Relating groundwater levels with meteorological parameters using ANN technique

[1]  Richard Taylor.  Interpretation of the Correlation Coefficient: A Basic Review , 1990 .

[2]  Witold F. Krajewski,et al.  Rainfall forecasting in space and time using a neural network , 1992 .

[3]  Mu-Lan Zhu,et al.  Application of Neural Networks to Runoff Prediction , 1994 .

[4]  Daniel Svozil,et al.  Introduction to multi-layer feed-forward neural networks , 1997 .

[5]  Holger R. Maier,et al.  Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications , 2000, Environ. Model. Softw..

[6]  Christian W. Dawson,et al.  Hydrological modelling using artificial neural networks , 2001 .

[7]  P. Koundouri,et al.  Groundwater management: an overview of hydro-geology, economic values and principles of management , 2002 .

[8]  Y. Kuo,et al.  Xanthones and benzophenones from the stems of Garcinia multiflora. , 2003, Journal of natural products.

[9]  Ferenc Szidarovszky,et al.  Artificial Neural Network Approach for Predicting Transient Water Levels in a Multilayered Groundwater System under Variable State, Pumping, and Climate Conditions , 2003 .

[10]  Tony R. Martinez,et al.  The general inefficiency of batch training for gradient descent learning , 2003, Neural Networks.

[11]  Andres Winston C. Oreta,et al.  Simulating size effect on shear strength of RC beams without stirrups using neural networks , 2004 .

[12]  Paulin Coulibaly,et al.  Groundwater level forecasting using artificial neural networks , 2005 .

[13]  S. Lallahem,et al.  On the use of neural networks to evaluate groundwater levels in fractured media , 2005 .

[14]  N. K. Goel,et al.  Takagi–Sugeno fuzzy inference system for modeling stage–discharge relationship , 2006 .

[15]  Venkatesh Uddameri,et al.  Using statistical and artificial neural network models to forecast potentiometric levels at a deep well in South Texas , 2007 .

[16]  Majid Kholghi,et al.  Comparison of Groundwater Level Estimation Using Neuro-fuzzy and Ordinary Kriging , 2009 .

[17]  P. Döll,et al.  Global-scale modeling of groundwater recharge , 2008 .

[18]  A. MacDonald,et al.  Groundwater research issues in Africa , 2008 .

[19]  Kourosh Mohammadi,et al.  Groundwater Table Estimation Using MODFLOW and Artificial Neural Networks , 2009 .

[20]  R. R. Sethi,et al.  Prediction of water table depth in a hard rock basin by using artificial neural network , 2010 .

[21]  A. K. Lohani,et al.  Development of Flood Forecasting System Using Statistical and ANN Techniques in the Downstream Catchment of Mahanadi Basin, India , 2010 .

[22]  Ozgur Solmaz,et al.  Prediction of Hourly Solar Radiation in Six Provinces in Turkey by Artificial Neural Networks , 2012 .

[23]  Klaus-Robert Müller,et al.  Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.

[24]  A. K. Lohani,et al.  Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques , 2012 .

[25]  Groundwater level simulation using artificial neural network: a case study from Aghili plain, urban area of Gotvand, south-west Iran , 2013 .

[26]  N. K. Goel,et al.  Improving real time flood forecasting using fuzzy inference system , 2014 .

[27]  Ramli Nazir,et al.  Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN , 2014 .

[28]  Z. Alipour,et al.  Comparison of three methods of ANN , ANFIS and Time Series Models to predict ground water level: (Case study: North Mahyar plain) , 2014 .

[29]  A. M. Muhammad,et al.  Evaluation of local groundwater vulnerability based on DRASTIC index method in Lahore, Pakistan , 2015 .

[30]  Jian-Hao Hong,et al.  Prediction of contraction scour using ANN and GA , 2016 .

[31]  Y. Srinivas,et al.  Wavelet based analysis on rainfall and water table depth forecasting using Neural Networks in Kanyakumari district, Tamil Nadu, India , 2017 .

[32]  Rafael F. S. Caldeirinha,et al.  Modeling and inferring the attenuation induced by vegetation barriers at 2G/3G/4G cellular bands using Artificial Neural Networks , 2017 .

[33]  S. Siddique,et al.  Prediction of mechanical properties of rubberised concrete exposed to elevated temperature using ANN , 2019 .

[34]  S. Matthai,et al.  Application of neural networks and fuzzy systems for the intelligent prediction of CO2-induced strength alteration of coal , 2019, Measurement.

[35]  Amir Hossein Zaji,et al.  Application of optimized Artificial and Radial Basis neural networks by using modified Genetic Algorithm on discharge coefficient prediction of modified labyrinth side weir with two and four cycles , 2020 .

[36]  K. I. Molla,et al.  Climatic data analysis for groundwater level simulation in drought prone Barind Tract, Bangladesh: Modelling approach using artificial neural network , 2020 .