中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共8条，第1-8条

帮助

条数/页：排序方式：
	Estimating Gridded Monthly Baseflow From 1981 to 2020 for the Contiguous US Using Long Short-Term Memory (LSTM) Networks 期刊论文 OAI收割 WATER RESOURCES RESEARCH, 2022, 卷号: 58, 期号: 8, 页码: 19 作者: Xie, Jiaxin; Liu, Xiaomang; Tian, Wei; Wang, Kaiwen; Bai, Peng \| 收藏 \| 浏览/下载：30/0 \| 提交时间：2022/11/09 baseflow time series simulation deep learning long short-term memory
	Estimating Gridded Monthly Baseflow From 1981 to 2020 for the Contiguous US Using Long Short-Term Memory (LSTM) Networks 期刊论文 OAI收割 WATER RESOURCES RESEARCH, 2022, 卷号: 58, 期号: 8, 页码: 19 作者: Xie, Jiaxin; Liu, Xiaomang; Tian, Wei; Wang, Kaiwen; Bai, Peng \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2022/11/09 baseflow time series simulation deep learning long short-term memory
	Predicting the Epidemics Trend of COVID-19 Using Epidemiological-Based Generative Adversarial Networks 期刊论文 OAI收割 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2022, 卷号: 16, 期号: 2, 页码: 276-288 作者: Wang, Haishuai; Tao, Guangyu; Ma, Jiali; Jia, Shangru; Chi, Lianhua \| 收藏 \| 浏览/下载：32/0 \| 提交时间：2022/07/25 COVID-19 Predictive models Mathematical models Data models Pandemics Market research Biological system modeling COVID-19 generative adversarial networks time series prediction SIR simulation
	Wavelet Neural Modeling for Hydrologic Time Series Forecasting with Uncertainty Evaluation SCI/SSCI论文 OAI收割 2015 作者: Sang Y. F.; Wang, Z. G.; Liu, C. M. 收藏 \| 浏览/下载：35/0 \| 提交时间：2015/12/09 Hydrologic time series analysis Probabilistic forecasting Uncertainty evaluation Wavelet neural model Monte-Carlo simulation monthly rainfall practical guide prediction networks precipitation decomposition sensitivity calibration level
	An online outlier detection method based on wavelet technique and robust RBF network 期刊论文 OAI收割 Transactions of the Institute of Measurement and Control, 2013, 卷号: 35, 期号: 8, 页码: 1046-1057 作者: Su WX(苏卫星); Zhu YL(朱云龙); Liu F(刘芳); Hu KY(胡琨元) 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/12/27 Computer simulation Control systems Hidden Markov models Process control Radial basis function networks Time series
	Contact-impact analys with clearance hinge in flexible multi-body system (EI CONFERENCE) 会议论文 OAI收割 2nd Annual Conference on Electrical and Control Engineering, ICECE 2011, September 16, 2011 - September 18, 2011, Yichang, China Ge M.; Jia H.; Liu B. 收藏 \| 浏览/下载：51/0 \| 提交时间：2013/03/25 Hinge in mechanical systems exist small clearance and contact deformation After consideration of flexible components cause the system to the wear and tear impact force reduced at the clearance noise contact time increased vibration contact-impact areas expand and clearance also caused disturbance of the rod angular velocity of the linkage. 2011 IEEE. reliability reduce or even failure[1]. Therefore the hinge clearance and the impact of flexible components in kinetic models should be considered. In this paper a nonlinear spring-damper hinge clearance model is considered to establish mechanical system structure of dynamic equations[46] through a four-bar linkage hinge with multi-clearance rotation of ADAMS dynamic simulation for dynamics simulation study. Simulation results show that hinge clearance and link flexible in Four-link mechanism dynamics have a great impact on performance: connection with the clearance lead to pin holes to produce a series of collisions and a larger initial impact force
	Flow Past Two Freely Rotatable Triangular Cylinders in Tandem Arrangement 期刊论文 OAI收割 Journal of Fluids Engineering-Transactions of The Asme, 2011, 卷号: 133, 期号: 8, 页码: 81202 作者: Wang SZ(王士召); Zhu LD; Zhang X(张星); He GW(何国威) 收藏 \| 浏览/下载：146/0 \| 提交时间：2012/04/01 Falling Paper Unsteady Aerodynamics Numerical-Simulation Circular-Cylinders Reynolds-Number Time-Series Autorotation Plates Cards Behavior
	Arc fault signatures detection on aircraft wiring system (EI CONFERENCE) 会议论文 OAI收割 6th World Congress on Intelligent Control and Automation, WCICA 2006, June 21, 2006 - June 23, 2006, Dalian, China Hongkun Z.; Tao C.; Wenjun L. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 In this paper an arc fault detection method Is proposed based on characteristics of the fault current of an electric arc. A localized signal processing method Is developed using wavelet analysis to decompose the differential current signal Into a series of wavelet components each of which Is a time-domain signal that covers a specific frequency band. Thus more distinctive signal features that represent arc faults and other fault transient phenomena are extracted. As a result by quantifying the extracted features an arc faults are distinguished from phenomena similar to arc and other fault transients using the differences In the quantified features. Simulation studies have demonstrated that the proposed method Is reliable and simple. 2006 IEEE.