Convex-hull & DBSCAN clustering to predict future weather

Machine learning methods are increasingly being used in conjunction with conventional meteorological observations in the synoptic analysis and conventional weather forecast to extract information of relevance for agriculture and food security of the human society in India. Density based clustering approach is incrementally used to predict the future weather conditions in this paper. One famous preprocessing approach, known as Convex-Hull is also used before fed the pollutant data into the clustering algorithm. This Convex-Hull method is strictly used to convert unstructured data into its corresponding structured form. These structured data is efficiently and effectively used by the DBSCAN clustering algorithm to form resultant clusters for weather derivatives. This forecasting database is totally based on the weather of Kolkata city in west Bengal and this forecasting methodology is developed to mitigating the impacts of air pollutions and launch focused modeling computations for prediction and forecasts of weather events. Here accuracy of this approach is also measured.