TY - GEN
T1 - Applications of Artificial Neural Network in the Prediction of Water Quality Index
AU - Murivhami, Tshedza
AU - Tartibu, Lagouge Kwanda
AU - Olayode, Isaac Oyeyemi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Artificial intelligence can significantly lower water supply and sanitation systems and assist to ensure compliance with drinking water and wastewater treatment standards. As a result, there has been extensive research on modelling and forecasting water quality to reduce water pollution. The proposed system's uniqueness is offered to create an effective monitoring operation. This paper uses Artificial Neural Network (ANN) for the prediction of water quality index (WQI). Seven important water quality parameters were considered, namely the Dissolved Oxygen (DO), the pH, the conductivity, the Biochemical Oxygen Demand (BOD), the nitrate, faecal coliform, and the total coliform. In the study, seven parameters were used for the modelling and prediction of water quality index. A design concept of a water purification system is disclosed in this work. The proposed model exhibits a prediction performance of 0.98114.
AB - Artificial intelligence can significantly lower water supply and sanitation systems and assist to ensure compliance with drinking water and wastewater treatment standards. As a result, there has been extensive research on modelling and forecasting water quality to reduce water pollution. The proposed system's uniqueness is offered to create an effective monitoring operation. This paper uses Artificial Neural Network (ANN) for the prediction of water quality index (WQI). Seven important water quality parameters were considered, namely the Dissolved Oxygen (DO), the pH, the conductivity, the Biochemical Oxygen Demand (BOD), the nitrate, faecal coliform, and the total coliform. In the study, seven parameters were used for the modelling and prediction of water quality index. A design concept of a water purification system is disclosed in this work. The proposed model exhibits a prediction performance of 0.98114.
KW - artificial intelligence
KW - artificial neural network
KW - water purification
KW - water quality index
UR - http://www.scopus.com/inward/record.url?scp=85168764507&partnerID=8YFLogxK
U2 - 10.1109/ICMIMT59138.2023.10199388
DO - 10.1109/ICMIMT59138.2023.10199388
M3 - Conference contribution
AN - SCOPUS:85168764507
T3 - 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023
SP - 100
EP - 104
BT - 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2023
Y2 - 26 May 2023 through 28 May 2023
ER -