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  • 标题:Performance of ANNs for Prediction of TDS of Godavari River, India
  • 本地全文:下载
  • 作者:Prajot D. Tarke ; Purushottam R. Sarda ; ParagA. Sadgir
  • 期刊名称:International Journal of Engineering Research
  • 印刷版ISSN:2319-6890
  • 出版年度:2016
  • 卷号:5
  • 期号:2
  • 页码:115-118
  • DOI:10.17950/ijer/v5s2/209
  • 出版社:IJER
  • 摘要:This research investigates the potential of the Artificial Neural Networks (ANNs) on simulating interrelation between water quality parameters for river water quality management. It aims to model Total Dissolved Solids (TDS) values at Pategaon station on Godavari River by application of ANNs. Monthly data from 2001 to 2012 of various water quality parameters is collected. Correlation analysis has been carried out for selecting the most suitable input parameters for the model. The ANN modelling strategy is implemented by Neural Network Toolbox in MATLAB. Several ANN architectures and training possibilities are assessed and the best AN N architecture is selected for finding the best prediction model of TDS. Comparisons between the measured and predicted values show that the ANNs model could be successfully applied and provide high accuracy and reliability for predicting water quality parameters. Coefficient of correlation between observed and predicted TDS values calculated using ANN s and analytical method is found to be similar (R=0.98293), which shows the effectiveness of ANNs in predicting the missing water quality parameters.
  • 关键词:ANN; Correlation; Regression; TDS; Water ; Quality Prediction
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