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About Deep Learning and Weather Forecasting Research
This document discusses using deep learning techniques for weather forecasting. It evaluates techniques like the deep hybrid model, multilayer perception, and recurrent neural networks. The deep hybrid model uses wind data as a two-dimensional vector and trains an algorithm to forecast weather with high accuracy. Multilayer perception uses a typical neural network structure to predict weather from photovoltaic data. Recurrent neural networks use a structure that incorporates sequential data like weather patterns over time. Overall, deep learning shows promise for improving weather forecasting accuracy and speeding predictions.
Detailed Information
| Author: | ['Chathuranga Rathnayake'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 24 |
| Language: | English |
| Format: | |
| Price: | FREE |
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