Year: 2025
Type: conference-paper
Abstract: Precipitation data are important for solving engineering problems. Missing data can be predicted, and historical data can be used to construct precipitation models. This study used monthly precipitation data, temperature, relative humidity, wind, and evaporation data from the Afyon Meteorological Observatory station between 1929 and 2018. The ANN (Artificial Neural Network) method was used to predict precipitation data, and the results were compared with MLR (Multilinear Regression) models.
Author: Halil Ibrahim Yildiz
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4417109582
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