Open AccessModels of predictive modeling on the example of a gas turbine
Author(s) -
E. Echkina,
V. V. Lvov
Publication year - 2021
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 - 10.1088/1742-6596/2090/1/012120
Subject(s) - autoregressive integrated moving average , gas turbines , task (project management) , computer science , basis (linear algebra) , work (physics) , linear regression , turbine , series (stratigraphy) , regression analysis , econometrics , time series , industrial engineering , engineering , machine learning , mathematics , mechanical engineering , systems engineering , paleontology , geometry , biology
The ability to accurately predict the operation of a particular mechanism and, on the basis of this, estimate the equipment life is a very important task. The amount of losses of the enterprise can depend on such study, as well as the health of many people whose lives depend on the health of the working installation. As part of this work, the main time series models were considered and the most suitable for the study was selected. The operation of a gas turbine was studied and a forecast was made. On the basis of the study, linear regression, ARIMA and moving average models were built and evaluated.