MODELLING BOD CONCENTRATION BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM

Authors

  • Jayesh S. Patel Civil Engineering Department,DJMIT,Mogar, Gujarat, India

Keywords:

Adaptive Neuro-Fuzzy Inference System, BioChemical Oxygen Demand(BOD)

Abstract

BOD is a parameter frequently used to evaluate
the water quality on different rivers. The aim of the present
study is to investigate applicability of artificial intelligence
techniques such as ANFIS (Adapti ve Neuro-Fuzzy Inference
System) in water quality BOD prediction for the case study,
Mahi river at Khanpur in Thasara Taluka of Kheda District
in Gujarat State, India. The proposed technique combines the
learning ability of neural network with the transparent
linguistic representation of fuzzy system. ANFIS models with
various input structures and membership functions are
constructed, trained and tested to evaluate efficiency of the
models. Statistical indices such as Root Mean Square Error
(RMSE), Correlation Coefficient (R), Coefficient of
Determination (R2
) and Discrepancy Ratio (D) are used to
evaluate performance of the ANFIS models in forecasting
BOD. ANFIS model is used for the estimation of BOD
concentration.

Published

2022-04-27

How to Cite

Jayesh S. Patel. (2022). MODELLING BOD CONCENTRATION BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM. International Journal of Advance Engineering and Research Development (IJAERD), 2(13), -. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/5729