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- W4313155191 abstract "The prediction of weather and is difficult because these phenomena are highly non-linear and complicated phenomena. Technology based on artificial intelligence enables knowledge processing and is utilised in predicting. Synthetic neural network (ANN) has emerged as an alluring substitute for conventional statistical techniques for anticipating the behaviour of nonlinear systems The purpose of this paper is to prevent tools to model and predict rainfall behavior form past observations based on past observation. There are two fundamentally different approaches that are used in the paper to develop a model, both based on statistical methods based on ANNs. The prediction efficiency was evaluated based on 115years of mean annual rainfall between 1901and 2015." @default.
- W4313155191 created "2023-01-06" @default.
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- W4313155191 date "2022-08-11" @default.
- W4313155191 modified "2023-09-27" @default.
- W4313155191 title "Data Driven Modelling and Prediction Of Rainfall" @default.
- W4313155191 doi "https://doi.org/10.1109/icicict54557.2022.9917744" @default.
- W4313155191 hasPublicationYear "2022" @default.
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