Temperature & Humidity Prediction Using Data Mining

The scope of this research work is to investigate the importance of data mining technique in understanding the variation of temperature and humidity data for which some statistical and mathematical models are used. Here, historical climate data (temperature and humidity) of a region and data mining algorithm K-Nearest Neighbor is used for prediction of temperature and humidity values based on which classification of climate condition is done. It has become important to find an effective and accurate tool to analyze and extract hidden knowledge from climate data due to its increasing availability during the last decade. Knowledge of climate data in a region is essential for business, society, agriculture, energy applications, research and development. Temperature and humidity data is also used in the estimation of bio-meteorological parameters in a region. Data Mining is recently applied to show affect of climate variation on human society and thus, statistical Data Miner software is used in this research work for the data mining purpose which is intelligent data miner software tool where various algorithms are applied.