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Vol.11, No.2, May 2022. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Non-Linear Autoregressive Dissolved Oxygen Prediction Model for Paddy Irrigation Channel
Syafira Mohd Aisha, Norashikin M. Thamrin, Muhammad Fariq Ghazali, Nik Nor Liyana Nik Ibrahim, Megat Syahirul Amin Megat Ali
© 2022 Megat Syahirul Amin Megat Ali, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 11, Issue 2, Pages 842-850, ISSN 2217-8309, DOI: 10.18421/TEM112-43, May 2022.
Received: 17 March 2022. Revised: 08 May 2022.
Abstract:
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.
Keywords –Paddy, non-linear autoregressive, neural network, dissolved oxygen, Levenberg-Marquardt. |
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