ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR BIOGAS YIELD PREDICTION

Currently, effective management of biogas production remains a difficult task. The purpose of the research is to analyze machine learning algorithms for predicting biogas output depending on the characteristics of biogas production. Currently, there is no necessary set of data, analyzing which indicators can be obtained to optimize biogas production in our installation. At the same time, testing various optimization algorithms and deciding on the best takes a lot of time, as experience shows. The application of machine algorithms for forecasting biogas production by using existing forecasting methods is considered. Provided that the control systems of typical biogas productions are equipped with the necessary sensing elements, there still remains the task of processing and analyzing data to make the best decision to meet the relevant technological requirements. The reason for this is the large volume of data and the complexity of the interaction of processes that are components of production. In this context, machine learning can be a useful tool for optimizing biogas production.