Solid Waste Prediction using ANN in the Nagpur City

Abstract: The objective of this paper is to predict the quantity of solid waste generated in Nagpur city. As population is increasing day by day solid waste generation is also increasing. This is very big question in front of NMC that how to tackle this problem. It is very important to predict the quantity of solid waste in the upcoming year to implement the best solid waste management system. Nagpur city is divided in to ten zones by NMC for better administration. Solid waste is collected from each zone and transferred at dumping station Bhandewadi, Nagpur. Solid waste prediction for the city like Nagpur is quite challenging as the values of the variables changes over the time rapidly. After studying the working of NMC, Nagpur city profile and literature review four factors, zone wise population, generated solid waste, slum population and electricity consumption in KWh/capita/day has been considered as most important factor in solid waste generation in the city. A radial basis function neural network mainly known for time series prediction is used in calculating the solid waste generated at Nagpur city. This work may be helpful to NMC for better implementation of solid waste management system.

Keywords: Nagpur Municipal corporation (NMC), Artificial Neural Networks (ANNs); Solid Waste Management System (SWMS); Neural Network (NN); Solid Waste (SW); kilo watt hour ( KWh); House Hold (HH).