A Methodology of Atmospheric Deterioration Forecasting and Evaluation through Data Mining and Business Intelligence

Abstract

The paper emphasis on an instinctual and efficacious method to forecast and analyze the condition of different atmospheric determinants all over the world. The difficulty in the extant remedies or the apparatus is its incapability to provide a comprehensive information regarding the evaluation of the attributes of the atmosphere. The proposed methodology in the paper gathers the actual information about the atmospheric attributes such as the water, air, the forest and the tree cover etc. from the government bases and processes the collective information. The methodology does the extrication transformation load over the original collective data’s that are in its raw format. The converted information sets are imported into the database to develop a dash boards with the multiple information’s displayed on it. This allows to have an evaluated data about the various atmospheric factors. To forecast the deteriorations and the conditions of the atmospheric attributes the methodology proffered utilizes the Fuzzy C means clustering, R-studio, and the ARIMA frame work. The dash board assists the NLP enabling the end users to post their queries as input and get back the desired output. The developed deterioration forecasting and evaluation can be used in the evaluation of the conditions of atmospheric attributes for the different countries in the world.