Implementation of artificial neural networks for very short range weather prediction
| Autor: | Martarizal, G B Wanugroho, R M Putra |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 1528:012039 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/1528/1/012039 |
| Popis: | Weather conditions are a significant factor for various sectors such as transportation safety, development, health, etc. Therefore, high development is needed in forecasting future weather conditions. Many ways are used to predict weather conditions. Along with the development of technology now, weather prediction can be made using Artificial Intelligence (AI) technology or artificial intelligence so that the results obtained are more optimal. In this study, the artificial neural network used has a feedforward neural network algorithm using training data consisting of temperature, air pressure, air humidity, wind speed, hourly wind speed at the Juanda Meteorological Station in Surabaya in Januari 2019 with the target is intensity of rainfall. Furthermore, the data was released in the period of 1 January 2019 to 31 Januari 2019. Based on the analysis results, the Artificial Neural Network model has a fairly good performance in predicting an increase in rainfall in Surabaya. The best model is considered by a model with architecture 7 - 60 - 1 with an estimate correlation is 0.87, with an error value of -0.03. With this model, it is expected to become one of the forecaster considerations in making special weather forecasts at intervals every hour. |
| Databáze: | OpenAIRE |
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