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Artificial Neural Network Application on Estimation of Aquifer Transmissivity
Aquifer Parameter Feed Forward Back Propagation
2015/8/13
The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...
Application of an artificial neural network to estimate groundwater level fluctuation
groundwater level fluctuation estimating artificial neural network back propagation algorithms radial basis function MATLAB
2015/8/13
This paper examines and compares the capability of an artificial neural network (ANN) with five different backpropagation (BP) algorithms, namely Gradient descent with momentum (GDM), Gradient descent...
Estimation of Aquifer Transmissivity using Kriging, Artificial Neural Network, and Neuro-Fuzzy models
ransmissivity Kriging Artificial Neural Network ANFIS Neuro-Fuzzy interpolation groundwater
2015/8/11
In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult t...
Artificial Neural Network Application on Estimation of Aquifer Transmissivity
Aquifer Parameter Feed Forward Back Propagation Radial Basis Function Recurrent Artificial Neural Network Inverse Modeling Finite Element Method
2015/1/7
The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...
Application of an artificial neural network to estimate groundwater level fluctuation
groundwater level fluctuation estimating
2015/1/7
This paper examines and compares the capability of an artificial neural network (ANN) with five different backpropagation (BP) algorithms, namely Gradient descent with momentum (GDM), Gradient descent...
Estimation of Aquifer Transmissivity using Kriging, Artificial Neural Network, and Neuro-Fuzzy models
Neuro-Fuzzy interpolation groundwater
2015/1/6
In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult t...
MULTI-TEMPORAL LAND USE ANALYSIS OF AN EPHEMERAL RIVER AREA USING AN ARTIFICIAL NEURAL NETWORK APPROACH ON LANDSAT IMAGERY
Ephemeral River area Multi-temporal Land Use LANDSAT Imagery
2014/4/24
This paper proposes a change detection analysis method based on multitemporal LANDSAT satellite data, presenting a study
performed on the Lama San Giorgio (Bari, Italy) river basin area. Based o...
Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam
non-generalized neural network model multi-lead inflow
2011/3/15
Artificial neural networks (ANN) have been found efficient, particularly in problems where characteristics of the processes are stochastic and difficult to describe using explicit mathematical models....
Improved non-linear transfer function and neural network methods of flow routing for real-time forecasting
non-linear transfer function neural network methods flow routing real-time forecasting
2009/12/4
Data-based methods of flow forecasting are becoming increasingly popular due to their rapid development times, minimum information requirements, and ease of real-time implementation, with transfer fun...
Neural network rainfall-runoff forecasting based on continuous resampling
Neural network rainfall-runoff forecasting continuous resampling
2009/12/4
Most neural network hydrological modelling has used split-sample validation to ensure good out-of-sample generalisation and thus safeguard each potential solution against the danger of overfitting. Ho...
Data transformation for neural network models in water resources applications
Data transformation neural network models water resources applications
2009/12/4
A step that should be considered when developing artificial neural network (ANN) models for water resources applications is the selection of an appropriate transformation of the data. In general, the ...
A Neural Network Approach to Inversion of Snow Water Equivalent from Passive Microwave Measurements
Neural Network Approach Snow Water Equivalent Passive Microwave Measurements
2009/10/26
The inversion of snow water equivalent, SWE, from passive microwave remote
sensing measurements may be accomplished by using a neural network trained
with a dense media multiple scattering model. Br...
Fuzzy Clustering Neural Network as Flood Forecasting Model
Fuzzy Clustering Neural Network Flood Forecasting Model
2009/10/22
Flood forecasting is always a challenge in Taiwan, which has a subtropical climate
and high mountains. This paper develops a fuzzy clustering neural network
(FCNN), and implements this novel structu...
USE OF THE SPATIAL ANALYSIS NEURAL NETWORK (SANN) METHOD FOR REGIONAL GROUNDWATER CONTAMINATION DECISION-MAKING
Spatial Analysis Neural Network DECISION-MAKING GROUNDWATER CONTAMINATION
2009/10/19
Spatial Analysis Neural Network (SANN) is a specified neural network for conducting the spatial analysis of any type of variable. It provides a nonparametric mean estimator and also estimators of high...
INVERSE MODELING TO IDENTIFY NONPOINT SOURCE POLLUTION USING A NEURAL NETWORK, TAIHU LAKE WATERSHED, CHINA
NONPOINT SOURCE POLLUTION INVERSE MODELING NEURAL NETWORK TAIHU LAKE WATERSHED
2009/10/13
Various studies have been carried out for the evaluation of non-point source pollution using physically-based distributed hydrological and water quality models. A number of modeling interactions have ...