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کنگره و نمایشگاه بین المللی معدن
جزئیات رویداد
اینستاگرام تی پی بین
همایش ، رویداد ، ژورنال
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  • prediction of spontaneous heating susceptibility of indian coals using soft computing techniques

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    • تاریخ ارائه: 1389/07/20
    • تاریخ انتشار در تی پی بین: 1389/07/20
    • تعداد بازدید: 751
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     coal mine fires due to spontaneous heating have been a great concern both for the industry and researchers worldwide. they not only endanger the lives of men in mines, but also cause considerable economic losses to the organization. most of these fires could be averted if suitable preventive measures are taken. since all coals are not susceptible to spontaneous heating to the same extent, its accurate prediction is essential to plan efficient preventive measures and improve production and storage capabilities of a mine. the present paper presents a comparison of two soft computing approaches viz. fuzzy expert system and the commonly used artificial neural networks (ann) for predicting the self heating of coals. to apply these techniques, a number of coal samples of varying ranks were collected from all the major coalfields of the country. the intrinsic properties of the coal seams were determined by proximate, ultimate and petrographic analyses. the spontaneous heating proneness of the samples was studied using crossing point temperature (cpt), which is used as a measure for fire susceptibility of coal seams in indian mines. correlation studies between the intrinsic properties and cpt was carried out to identify the parameters for prediction purpose. using the constituents of proximate analysis as input parameters, cpt is predicted using fuzzy logic based on takagi-sugeno-kang (tsk) model and ann based on back propagation algorithm. the results show both the models predict cpt with reasonable accuracy.

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