Open AccessThe technique for increase of generating system technical and economic indexes evaluation accuracy using machine learning
Author(s) -
É. K. Arakelyan,
И. А. Болдырев,
Kirill V. Evseev,
М. М. Султанов,
V A Yurov
Publication year - 2020
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 - 10.1088/1742-6596/1683/4/042044
Subject(s) - artificial neural network , computer science , machine learning , regression , artificial intelligence , regression analysis , unit (ring theory) , power (physics) , statistics , mathematics , mathematics education , physics , quantum mechanics
This paper addresses the problem of thermal power plant generating unit efficiency evaluation accuracy increase. The comparison of classic regression analysis and artificial neural network regression approaches is described. The feasibility and reasonability of application of the machine learning techniques for generating unit performance prediction and selecting most influential parameters on its efficiency evaluation accuracy are considered.