Abstract
In Ecuador, solar radiation and wind speed data are not always available for places of interest due to the absence of meteorological stations. Within the scope of this work, a low-cost automatic weather station prototype based on Raspberry technology was developed to measure the variables mentioned above. The objective of this work is twofold: a) to present a project proposal for a low-cost automatic meteorological station using the Raspberry Pi microcomputer, showing the viability of this technology as an alternative for the construction of an automatic meteorological station, and; b) to use neural network forecasting to predict solar radiation in Manta, Ecuador, based on historical data collected: solar radiation, wind speed, and direction. We prove that technology feasibility and machine learning have a high potential as a tool to be used in this field of study.
Translated title of the contribution | Neural networks for solar radiation prediction in Manta - Ecuador |
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Original language | Portuguese (Brazil) |
Pages (from-to) | 183-194 |
Number of pages | 12 |
Journal | Revista Campo da História |
Volume | 8 |
Issue number | 1 |
DOIs | |
State | Published - 31 Jan 2023 |
Keywords
- Meteorological station
- Solar radiation
- Wind speed
- Neural networks
- Forecast