Using machine learning algorithms for solar heat supply system

Abstract

Using machine learning algorithms for solar heat supply system

Kunelbayev M.M.

Incoming article date: 26.02.2022

This article explores the use of machine learning algorithms to identify anomalies in a solar heating system. The developed solar heating system consists of several parts to simplify the process of description and modeling. The author propose a new neural network architecture based on ordinary differential equations. The idea is to apply the new architecture to practical problems of accident forecasting (the problem of extrapolation of time series) and classification (classification of accidents based on historical data). The developed machine learning algorithms, artificial intelligence methods, and the theory of differential equations - these areas allow us to build a model for predicting system failure. Database management theory (relational databases) - these systems allow you to establish optimal storage of large time series.

Keywords: flat solar collector, solar heating system, machine learning, algorithm