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在“
自然资源管理
”中,
命中:
34
条,耗时:小于0.01 秒
1.
Pumping Optimization of Coastal Aquifers Assisted by Adaptive Metamodelling Methods and
Radial
Basis
Function
s
作者:
Vasileios Christelis
;
Aristotelis Mantoglou
关键词:
Coastal aquifers
;
Pumping optimization
;
Metamodels
;
Radial
basis
function
s
;
Global optimization
刊名:Water Resources Management
出版者:Springer Netherlands
年:2016
2.
A New Inverse Solution Assessment for the Recovery Test Using
Radial
Basis
Function
Collocation Method
作者:
A. Ufuk Sahin
关键词:
Aquifer
;
Heterogeneity
;
Parameter estimation
;
Radial
basis
function
s
;
Recovery test
刊名:Water Resources Management
出版者:Springer Netherlands
年:2016
3.
Estimation of river pollution source using the space-time
radial
basis
collocation method
作者:
Zi Lia
;
b
;
Xian-Zhong Maoa
;
maoxz@sz.tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author
;
Tak Sing Lic
;
Shiyan Zhangd
关键词:
Contaminant source identification
;
Global space-time collocation model
;
K-fold cross-validation
;
Inverse problem
;
Radial
basis
function
刊名:Advances in Water Resources
年:2016
4.
Application of Support Vector Regression for Mid- and Long-term Runoff Forecasting in “Yellow River Headwater” Region
作者:
Haibo Chua
;
Jiahua Weia
;
b
;
weijiahua@tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author
;
Tiejian Lia
;
b
;
Kun Jiac
关键词:
Support vector regression
;
Runoff forecasting
;
Yellow River Headwater
;
Radial
basis
function
neural network
刊名:Procedia Engineering
年:2016
5.
基于改进径向基函数的降雨量短期预测研究
作者:
董淑华
;
邢贞相
;
娄丹
;
张玉国
;
张涵
;
郭皓
关键词:
径向基函数
;
密度参数
;
K-均值
;
汛期降雨量
刊名:沈阳农业大学学报
年:2017
6.
RBFNN Versus Empirical Models for Lag Time Prediction in Tropical Humid Rivers
作者:
Mohammed Seyam
;
Faridah Othman
;
Ahmed El-Shafie
关键词:
Surface water
;
Lag time
;
Empirical models
;
Hydrology
;
Water resources
;
Tropical humid rivers
刊名:Water Resources Management
出版者:Springer Netherlands
年:2017
7.
Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget
作者:
Ioannis Tsoukalas
;
itsoukal@mail.ntua.gr" class="auth_mail" title="E-mail the corresponding author
;
Panagiotis Kossieris
;
Andreas Efstratiadis
;
Christos Makropoulos
关键词:
Global optimization
;
Meta-models
;
Radial
basis
function
s
;
Hydrological calibration
;
Multi-reservoir management
;
Synthetic data
刊名:Environmental Modelling & Software
年:2016
8.
ANN Based Sediment Prediction Model Utilizing Different Input Scenarios
作者:
Haitham Abdulmohsin Afan (1) Ahmed El-Shafie (1) Zaher Mundher Yaseen (1) Mohammed Majeed Hameed (1) Wan Hanna Melini Wan Mohtar (1) Aini Hussain (2)
关键词:
Sediment load
;
Feed forward neural network
;
Radial
basis
function
刊名:Water Resources Management
出版者:Springer Netherlands
年:2015
9.
Utilizing RBF-NN and ANFIS Methods for Multi-Lead ahead Prediction Model of Evaporation from Reservoir
作者:
Mohammed Falah Allawi
;
Ahmed El-Shafie
关键词:
Radial
basis
function
neural network (RBF
;
NN)
;
Adaptive neuro
;
fuzzy inference system (ANFIS)
;
Evaporation rate
;
Reservoir
刊名:Water Resources Management
出版者:Springer Netherlands
年:2016
10.
China’s natural gas production and consumption analysis based on the multicycle Hubbert model and rolling Grey model
作者:
Jianzhou Wanga
;
Haiyan Jiangb
;
jianghy2012@lzu.edu.cn" class="auth_mail" title="E-mail the corresponding author
;
Qingping Zhoub
;
Jie Wub
;
c
;
Shanshan Qinb
关键词:
GW
;
gigawatt
;
BP
;
British Petroleum
;
Mtoe
;
million tons oil equivalent
;
tcm
;
trillion cubic meters
;
bcm
;
billion cubic meters
;
URR
;
ultimate recoverable reserves
;
PCMACP
;
polynomial curve and moving average combination projection
;
FTW estimation
;
Fermat&ndash
;
Torricelli&ndash
;
Weber estimation
;
ARIMA
;
autoregressive integrated moving average
;
ANNs
;
artificial neural networks
;
FIS
;
fuzzy inference system
;
RBF
;
radial
basis
function
;
OLS
;
ordinary least square
;
ANFIS-SFA
;
adaptive network-based fuz
刊名:Renewable and Sustainable Energy Reviews
年:2016
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