Статья 'Применение многоцелевой оптимизации для прогнозирования групп временных рядов ' - журнал 'Кибернетика и программирование' - NotaBene.ru
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Cybernetics and programming

Application of multiobjective pptimization for time series groups forecasting

Astakhova Nadezhda

graduate student, Department of Computational and Applied Mathematics, Ryazan State Radio Engineering University

390005, Russia, Ryazanskaya oblast', g. Ryazan', ul. Gagarina, 59/1

Demidova Liliya

Doctor of Technical Science

Professor, Department of Computational and Applied Mathematics, Ryazan State Radio Engineering University; Department of Informatics and Automation, Oskovsky Institute of Technology

390005, Russia, Ryazanskaya oblast', g. Ryazan', ul. Gagarina, 59/1

Nikulchev Evgeny

Doctor of Technical Science

Professor, Vice-Rector for Research,  Moscow Institute of Technology; Chief Researcher, Kuban State University

119334, Russia, Moskva, g. Moscow, ul. Leninskii Prospekt, 38A




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Abstract: In article the approach to forecasting of time series groups with use of technologies of the cluster analysis and the principles of multiobjective optimization has been offered. The description of time series – centroids of clusters with use of the forecasting models on the base of the strictly binary trees and the multiobjective modified clonal selection algorithm in case of which the implementation of two quality indicators of models – the affinity indicator based on calculation of an average forecasting relative error and the tendencies discrepancy indicator are involved in selection process of the best forecasting models has been developed. Accounting of quality two indicators of the forecasting model is realized with use of the Pareto-dominance principles applied when forming new populations of the forecasting models in the multiobjective modified clonal selection algorithm. Within the solution of a problem of multiobjective optimization when forming new population of the forecasting models for maintenance of its high variety it is offered to consider values of the crowding distance of the forecasting models. Prospects of application of the general forecasting models created on the base of the strictly binary trees for forecasting of the time series entering one cluster are shown. The results of experimental studies confirming the efficiency of the offered approach to short-term and mid-term forecasting of time series groups within the solution of a problem of multiobjective optimization are given.

Keywords: tendencies discrepancy indicator, affinity indicator, multiobjective optimization, clonal selection algorithm, strictly binary tree, forecasting model, time series, average error rate, Pareto-dominance, crowding distance
This article written in Russian. You can find full text of article in Russian here .

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