PREDICTION OF CROP YIELD USING FUZZY LOGIC METHODS
Ruslan Musarbievich Bischokov, Sukhanova Svetlana F. · VESTNIK OF THE BASHKIR STATE AGRARIAN UNIVERSITY · 2023
The paper deals with the crop yield issues. Analysis, modelling and prediction of crop yields were performed based on the dynamics of changes in natural and climatic characteristics by choosing configurations of the fuzzy logic methods. The study evaluated the time series of winter wheat yields for 2008–2018 and climatic characteristics (air temperature and precipitation) for 1955–2018 using the Dixon, SmirnovGrubbs, Student and Fisher criteria. The results of the analysis are crucial for identifying the level of empirical adequacy. A computer model of crop yield dependence and climate change dynamics was developed using Fuzzy Logic application of MATLAB software. After completing the stages of training and testing the computer model variants, the authors could predict crop yields for the coming years using previously obtained meteorological values.