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Chinese Academy of Sciences Institutional Repositories Grid
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地理科学与资源研究所 [5]
成都山地灾害与环境研... [4]
自动化研究所 [2]
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地质与地球物理研究所 [1]
大连化学物理研究所 [1]
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OAI收割 [17]
内容类型
期刊论文 [14]
会议论文 [3]
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2024 [1]
2022 [2]
2021 [2]
2020 [1]
2019 [1]
2018 [6]
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A feasibility study on applying meta-heuristic optimization and Gaussian process regression for predicting the performance of pantograph-catenary system
期刊论文
OAI收割
ACTA MECHANICA SINICA, 2024, 卷号: 40, 期号: 1, 页码: 12
作者:
Zhang MH(张莫晗)
;
Yin B(银波)
;
Sun ZX(孙振旭)
;
Bai, Ye
;
Yang GW(杨国伟)
  |  
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2024/02/26
Pantograph-catenary system
Gaussian process regression
Surrogate model
Physical-based model
Comparing Different Methods for Wheat LAI Inversion Based on Hyperspectral Data
期刊论文
OAI收割
AGRICULTURE-BASEL, 2022, 卷号: 12, 期号: 9, 页码: 14
作者:
Ma, Junwei
;
Wang, Lijuan
;
Chen, Pengfei
  |  
收藏
  |  
浏览/下载:40/0
  |  
提交时间:2022/11/09
leaf area index
gaussian process regression
artificial neural networks
partial least squares regression
hyperspectral
wheat
Comparing Different Methods for Wheat LAI Inversion Based on Hyperspectral Data
期刊论文
OAI收割
AGRICULTURE-BASEL, 2022, 卷号: 12, 期号: 9, 页码: 14
作者:
Ma, Junwei
;
Wang, Lijuan
;
Chen, Pengfei
  |  
收藏
  |  
浏览/下载:32/0
  |  
提交时间:2022/11/09
leaf area index
gaussian process regression
artificial neural networks
partial least squares regression
hyperspectral
wheat
Improving terrestrial evapotranspiration estimation across China during 2000-2018 with machine learning methods
期刊论文
OAI收割
JOURNAL OF HYDROLOGY, 2021, 卷号: 600, 页码: 18
作者:
Yin, Lichang
;
Tao, Fulu
;
Chen, Yi
;
Liu, Fengshan
;
Hu, Jian
  |  
收藏
  |  
浏览/下载:66/0
  |  
提交时间:2021/11/05
Evapotranspiration
Machine learning
process-based ET
ET integration
China
Gaussian process regression
Improving terrestrial evapotranspiration estimation across China during 2000-2018 with machine learning methods
期刊论文
OAI收割
JOURNAL OF HYDROLOGY, 2021, 卷号: 600, 页码: 18
作者:
Yin, Lichang
;
Tao, Fulu
;
Chen, Yi
;
Liu, Fengshan
;
Hu, Jian
  |  
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2021/11/05
Evapotranspiration
Machine learning
process-based ET
ET integration
China
Gaussian process regression
Determination of influential parameters for prediction of total sediment loads in mountain rivers using kernel-based approaches
期刊论文
OAI收割
JOURNAL OF MOUNTAIN SCIENCE, 2020, 卷号: 17, 期号: 2, 页码: 480-491
作者:
Roushangar, Kiyoumars
;
Shahnazi, Saman
  |  
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2020/11/11
Total sediment loads
Support vector machine
Gaussian process regression
Kernel extreme learning machine
Mountain Rivers
An AUV Adaptive Sampling Path Planning Method Based On Online Model Prediction
会议论文
OAI收割
Daejeon, KOREA, September 18-20, 2019
作者:
Yan SX(阎述学)
;
Li YP(李一平)
;
Feng XS(封锡盛)
;
Li S(李硕)
;
Tang YG(唐元贵)
  |  
收藏
  |  
浏览/下载:59/0
  |  
提交时间:2020/01/11
adaptive sampling
Gaussian Process Regression
AUV
online path planning
hot spot area observation
A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease
期刊论文
OAI收割
GIGASCIENCE, 2018, 卷号: 7, 期号: 7, 页码: 10
作者:
Zhang, Hongjiu
;
Zhu, Fan
;
Dodge, Hiroko H.
;
Higgins, Gerald A.
;
Omenn, Gilbert S.
  |  
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2020/02/14
Gaussian Process Regression
Alzheimer's Disease
Patient similarity network
Kernel method
Machine learning
Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance
期刊论文
OAI收割
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2018, 卷号: 7, 期号: 7, 页码: 14
作者:
Yin, Gaofei
;
Li, Ainong
;
Wu, Chaoyang
;
Wang, Jiyan
;
Xie, Qiaoyun
  |  
收藏
  |  
浏览/下载:59/0
  |  
提交时间:2019/05/23
aboveground biomass (AGB)
uncertainty
consistent adjustment of the climatology to actual observations (CACAO)
Gaussian process regression (GPR)
Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance
期刊论文
OAI收割
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2018, 卷号: 7, 期号: 7, 页码: 14
作者:
Yin, Gaofei
;
Li, Ainong
;
Wu, Chaoyang
;
Wang, Jiyan
;
Xie, Qiaoyun
  |  
收藏
  |  
浏览/下载:77/0
  |  
提交时间:2018/10/10
aboveground biomass (AGB)
uncertainty
consistent adjustment of the climatology to actual observations (CACAO)
Gaussian process regression (GPR)