Search
Now showing items 1-3 of 3
Machine Learning Approaches for One-Day Ahead Soil Temperature Forecasting
(2023)
Present study investigates the capabilities of six distinct machine learning techniques such as ANFIS network with fuzzy c-means (ANFIS-FCM), grid partition (ANFIS-GP), subtractive clustering (ANFIS-SC), feed-forward neural ...
The Estimation of Monthly Mean Soil Temperature at Different Depths in Sivas Province, Turkey by Artificial Neural Networks
(2023)
In this study, soil temperature of Sivas province was estimated by the
artificial neural networks (ANNs) method using data obtained from five
different meteorological measurement stations situated in provincial
borders. ...
Artificial neural networks approach for forecasting of monthly relative humidity in Sivas, Turkey
(2023)
Relative humidity is a crucial parameter for various agricultural and engineering
applications and atmospheric dynamics; hence its accurate and reliable estimation is essential.
This study aims to predict monthly relative ...