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Development of trees management system using radial basis function neural network for rain forecast

Auzani, Hasnul and Hashim, Khairusy Syakirin Has-Yun and Mohd Nazri, Farah Aniza (2021) Development of trees management system using radial basis function neural network for rain forecast. Computational Water, Energy, and Environmental Engineering, 11 (1). pp. 1-10. ISSN 2168-1562 E-ISSN 2168-1570

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Agriculture and farming are mainly dependent on weather especially in Malaysia as it received heavy rainfall throughout the years. An efficient crop or tree management system with a weather forecast needed for suitable planning of farming operation. Radial Basis Function Neural Network (RBFNN) algorithm was used in this study to predict rainfall and the main focus of this study is to analyze the factor that affects the performance of neural model. This study found that the model works better the more hidden nodes and the optimum learning rate is 0.01 with the RMSE 49% and the percentage accuracy is 57%. Besides that, it is found that the meteorology data also affect the model performance. Future research can be conducted to improve the rainfall forecast of this study and improve the tree management system.

Item Type: Article (Journal)
Uncontrolled Keywords: Tree Management, Radial Basis Function, Rain Prediction, Artificial Neural Network
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Architecture and Environmental Design > Department of Quantity Surveying
Depositing User: Dr. Khairusy Syakirin Has-Yun Hashim
Date Deposited: 03 Oct 2022 14:10
Last Modified: 03 Oct 2022 14:10
URI: http://irep.iium.edu.my/id/eprint/100391

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