Prediction for Türkiye’s Tea Product With Machine Learning Algorithms
Year: 2024
Type: article
Abstract: This study predicts tea production in Turkey using machine learning algorithms. The analysis utilized data from 2001 to 2022, including tea production quantity, fresh tea prices, tea production area, temperature, and humidity. The study was conducted using the MATLAB 2023b Regression Learner toolbox. Initially, the obtained data were normalized, and then prediction performances were evaluated using various machine learning algorithms. The metrics used in the study included R², MAE, RMSE, and MSE. As a result, the Gaussian Process Regression algorithm emerged as the best-performing machine learning method
Source: Turkish Journal of Forecasting
Author: Mehmet Akif Kara
Institution: Giresun University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4405019355