)SiC2 for interconnect of intermediate temperature solid oxide fuel cell 期刊论文 INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2018, 卷号: 43, 期号: 15, 页码: 7483-7491 作者:  Zheng, Lili;  Hua, Qingsong;  Li, Xichao;  Li, Meishuan;  Qian, Yuhai 收藏  |  浏览/下载：7/0  |  提交时间：2019/12/11 Ti3SiC2  W doping  Interconnect  Oxidation resistance  Area-specific  resistance   Deep Saliency With Channel-Wise Hierarchical Feature Responses for Traffic Sign Detection 期刊论文 IEEE Transactions on Intelligent Transportation Systems, 2018 作者:  Li C.;  Chen Z.;  Wu Q.M.J.;  Liu C. 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/11 channel-wise feature responses  Convolutional neural networks  Deep saliency  Feature extraction  hierarchical feature refinement  Image color analysis  Kernel  Saliency detection  Shape  squeeze-and-excitation-residual network  traffic sign detection.  Visualization   Risk-based Reserve Coordinative Unit Commitment for a Large-scale Wind-storage System 期刊论文 ELECTRIC POWER COMPONENTS AND SYSTEMS, 2018, 卷号: 46, 期号: 19-20, 页码: 2004-2020 作者:  Zhang, Yumin;  Han, Xueshan;  Xu, Bo;  Wang, Yong;  Wang, Mengxia 收藏  |  浏览/下载：8/0  |  提交时间：2019/12/11 conditional value-at-risk (CVaR)  column and constraint generation  algorithm (C&CG)  energy storage system (ESS)  reserve transfer (RT)  reserve coordinative unit commitment   Capacity Optimization Strategy of Energy Storage System for Power Grid with High Penetration of Photovoltaic Considering Limited Smoothing of Photovoltaic Ramping Power [考虑爬坡功率有限平抑的高渗透率光伏电网储能配置策略] 期刊论文 Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2018, 卷号: 42, 期号: 15, 页码: 53-61 and 185 作者:  Fu, Aihui;  Zhang, Feng;  Zhang, Li;  Liang, Jun;  Xu, Zhen 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/11 Capacity optimization  Cost of frequency regulation  Energy storage system (ESS)  High penetration  Photovoltaic power generation  Reserve   Unit commitment considering demand response behavior based on utility maximization 期刊论文 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings, 2018, 卷号: 2018-January, 页码: 1-6 作者:  Zhang, Yumin;  Han, Xueshan;  Xu, Bo;  Zhang, Li;  Sun, Donglei 收藏  |  浏览/下载：8/0  |  提交时间：2019/12/11 Decomposition coordination  Demand utility  Electricity market  Lagrangian relaxation  Real-time pricing  unit commitment   Designing interruptible load management scheme based on customer performance using mechanism design theory 期刊论文 INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2018, 卷号: 95, 页码: 476-489 作者:  Jian, Xuehui;  Zhang, Li;  Miao, Xiaofeng;  Zhang, Yumin;  Han, Xueshan 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/11 Customer baseline load  Customer performance  Demand response  Interruptible load management   Flexible Third Harmonic Voltage Control of Low Capacitance Cascaded H-Bridge STATCOM 期刊论文 IEEE TRANSACTIONS ON POWER ELECTRONICS, 2018, 卷号: 33, 期号: 3, 页码: 1884-1889 作者:  Ge, Xuefeng;  Gao, Feng 收藏  |  浏览/下载：7/0  |  提交时间：2019/12/11 Cascaded H-bridge (CHB) converter  STATCOM  third harmonic control  voltage ripple   A knowledge generation mechanism of machining process planning using cloud technology 期刊论文 Journal of Ambient Intelligence and Humanized Computing, 2018, 页码: 1-12 作者:  Yang Y.;  Hu T.;  Ye Y.;  Gao W.;  Zhang C. 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/11 Cloud technology  Intelligent process planning  Knowledge generation  Smart manufacturing