3.8 Proceedings Paper

River water modelling prediction using multi-linear regression, artificial neural network, and adaptive neuro-fuzzy inference system techniques

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.procs.2017.11.212

Keywords

Multilinear regression; artificial neural network; adaptive neuro fuzzy inference; dissolve oxygen

Ask authors/readers for more resources

In this study, multi linear regression (MLR), artificial neural network (ANN) and adaptive neuro fuzzy inference system(ANFIS) techniques were developed to predict the Dissolve oxygen concentration at down stream of Agra city, using monthly input data which are dissolve oxygen(DO), pH, biological oxygen demand(BOD) and water temperature (WT) at three different places viz, Agra upstream, middle stream and downstream. Initially, 11 input parameters for all the three locations were used except DO at the downstream, then, 7 input for middle and downstream except DO at the target location and finally the downstream location was considered in the analysis. The performance was evaluated using determination coefficient (DC) and root mean square error (RMSE), the result of DO showed that both the ANN and ANFIS can be applied in modelling DO concentration in Agra city, and also indicate that, ANN model is slightly better than ANFIS and also indicates a considerable superiority to MLR. (c) 2018 The Authors. Published by Elsevier B.V.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

3.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available