搜索结果: 1-12 共查到“水文学 Artificial Neural Network”相关记录12条 . 查询时间(0.093 秒)
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...
An artificial neural network model for rainfall forecasting in Bangkok, Thailand
network model rainfall forecasting Thailand
2009/9/11
This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 ...
Water level forecasting through fuzzy logic and artificial neural network approaches
Water level forecasting fuzzy logic artificial neural network approaches
2009/5/13
In this study three data-driven water level forecasting models are presented and discussed. One is based on the artificial neural networks approach, while the other two are based on the Mamdani and t...
Multi-criteria validation of artificial neural network
rainfall-runoff multi-criteria artificial neural network
2009/4/28
In this study we propose a comprehensive multi-criteria validation test for rainfall-runoff modeling by artificial neural networks. This study applies 17 global statistics and 3 additional non-parame...
Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China
Artificial neural network multilayer perception
2009/3/17
While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This...
Comparison of three updating schemes using artificial neural network in flow forecasting
artificial neural network (ANN) updating flow forecasting backpropagation method
2009/3/5
Three updating schemes using artificial neural network (ANN) in flow forecasting are compared in terms of model efficiency. The first is the ANN model in the simulation mode plus an autoregressive (AR...