A Hybrid Data Model for Prediction of Disaster using Data Mining Approaches

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2016 by IJETT Journal
Volume-41 Number-7
Year of Publication : 2016
Authors : Arjun Singh, Prof. AmitSaxena
DOI :  10.14445/22315381/IJETT-V41P270


Arjun Singh, Prof. AmitSaxena "A Hybrid Data Model for Prediction of Disaster using Data Mining Approaches", International Journal of Engineering Trends and Technology (IJETT), V41(7),384-392 November 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

The disasters are the unwanted event which affect the human life and human not able to recover form it’s effects by available resources. Therefore these events are classified according to the natural or the human initiated. The human initiated disasters are controllable but the natural events are unpredictable in nature. In the literature the different data models are available that claims to understand and predict the much nearer data for any unpredictable events such as stock market, frauds and others. All these techniques are developed with the help of data mining techniques. That involves the computational algorithms for learning with historical patterns and predicts the data according to current situations. By the motivations of these techniques in this presented work a new data model is proposed which collect the real world knowledge from the web data sources and use with the data mining algorithms for predicting the unpredictable natural disasters. In order to perform this K-means clustering and HMM based hybrid model is proposed. The k-means clustering algorithm helps to prepare the disaster observations and the HMM algorithm is used for training and prediction of the disaster events. The implementation of this model is performed using the JAVA technology. After implementation the results are considered in conditions of exactness, error rate, memory expenditure and the time consumption. The results show the presentation of the futuremethod is accurate and efficient for prediction with any kind of other data also.


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natural disaster, prediction, data mining, HMM, K-means, Hybrid data mining.