Дослідження ефективності штучних нейронних мереж (ШНМ) різних поколінь у задачі прогнозування у фінансовій сфері

• Date: 2025
• Author Affiliations: Yevgeniy Bodyanskiy — Kharkiv National University of Radio Electronics, Kharkiv; Yuriy Zaychenko — Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv; Helen Zaichenko — Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv; Oleksii Kuzmenko — Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv
• Keywords: keywords
• Main Authors: Bodyanskiy, Yevgeniy, Zaychenko, Yuriy, Zaichenko, Helen, Kuzmenko, Oleksii
• Format: Article
• Language: English
• Published: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2025
• Subjects: покоління ШНМ; Back Propagation; LSTM; GMDH neo fuzzy; HSCI bagging
• Online Access: https://journal.iasa.kpi.ua/article/view/312420
• Journal Title: System research and information technologies

This paper discusses ANNs of different generations. The efficiency of using computational intelligence in the task of short- and medium-term forecasting in the financial sphere is investigated. For the investigation, a fully connected feed-forward network (Back Propagation), a recurrent network (LST...