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在“
自然资源管理
”中,
命中:
6
条,耗时:小于0.01 秒
1.
Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions
作者:
Zhenfang He (1) (2) (3) Yaonan Zhang (1) Qingchun Guo (3) (4) Xueru Zhao (1) (5)
关键词:
Artificial neural network
;
Wavelet artificial neural network
;
Groundwater depth
;
Training
algorithm
s
;
Mallat decomposition
algorithm
;
Fractal dimension
刊名:Water Resources Management
年:2014
2.
Artificial Neural Network Modeling for Groundwater Level Forecasting in a River Island of Eastern India
作者:
Sheelabhadra Mohanty
;
Madan K. Jha
;
Ashwani Kumar and K. P. Sudheer
关键词:
Artificial neural network
;
Groundwater level prediction
;
Backpropagation GDX
algorithm
;
Lavenberg
;
Marquardt
algorithm
;
Bayesian
regularization
algorithm
;
River island
刊名:Water Resources Management
年:2010
3.
A sparse
Bayesian
framework for conditioning uncertain geologic models to nonlinear flow measurements
作者:
Lianlin Li
;
Behnam Jafarpour
关键词:
Sparse reconstruction
;
Bayesian
inversion
;
Model calibration
;
Subsurface characterization
;
History matching
刊名:Advances in Water Resources
年:2010
4.
Hybrid neural modeling for groundwater level prediction
作者:
Nikunja B. Dash
;
Sudhindra N. Panda
;
Renji Remesan and Narayan Sahoo
关键词:
Training
algorithm
s
;
Prediction
;
Genetic
algorithm
;
ANN
;
Winter
;
Groundwater
;
India
刊名:Neural Computing & Applications
年:2010
5.
Event-based Sediment Yield Modeling using Artificial Neural Network
作者:
Raveendra K. Rai and B. S. Mathur
关键词:
Automated
Bayesian
Regularization
;
ANN
;
Event
;
based
;
Runoff
;
Sediment yield
;
Sedimentograph
;
Small watersheds
刊名:Water Resources Management
出版者:Springer Netherlands
年:2008
6.
Neural Networks for Real Time Catchment Flow Modeling and Prediction
作者:
Muhammad Aqil
;
Ichiro Kita
;
Akira Yano and Soichi Nishiyama
关键词:
neural networks
;
feed forward
;
recurrent
;
catchment flow
刊名:Water Resources Management
出版者:Springer Netherlands
年:2007
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