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北京大学 [11]
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厦门大学 [2]
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地理科学与资源研究所 [2]
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期刊论文 [21]
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浏览/检索结果:
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A Framework to Predict High-Resolution Spatiotemporal PM(2.5)Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China
期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 17, 页码: 33
作者:
Zhang, Guangyuan
;
Lu, Haiyue
;
Dong, Jin
;
Poslad, Stefan
;
Li, Runkui
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2021/03/16
PM2.5
AOD
XGBoost
prediction
deep learning
ConvLSTM
SARIMA
The Prediction of Finely-Grained Spatiotemporal Relative Human Population Density Distributions in China
期刊论文
IEEE ACCESS, 2020, 卷号: 8, 页码: 181534-181546
作者:
Zheng, Zhi
;
Zhang, Guangyuan
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2021/03/16
Prediction
human population density distribution
SARIMA
ConvLSTM
Tencent positioning data
deep learning
geographic spatiotemporal big data
Innovative education and training in high power laser plasmas (PowerLaPs) for plasma physics, high power laser matter interactions and high energy density physics: experimental diagnostics and simulations
期刊论文
HIGH POWER LASER SCIENCE AND ENGINEERING, 2020, 卷号: 8
-
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  |  
浏览/下载:8/0
  |  
提交时间:2020/10/26
laser plasma interactions
postgraduate education
Approaches to wind power curve modeling: A review and discussion
期刊论文
Renewable and Sustainable Energy Reviews, 2019, 卷号: Vol.116, 页码: 109422
作者:
Yun Wang
;
Qinghua Hu
;
Linhao Li
;
Aoife M. Foley
;
Dipti Srinivasan
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2019/11/21
Wind power curve modeling
Wind data classification
Wind data preprocessing
Error characteristics
Asymmetric distributions
Asymmetric loss function
Approaches to wind power curve modeling: A review and discussion
期刊论文
Renewable and Sustainable Energy Reviews, 2019, 卷号: Vol.116
作者:
Wang, Y.
;
Hu, Q.
;
Li, L.
;
Foley, A.M.
;
Srinivasan, D.
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/11/21
Asymmetric distributions
Asymmetric loss function
Error characteristics
Wind data classification
Wind data preprocessing
Wind power curve modeling
Quantum autoencoders via quantum adders with genetic algorithms
期刊论文
QUANTUM SCIENCE AND TECHNOLOGY, 2019, 卷号: 4
作者:
Lamata, L.[1]
;
Alvarez-Rodriguez, U.[2]
;
Martin-Guerrero, J. D.[3]
;
Sanz, M.[4]
;
Solano, E.[5]
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/04/22
quantum autoencoder
quantum adder
quantum machine learning
genetic algorithms
First demonstration of olfactory learning and long-term memory in honey bee queens
期刊论文
JOURNAL OF EXPERIMENTAL BIOLOGY, 2018, 卷号: 221, 期号: 14, 页码: -
作者:
Gong, Zhiwen
;
Tan, Ken
;
Nieh, James C.
;
Tan, K (reprint author), Chinese Acad Sci, Key Lab Trop Forest Ecol, Xishuangbanna Trop Bot Garden, Kunming 650223, Yunnan, Peoples R China.
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  |  
浏览/下载:31/0
  |  
提交时间:2018/09/05
Queen Learning
Worker Learning
Dna Methylation
Remote Memory
Deep Mutual Learning
会议论文
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018-01-01
作者:
Zhang, Ying
;
Xiang, Tao
;
Hospedales, Timothy M.
;
Lu, Huchuan
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  |  
浏览/下载:4/0
  |  
提交时间:2019/12/02
Deep Co-Space: Sample Mining Across Feature Transformation for Semi-Supervised Learning
期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2018, 卷号: Vol.28 No.10, 页码: 2667-2678
作者:
Wang, Xiao
;
Peng, Pai
;
Lin, Liang
;
Chen, Ziliang
;
Izquierdo, Ebroul
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2019/04/24
Cost-effective
model
visual
classification
deep
semi-supervised
learning
incremental
processing
visual
feature
learning
Joint problem solving and organizational learning capacity in new product innovation
期刊论文
R & D MANAGEMENT, 2018, 卷号: Vol.48 No.5, 页码: 519-533
作者:
Ning, LT
;
Li, J
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  |  
浏览/下载:4/0
  |  
提交时间:2019/12/26
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