Government College of Science

Semiparametric hybrid air quality forecasting using prophet ensemble and feature selection

Due to air quality management and public health planning, accurately predicting PM2.5 concentrations is absolutely imperative. Having many lagged variables, interactions between pollutants and other temporal features means that high-dimensional environmental datasets (that may in...

Development of water consumption prediction models: a data-driven machine learning and deep learning approach

Water demand is increasing day by day due to rapid growth in urban areas and varying climatic conditions. Therefore, it becomes necessary to manage water resources in a sustainable way. Water consumption prediction can greatly support sustainable water resource management. In thi...