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在“
自然资源管理
”中,
命中:
6
条,耗时:0.0309821 秒
1.
Improving Forecasting Accuracy of Streamflow Time Series Using
Least
Squares
Support
Vector
Machine
Coupled with Data-Preprocessing Techniques
作者:
Aman Mohammad Kalteh
关键词:
Monthly streamflow forecasting
;
Least
squares
support
vector
machine
;
Singular spectrum analysis
;
Discrete wavelet analysis
刊名:Water Resources Management
出版者:Springer Netherlands
年:2016
2.
A hybrid LS-HE and LS-SVM model to predict time series of precipitable water vapor derived from GPS measurements
作者:
M. A. Sharifi
;
A. H. Souri
关键词:
GPS meteorology
;
Least
squares
harmonic estimation
;
Precipitable water vapor
;
Least
squares
support
vector
machine
刊名:Arabian Journal of Geosciences
出版者:Springer Berlin Heidelberg
年:2015
3.
Estimation of Failure Rate in Water Distribution Network Using Fuzzy Clustering and LS-SVM Methods
作者:
Mahmut Aydogdu
;
Mahmut Firat
关键词:
Water distribution network
;
Failure rate
;
LS
;
SVM
;
Fuzzy clustering
刊名:Water Resources Management
出版者:Springer Netherlands
年:2015
4.
Mid-term electricity market clearing price forecasting: A hybrid LSSVM and ARMAX approach
作者:
Xing Yan
;
Nurul A. Chowdhury
关键词:
Auto-regressive moving average with external input (ARMAX)
;
Deregulated electric market
;
Electricity market clearing price (MCP)
;
Electricity price forecasting
;
PJM
;
Least
squares
support
vector
machine
(LSSVM)
刊名:International Journal of Electrical Power and Energy Systems
年:2013
5.
Using
Support
Vector
Machine
to Predict Eco-environment Burden: A Case Study of Wuhan, Hubei Province, China
作者:
Xiang-Mei LI
;
Jing-Xuan ZHOU
;
Song-Hu YUAN
;
Xin-Ping ZHOU
;
Qiang FU
关键词:
Urban eco-environment
;
Total ecological footprint
;
Support
vector
machine
;
Partial
least
square
刊名:Biomedical and Environmental Sciences
年:2008
6.
Soil Water Simulation and Predication Using Stochastic Models Based on LS-SVM for Red Soil Region of China
作者:
Jianqiang Deng (12) djq1djq2@sina.com.cn Xiaomin Chen (1) xmchen@njau.edu.cn Zhenjie Du (1) Yong Zhang (1)
关键词:
Soil water models –
;
Chaotic analysis –
;
Artificial intelligence –
;
De
;
noising methods –
;
Wavelet
刊名:Water Resources Management
出版者:Springer Netherlands
年:2011
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