Assessing rainfall prediction models: Artificial neural networks (ANN)

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.

Authors

Publication Details

Published
2025-12-05
DOI
https://doi.org/10.13164/juniorstav.2025.25047
Primary Topic
Hydrological Forecasting Using AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing rainfall prediction models: Artificial neural networks (ANN)

Halil Ibrahim Yildiz
Hydrological Forecasting Using AI
article

Assessing rainfall prediction models: Artificial neural networks (ANN)

Halil Ibrahim Yildiz
article en

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.

Openalex Percentile: Top 63%
Hydrological Forecasting Using AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Assessing rainfall prediction models: Artificial neural networks (ANN) — Halil Ibrahim Yildiz · (2025) | TGRS Research Map | TGRS