پیش بینی نرخ تولید پسماند شهر تبریز با استفاده از روش های هوش مصنوعی (ANN و SVM) و پیش پردازش موجکی برای افق بلندمدت

مینوسپهر م، علیزاده م، طالب بیدختی ن، "ارزیابی تکنیک ­های هوش محاسباتی در پیش­ بینی سرانه تولید پسماند (مطالعه موردی: استان هرمزگان)"، نشریه مهندسی عمران و محیط زیست دانشگاه تبریز، 1397، 48 (1)، 67-75.

Abbasi M, Abduli M, Baghvand A, “Forecasting municipal solid waste generation by hybrid support vector machine and partial least square model”, International Journal of Environmental Research, 2012, 7 (1), 27-38.

Abbasi M, Abduli M, Omidvar B, Baghvand A, “Results uncertainty of support vector machine and hybrid of wavelet transform-support vector machine models for solid waste generation forecasting”, Environmental Progress and Sustainable Energy, 2014, 33 (1), 220-228.

Abdoli MA, Falah Nezhad M, Salehi Sede R, Behboudian S, “Longterm forecasting of solid waste generation by the artificial neural networks”, Environmental Progress and Sustainable Energy, 2012, 31 (4), 628-636.

Adeleke O, Akinlabi SA, Jen TC, Dunmade I, “Prediction of municipal solid waste generation: an investigation of the effect of clustering techniques and parameters on ANFIS model performance”, Environmental Technology, 2020. DOI: 10.1080/09593330.2020.1845819.

Azadi S, Karimi-Jashni A, “Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province”, Iran. Waste Management, 2016, 48, 14-23.

Azarmi S, Oladipo A, Vaziri R, Alipour H, “Comparative modelling and artificial neural network inspired prediction of waste generation rates of hospitality industry: The Case of North Cyprus”, Sustainability 2018, 10, 2965. DOI:10.3390/su10092965.

Beigl P, Lebersorger S, Salhofer S, “Modelling municipal solid waste generation: A review”, Waste Management, 2008, 28 (1), 200-214.

Hagan MT, Menhaj MB, “Training feed forward networks with the Marquaradt algorithm”, IEEE Transactions on Neural Networks, 1994, 6, 861-867.

Kim T, Valdes JB, “Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks”, Journal of Hydrologic Engineering, 2003, 8 (6), 319-328.

Legates D, McCabe G, “Evaluating the use of ‘goodness‐of‐fit’ Measures in hydrologic and hydro climatic model validation”, Water Resources Research, 1999, 35 (1), 233-241.

Noori R, Abdoli M, Farokhnia MA, Abbasi M, “Results uncertainty of solid waste generation forecasting by hybrid of wavelet transform-ANFIS and wavelet transform-neural network”, Expert Systems with Applications, 2009, 36 (6), 9991-9999.

Noori R, Karbassi A, Salman Sabahi M, “Evaluation of PCA and Gamma test techniques on ANN operation for weekly solid waste prediction”, Journal of Environmental Management, 2010, 91 (3), 767-771.

Nourani V, Andalib G, “Daily and monthly-suspended sediment load predictions using wavelet based artificial intelligence approaches”, Journal of Mountain Science, 2015, 12 (1), 85-100.

Nourani V, Razzaghzadeh Z, Baghanam AH, Molajou A, “ANN-based statistical downscaling of climatic parameters using decision tree predictor screening method”, Theoretical and Applied Climatology, 2019, 137 (3-4), 1729 1746.

Song J, He J, Zhen J, “Real-time data assimilation for improving linear municipal solid waste prediction model: a case study in Seattle”, Journal of Energy Engineering, 2015, 141 (4), 05014002.

Vapnik V, Cortes C, “Support vector networks”, Machine Learning, 1995, 20, 1-25.

Yetilmezsoy K, Ozkaya B, Cakmakci M, “Artificial intelligence-based prediction models for environmental engineering”, Neural Network World, 2011, 21 (3), 193-218.

Younes MK, Nopiah ZM, Ahmad Basri NE, Basri H, Abushammala MFM, Maulud KNA, “Solid waste for ecasting using modified ANFIS modeling”, Journal of the Air and Waste Management Association, 2015, 65 (10), 1229-1238.