دسته بندی:

داده های بزرگ - big data

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سال انتشار:

2020

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عنوان انگلیسی مقاله:

Prediction of greenhouse gas emissions from Ontario’s solid waste landfills using fuzzy logic based model

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ترجمه فارسی عنوان مقاله:

پیش بینی انتشار گازهای گلخانه ای از محل های دفع زباله جامد انتاریو با استفاده از مدل مبتنی بر منطق فازی

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منبع:

Sciencedirect - Elsevier - Waste Management, 102 (2020) 743-750: doi:10:1016/j:wasman:2019:11:035

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نویسنده:

Riham A. Mohsen ⇑, Bassim Abbassi

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چکیده انگلیسی:

In this study, multi-criteria assessment technique is used to predict the methane generation from large municipal solid waste landfills in Ontario, Canada. Although a number of properties determine the gas generation from landfills, these parameters are linked with empirical relationships making it difficult to generate precise information concerning gas production. Moreover, available landfill data involve sources of uncertainty and are mostly insufficient. To fully characterize the chemistry of reaction and predict gas generation volumes from landfills, a fuzzy-based model is proposed having seven input parameters. Parameters were identified in a linguistic form and linked by 19 IF-THEN statements. When compared to measured values, results of the fuzzy based model showed good prediction of landfill gas generation rates. Also, when compared to other first order decay and second order decay models like LandGEM, the fuzzy based model showed better results. When plotting the LandGEM and Fuzzy model values to the actual measured data, the fuzzy model resulted in a better fit to actual data than the LandGEM model with a coefficient of determination R2 of 0.951 for fuzzy model versus 0.804 for LandGEM model. The results show how multi-criteria assessment technique can be used in modelling of complicated processes that take place within the landfills and somehow accurately predicting the landfill gas generation rate under different operating conditions
Keywords: Municipal solid waste | Landfill gas | Life-cycle assessment | Waste to energy | Greenhouse gas emissions | Fuzzy model

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قیمت: رایگان

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توضیحات اضافی:

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