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Combined approach to forecasting of manufacturing system target indicators in a changing external environment
Author(s) -
Zinaida K. Avdeeva,
E. A. Grebenyuk,
Svetlana V. Kovriga
Publication year - 2019
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2019.09.261
Subject(s) - computer science , key (lock) , identification (biology) , business environment , order (exchange) , performance indicator , system dynamics , data mining , operations research , artificial intelligence , engineering , business administration , botany , computer security , management , finance , economics , business , biology
The paper presents a combined approach to forecasting of the manufacturing system target indicators, depending on the key factors determining the functioning of this system and business environmental factors. The approach includes: (i) identification of key factors and weak signals influencing the target indicators by analyzing the system functioning model in the external environment represented by a cognitive map of the situation; (ii) analysis of dynamics of the identified key factors and manufacturing system target indicators and the construction of a forecast model using time series analysis methods; (iii) monitoring of the heterogeneous information space in order to detect changes in trends and the composition of parameters of the forecast model; (iv) correction of the forecast model and cognitive map of the situation according to the results of the detected changes. The approach is focused on the formation of long-term forecasts of the target indicators and increasing the accuracy of these forecasts by identifying significant influencing events whose influence does not have time to reflect in time series.

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