Hybrid system of computational intelligence based on bagging and group method of data handling
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Дата
2024
Науковий керівник
Назва журналу
Номер ISSN
Назва тому
Видавець
КПІ ім. Ігоря Сікорського
Анотація
The paper considers the problem of short- and middle-term forecasting in the financial sphere. To solve this problem, a hybrid system of computational intelligence based on the group method of data handling (GMDH) and bagging, as well as an algorithm for its training, is proposed. The odd stacks of the hybrid system are formed by ensembles of parallel connected subsystems. ARIMA and the GMDHneo-fuzzy hybrid network were chosen as such subsystems. The proposed system does not require a large training data set, automatically determines the number of stacks during training, and provides online operation. The experimental investigations were conducted using the proposed hybrid system, as well as separately using ARIMA and GMDH-neo-fuzzy. The accuracy of the predictions obtained is compared, based on which the feasibility of using the proposed hybrid system is substantiated.
Опис
Ключові слова
hybrid system, bagging, hybrid GMDH-neo-fuzzy network, ARIMA, short- and middle-term forecasting, гібридна система, беггінг, гібридна мережа МГУА-нео-фаззі, короткострокове та середньострокове прогнозування
Бібліографічний опис
Hybrid system of computational intelligence based on bagging and group method of data handling / Bodyanskiy Ye., Kuzmenko O., Zaichenko He., Zaychenko Yu. // Системні дослідження та інформаційні технології : міжнародний науково-технічний журнал. – 2024. – № 1. – С. 75-85. – Бібліогр.: 17 назв.