Evaluation of Machine Learning Techniques for High Dimension Dataset for Predicting Municipal Solid Waste Generation

The forecast of waste generation is an essential step for an adequate planning of waste management, since it has various factors that can be used effectively. To make a decision process, the application of predictive and prognosis models are used as tools. In this paper ,the raw dataset is obtained from the Tiruchirappalli municipal corporation as case study.The real time data set has indicators such as : population , number of residents , bio degradable waste ,non- biodegradable waste, hazardous waste and other total municipal solid waste are applied as input variables into the models to predict the amount of solid waste fractions obtained from various cities. The real time raw data set is preprocessed and applied into Support vector machine(SVM).The SVM model shows with an accuracy of 85% that is analyzed for the forecasting of solid waste generation and composition