Data mining as a tool for hot day prediction during summer monsoon

Human health, energy, and comfort are affected more by climate than by any other element of the physical environment. Physiological functions of the human body respond to changes in the weather with climate and the seasons. The emphasis of present work is to provide the hot day temperature patterns during April and May months and extract its behavioral aspects using association rule mining of data mining technique. This study describes that the proposed learning mechanism can predict the occurrence of hot day during April and May months over the coastal station Cuddalore (Latitude 11°46' N / Longitude 79°46' E) of south east India. The proposed model finds the extreme hot day prediction 24 hours ahead and 48 hours ahead with the help of local weather parameters.