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- W4386310905 abstract "Weather forecasting accuracy is a challenging task faced throughout the world today because of its multi-dimensional and nonlinear data. Weather forecasting is a method that relies on a variety of meteorological data to make predictions about the atmospheric state. The technological development has made it possible for us to make predictions using complex mathematical models. There are several soft computing techniques and algorithms through which the weather changes can be predicted. For the last three decades, soft computing-based learning models have shown much better results for weather forecasting. This is due to their pattern classification and pattern recognition capability. These soft computing-based learning models are applied on massive past datasets to predict future weather conditions. This study presents an overview of various methods for improving the predicting accuracy of weather forecasts using soft computing-based learning models." @default.
- W4386310905 created "2023-09-01" @default.
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- W4386310905 date "2023-01-01" @default.
- W4386310905 modified "2023-10-18" @default.
- W4386310905 title "Soft Computing Techniques for Weather Forecasting: A Review" @default.
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- W4386310905 doi "https://doi.org/10.1007/978-981-99-3485-0_32" @default.
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