Non-Linear Autoregressive Dissolved Oxygen Prediction Model for Paddy Irrigation Channel

• Published in: TEM Journal
• Main Author: Aisha S.M.; Thamrin N.M.; Ghazali M.F.; Ibrahim N.N.L.N.; Ali M.S.A.M.
• Format: Article
• Language: English
• Published: UIKTEN - Association for Information Communication Technology Education and Science 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131439340&doi=10.18421%2fTEM112-43&partnerID=40&md5=b755576739cb833c8eec3d90564f33f6
• ISSN: 22178309
• DOI: 10.18421/TEM112-43

This study has proposed a non-linear autoregressive model to predict one-day ahead dissolved oxygen in paddy field irrigation channel. A 32-day data is obtained from Kampung Padang To’ La in Pasir Mas, Kelantan using off-the shelf water quality parameter sensors. Analysis has revealed no correlation between dissolved oxygen with pH and electrical conductivity. A non-linear autoregressive model is then developed using the dissolved oxygen measurements and artificial neural network. A prediction model developed using Levenberg-Marquardt algorithm yielded the best results with overall regression of 0.9253. The model has also passed all correlation tests and can therefore, be accepted. © 2022. Syafira Mohd Aisha et al; published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License.