Mohammad Alamgeer1, Amal Al-Rasheed2, Ahmad Alhindi3, Manar Ahmed Hamza4,*, Abdelwahed Motwakel4, Mohamed I. Eldesouki5
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2725-2738, 2023, DOI:10.32604/cmc.2023.029163
- 31 October 2022
Abstract Data mining process involves a number of steps from data collection to visualization to identify useful data from massive data set. the same time, the recent advances of machine learning (ML) and deep learning (DL) models can be utilized for effectual rainfall prediction. With this motivation, this article develops a novel comprehensive oppositional moth flame optimization with deep learning for rainfall prediction (COMFO-DLRP) Technique. The proposed CMFO-DLRP model mainly intends to predict the rainfall and thereby determine the environmental changes. Primarily, data pre-processing and correlation matrix (CM) based feature selection processes are carried out. In More >
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