中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究所 [1]
新疆生态与地理研究所 [1]
寒区旱区环境与工程研... [1]
生态环境研究中心 [1]
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OAI收割 [3]
iSwitch采集 [1]
内容类型
期刊论文 [2]
SCI/SSCI论文 [1]
会议论文 [1]
发表日期
2017 [1]
2010 [2]
2009 [1]
学科主题
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Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland
期刊论文
iSwitch采集
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 卷号: 72, 页码: 828-848
作者:
Deo, Ravinesh C.
;
Sahin, Mehmet
收藏
  |  
浏览/下载:40/0
  |  
提交时间:2019/10/09
Satellite-based solar model
Neural network
Multi-linear regression
ARIMA model
Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China
期刊论文
OAI收割
CHINESE GEOGRAPHICAL SCIENCE, 2010, 卷号: 20, 期号: 2, 页码: 152-158
作者:
Jiang Yan
;
Liu Changming
;
Zheng Hongxing
;
Li Xuyong
;
Wu Xianing
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2015/07/30
river runoff
runoff forecast
nonlinear mixed regression model
linear multi-regression model
linear mixed regression model
BP neural network
Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China
SCI/SSCI论文
OAI收割
2010
Jiang Y.
;
Liu C. M.
;
Zheng H. X.
;
Li X. Y.
;
Wu X. N.
收藏
  |  
浏览/下载:30/0
  |  
提交时间:2012/06/08
river runoff
runoff forecast
nonlinear mixed regression model
linear
multi-regression model
linear mixed regression model
BP neural network
bone
Cultivated land change and its human driving forces based on RS and GIS in Fuzhou, China
会议论文
OAI收割
2009 International Conference on Environmental Science and Information Application Technology, Wuhan, China, 2009
Dewen
;
Wu1
;
2
;
Jinchuan
;
Huang3
;
Xiaolei
;
Zhang1
;
Hanying
;
Mao3
收藏
  |  
浏览/下载:30/0
  |  
提交时间:2011/08/23
Economics - Environmental engineering - Forestry - Human engineering - Land use - Linear regression - Rapid solidification - Remote sensing - China - Cultivated land change - Human driving forces - Multi-linear regression model - RS and GIS