A hadoop based weather prediction model for classification of weather data

Big Data is spreading vastly in the industry. Most of the industries want to have the records of not only the work they do but also are eager to know the taste of the consumer. Big Data is becoming relative to almost all aspects of human activity from just recording events to research, design, production and digital services or products delivery to the final consumer. In this work, application of big data is investigated in the field of weather prediction. The weather prediction data is generated from various sources such as radar, ships, ground observation etc. It contains certain useful and useless information for prediction of weather data and in the form of unstructured data. Further, in this work, Hadoop framework is applied to process this unstructured data. The word count algorithm is being used to find the overall condition of that day. Further fuzzy logic (FL) and artificial neural network fuzzy interface system (ANFIS) methods are investigated for accurate prediction of weather data on the basis of mean square error. Experimental results show that the ANFIS method gives more accurate results in comparison to other methods being compared.