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Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/35393
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Документ Моделирование температуры обратной сетевой воды ТЭЦ(Інститут електродинаміки НАН України, 2005) Вороновский, Геннадий Кириллович; Махотило, Константин Владимирович; Сергеев, Сергей АлександровичThe return water temperature model for a large district heating system is suggested. The hot tap water load impact on return water tem-perature is considered and the distribution time for heating network is estimated. The neural-network-based model is synthesized and successfully tested on data from Kharkiv CHP Plant 5 during heating season 2005.Документ Evolutionary Synthesis of Dynamical Object Emulator Based on RBF Neural Network(Nagoya University, 1996) Sergeev, S. A.; Mahotilo, K. V.The combination of Genetic Algorithms (GAs) and Artificial Neural Networks (ANNs) has already resulted in researchers advancing in quite a few real world applications but it is in control that this alliance yields much appreciable benefit. The paper reports a Radial Basis Function (RBF) network training technique which joins together global strategy of GAs and a local adjusting procedure typical for RBF networks. While activation function window centres and widths are processed via a "slow" numeric GA, output-layer neurone synaptic weights are defined by a "fast" analytical method. The technique allows to minimize not only the network hidden-layer size but also the pattern set required for training the adequate dynamical object neuroemulator.