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地理科学与资源研究所 [2]
上海财经大学 [2]
兰州理工大学 [1]
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北京航空航天大学 [1]
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期刊论文 [9]
会议论文 [2]
发表日期
2019 [11]
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A modular and parallelized watershed modeling framework
期刊论文
ENVIRONMENTAL MODELLING & SOFTWARE, 2019, 卷号: 122, 页码: 16
作者:
Zhu, Liang-Jun
;
Liu, Junzhi
;
Qin, Cheng-Zhi
;
Zhu, A-Xing
收藏
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浏览/下载:6/0
  |  
提交时间:2020/05/19
Watershed modeling framework
Modular
Parallelization
Watershed process simulation
SEIMS
Multi-source coordination and scheduling strategy of new energy with high proportion of wind power, photovoltaic and photothermal
会议论文
Yichang, China, September 6, 2019 - September 9, 2019
作者:
Wei, Xiong
;
Xiaoying, Zhang
;
Kun, Wang
;
Wei, Chen
;
Xiaolan, Wang
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  |  
浏览/下载:13/0
  |  
提交时间:2020/11/15
Electric power system economics
Electric power transmission networks
Energy efficiency
Fossil fuel power plants
Integer programming
Linear programming
MATLAB
Photovoltaic cells
Scheduling
Smart power grids
Solar power generation
Wind power
Coordinated scheduling
Grid efficiency
New energies
Objective to optimize
Photovoltaic
An Instruction Set Architecture for Machine Learning
期刊论文
ACM TRANSACTIONS ON COMPUTER SYSTEMS, 2019, 卷号: 36, 期号: 3, 页码: 35
作者:
Chen, Yunji
;
Lan, Huiying
;
Du, Zidong
;
Liu, Shaoli
;
Tao, Jinhua
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  |  
浏览/下载:19/0
  |  
提交时间:2020/12/10
An Efficient Numerical Method for the Symmetric Positive Definite Second-Order Cone Linear Complementarity Problem
期刊论文
JOURNAL OF SCIENTIFIC COMPUTING, 2019, 卷号: 79, 期号: 3, 页码: 1608-1629
作者:
Wang, Xiang
;
Li, Xing
;
Zhang, Lei-Hong
;
Li, Ren-Cang
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  |  
浏览/下载:19/0
  |  
提交时间:2019/08/22
Second-order cone
Linear complementarity problem
SOCLCP
Globally uniquely solvable property
GUS
Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models
期刊论文
ENVIRONMENTAL MODELLING & SOFTWARE, 2019, 卷号: 114, 页码: 112-128
作者:
Zaherpour, Jamal
;
Mount, Nick
;
Gosling, Simon N.
;
Dankers, Rutger
;
Eisner, Stephanie
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  |  
浏览/下载:34/0
  |  
提交时间:2019/05/22
Machine learning
Model weighting
Gene expression programming
Global hydrological models
Optimisation
Scenario-based heuristic to two-stage stochastic program for the parallel machine ScheLoc problem
期刊论文
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2019, 卷号: 57, 期号: 6, 页码: 1706-1723
作者:
Liu, Ming
;
Liu, Xin
;
Zhang, E.
;
Chu, Feng
;
Chu, Chengbin
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浏览/下载:20/0
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提交时间:2019/08/22
ScheLoc problem
uncertain processing times
two-stage stochastic integer program
scenario-based heuristic
Multiple phase tabu search for bipartite boolean quadratic programming with partitioned variables
期刊论文
Computers and Operations Research, 2019, 卷号: 102, 页码: 141-149
作者:
Shang, Zhen
;
Zhao, Songzheng
;
Hao, Jin-Kao
;
Yang, Xue
;
Ma, Fuda
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浏览/下载:17/0
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提交时间:2019/11/19
Binary quadratic programming
Experimental assessment
Hybrid Meta-heuristic
Lower bounds
Quadratic programming problems
Search phasis
Tabu search algorithms
Very Large Scale Neighborhoods
Formation optimization of large-scale UCAV based on bi-level programming model
期刊论文
Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2019, 卷号: Vol.51 No.3, 页码: 15-22
作者:
Zong, Q.
;
Qin, X.
;
Zhang, B.
;
Tian, B.
;
Zhao, X.
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  |  
浏览/下载:5/0
  |  
提交时间:2019/11/21
Bi-level programming model
DPSO-SA
Formation optimization
Improved simulated annealing
Large-scale UCAV
Long-term complementary operation of a large-scale hydro-photovoltaic hybrid power plant using explicit stochastic optimization
期刊论文
APPLIED ENERGY, 2019, 卷号: 238
作者:
Li, He
;
Liu, Pan
;
Guo, Shenglian
;
Ming, Bo
;
Cheng, Lei
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浏览/下载:1/0
  |  
提交时间:2019/12/05
Hydro-PV hybrid power plant
Uncertainty
Streamflow
PV output
Stochastic dynamic programming
An Efficient Insertion Operator in Dynamic Ridesharing Services
会议论文
2019 IEEE 35TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2019), 2019-01-01
作者:
Xu, Yi
;
Tong, Yongxin
;
Shi, Yexuan
;
Tao, Qian
;
Xu, Ke
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2019/12/30
Efficiency
Large dataset
Traffic control
Travel time
Index structure
Insertion
Intelligent transportation
Large-scale datasets
Origin-destination pairs
Ride-sharing
Time complexity
Time efficiencies
Dynamic programming
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