机构

• 长春光学精密机械与物... [4]
• 武汉岩土力学研究所 [3]
• 合肥物质科学研究院 [3]
• 成都山地灾害与环境研... [2]
• 地理科学与资源研究所 [1]
• 新疆生态与地理研究所 [1]
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采集方式

• OAI收割 [14]

内容类型

• 期刊论文 [8]
• 会议论文 [6]

发表日期

• 2024 [2]
• 2023 [2]
• 2020 [2]
• 2019 [2]
• 2016 [1]
• 2011 [2]
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浏览/检索结果: 共14条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择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作者升序作者降序 Velocity field and outflow discharge behavior in overtopping dam-break of an iron mine tailings dam: a model test 期刊论文  OAI收割 BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2024, 卷号: 83, 期号: 6, 页码: 14 作者:  Ma, Changkun;  Guo, Xiaogang;  Yang, Chunhe;  Zhang, Chao;  Ma, Lei   |  收藏  |  浏览/下载：1/0  |  提交时间：2025/06/27 Tailings dam  Dam-break flow  Velocity-field  Outflow discharge  Non-intrusive measurement  Model test   Large-scale field tunnel model experience and time-dependent floor heave induced by humidification 期刊论文  OAI收割 TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2024, 卷号: 145, 页码: 18 作者:  Chang, Zhou;  Yan, Changgen;  Xie, Wanye;  Lu, Zhifang;  Lan, Hengxing   |  收藏  |  浏览/下载：52/0  |  提交时间：2024/04/01 Loess tunnel  Field model test  Humidification  Floor heave  Time -dependency model   大气光学湍流模式研究:C_n~2廓线模式 期刊论文  OAI收割 物理学报, 2023, 卷号: 72 作者:  吴晓庆;  杨期科;  黄宏华;  青春;  胡晓丹   |  收藏  |  浏览/下载：19/0  |  提交时间：2023/11/10 atmospheric optical turbulence  modified CLEAR I night model  C_n~2 profile model of 5 field test site  suspicion of the H-V(5/7)model  大气光学湍流  修正的CLEAR I夜晚模式  5个实验点C_n~2廓线公式  H-V(5/7)模式的存疑   填埋场单井注气气体压力监测试验及预测模型 期刊论文  OAI收割 岩土力学, 2023, 卷号: 44, 期号: 1, 页码: 259 作者:  金佳旭;  朱磊;  刘磊;  陈亿军;  姚远   |  收藏  |  浏览/下载：2/0  |  提交时间：2025/06/27 waste  landfill  single well aeration  gas pressure  field test  prediction model  垃圾土  填埋场  单井注气  气体压力  现场试验  预测模型   Optimal Design Method to Improve the Magnetic Field Distribution of Multiple Square Coil Systems 期刊论文  OAI收割 IEEE ACCESS, 2020, 卷号: 8 作者:  Huang, Ya;  Jiang, Li;  Fu, Peng;  Huang, Zhengyi;  Xu, Xuesong   |  收藏  |  浏览/下载：55/0  |  提交时间：2020/11/30 Magnetic fields  Optimization  Mathematical model  Taylor series  Conductors  Design methodology  Power electronics  Error analysis  immunity test  magnetic field uniformity  multiple square coil systems   Displacement characteristic of landslides reinforced with flexible piles: field and physical model test 期刊论文  OAI收割 JOURNAL OF MOUNTAIN SCIENCE, 2020, 卷号: 17, 期号: 4, 页码: 787-800 作者:  Zhou Chang;  Hu Xin-li;  Zheng Wen-bo;  Xu Chu;  Wang Qiang   |  收藏  |  浏览/下载：23/0  |  提交时间：2020/11/12 Pile-soil interaction  Field trail  Physical model test  Soil arching  Displacement characteristics  Three Gorges Reservior   Studies of Deformation Properties of Collapsible Loess Foundation under Overburden Pressure with Large Thickness by Centrifugal Model Test 会议论文  OAI收割 Dalian, 2019-9-28～29 作者:  Jin,Songli;  Xing,Yichuan;  Yan,Jun;  Zhao,Weiquan;  Zhou,Shu   |  收藏  |  浏览/下载：87/0  |  提交时间：2020/03/10 loess  collapse under overburden pressure  centrifugal model test  field immersion test   Ecological Research on the Cracks Evolution Mechanism of Coal -Rock Mass in Deep Coal Mine 期刊论文  OAI收割 EKOLOJI, 2019, 卷号: 28, 期号: 107, 页码: 4537-4543 作者:  Liu, Bin;  Li, Jinlan;  Kang, Yongshui   |  收藏  |  浏览/下载：24/0  |  提交时间：2020/04/08 coal-rock mass  gas drainage  crack  evolution mechanism  AE technique  model test  stopping method  fracture zone shape  stress field  crack features of fracture zone   AC Loss Analysis of Central Solenoid Model Coil for China Fusion Engineering Test Reactor 期刊论文  OAI收割 IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2016, 卷号: 26, 期号: 7, 页码: 5900505 作者:  Zhou, Wei;  Fang, Jin;  Liu, Bo;  Fang, Xinyu;  Liu, Yanchao 收藏  |  浏览/下载：28/0  |  提交时间：2017/07/13 Ac Loss  Central Solenoid Model Coil (Csmc)  China Fusion Engineering Test Reactor (Cfetr)  Magnetic Field Distribution   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：43/0  |  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.