Any comprehensive plan for management of urban solid wastes requires accurate forecast of the waste level. Development of a reliable model to predict impacts of economic trends, changes in population, and environmental transformations on generation of solid waste is a crucial progress in terms of waste management. The present study, therefore, applies fuzzy regression models to forecast the level of solid waste generated by urban population. Given the lack of data in developing countries, fuzzy regression approach can be useful in properly forecasting quantities of solid waste. The present study employs fuzzy regression approach to time series to forecast quantity of waste produced by urban population of Mashhad in 2012-2021 by taking into account most significant economic, social, and environmental factors. A number of variables are used to fit the models, and then the best model is selected based on minimum fuzziness criterion. For this purpose, a hybrid method has been utilized to combine fuzzy regression and autoregressive integrated moving average (ARIMA).

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