Neurofuzzy method setting of norms electro-consumption ore enriching factory MEC
DOI:
https://doi.org/10.15587/1729-4061.2012.5779Keywords:
electricity, rationing, ore mining factory, adaptive neural networkAbstract
The results of the second stage of research work, which is funded by the Open joint-stock company “UGOK” (Krivyi Rih) under contract №1392 from 01.09.2012 with State institution of higher education «Kryvyi Rih National University». Purpose ‑ to develop a method rationing concentration plants electricity in order to systematically implement energy saving measures.
Expected results: the implementation of the developed method rationing electricity in ore production will occur reducing the costs of routine preventive repairs to 40% and reduce the energy consumption departments of ore mining enterprises to 2%.
An economic effect is arrived for next ways: increasing reliability rationing objects electricity with application of neuro-fuzzy prediction method; exposuring objects and subsections which consume electric power unrationally and have most potential of energy saving.
The article presents results of development rationing ore mining factories electricity method which based on the process electricity neuro-fuzzy model of these subsections. The results of developed method industrial tests confirm efficiency of his application which will allow system to inculcate measures on energy saving on ore mining enterprisesReferences
- Кудрин Б.И. Проблемы создания и управления ценозами искусственного происхождения // Кибернетические системы ценозов: Синтез и управление. – М.: Наука, 1991. – С. 5 – 17.
- Гнатюк В.И. Закон оптимального построения техноценозов. – Выпуск 29. Ценологические исследования. – М.: Изд-во ТГУ – Центр системных исследований, 2005.
- Аналіз енергетичних режимів роботи основних цехів ВАТ «ПівнГЗК»: Звіт з НДР/ Криворізький техн. університет. – № 1238. -Кривий Ріг, 2003.-150 с.
- Osowski S. Sieci neuronowe do przetwarzania informacji. Oficyna wydawnicza politechniki warszawskiej, Warszawa, 2000. - Pp. 124-128.
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