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- W2895064910 abstract "Forecasting the weather has always been a challenge using conventional methods of climatology, analogue and numerical weather prediction. To improvise the prediction of weather much further, the proposed method can be used. In this work, authors proposed a method which uses the advantages of deep neural network to achieve high degree of performance and accuracy compared to the old conventional ways of forecasting the weather. It is done by feeding the perceptrons of the DNN some specific features like temperature, relative humidity, vapor and pressure. The output generated is a highly accurate amount of the rainfall based on the given input data." @default.
- W2895064910 created "2018-10-12" @default.
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- W2895064910 date "2018-10-05" @default.
- W2895064910 modified "2023-09-24" @default.
- W2895064910 title "Quantitative Rainfall Prediction: Deep Neural Network-Based Approach" @default.
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- W2895064910 doi "https://doi.org/10.1007/978-981-13-1544-2_37" @default.
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