Open AccessApplication of machine learning to predict the thermal power plant process condition
Author(s) -
М. М. Султанов,
И. А. Болдырев,
Kirill V. Evseev
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2150/1/012029
Subject(s) - python (programming language) , computer science , thermal power station , process (computing) , machine learning , artificial intelligence , thermal , power station , data mining , engineering , programming language , electrical engineering , physics , meteorology
This paper deals with the development of an algorithm for predicting thermal power plant process variables. The input data are described, and the data cleaning algorithm is presented along with the Python frameworks used. The employed machine learning model is discussed, and the results are presented.