Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 10, Pages: 1-5
Anjana Joseph1 and M. Lakshmi2
1Department of Computer Science and Engineering, Sathyabama University,Chennai-600119, Tamil Nadu, India; [email protected] 2Faculty of Computing, Sathyabama University, Chennai-600119,Tamil Nadu, India; [email protected]
Objectives: The main objective of this paper is to propose a methodology to develop a Storm analysis model from Raw Rainfall dataset using techniques such as Artificial Neural Network and Min-Max Algorithm. Storm analysis model aims at predicting the occurrence and strength of a storm by analyzing the rainfall data of that region. Methods: In the proposed methodology the raw rainfall dataset is being trained by Artificial Neural network based on the three layers -Input, Hidden, and Output layers. The trained dataset is then summarized into a model which performs the prediction of storm centric characteristics. Neural network training is implemented in Hadoop framework. We obtain a considerable improvement in the total performance of the system by employing Artificial Neural Network. Min-Max algorithm is also used in the system for predicting the intensity of storm. The dataset used for training and prediction consists of daily rainfall data of Cherrapunjee area collected by The Meteorological Department of India. Findings: In the existing system, the raw rainfall dataset is collected and stored in a relational database and then map-reduce based techniques are applied for storm analysis. The major disadvantages associated with this technique are the performance and accuracy rate get reduced with increase in data size. In the proposed methodology as the raw rainfall dataset is being trained by Artificial Neural network the performance and accuracy rate got improved. Also, the training process is done on multi-node hadoop cluster by considering large raw rainfall dataset. With multi-node hadoop cluster there was a large reduction in the total training time. Storm depth of a particular region is calculated by applying MIN-MAX algorithm. This improved the total efficiency of the storm intensity prediction. Applications/Improvement: The performance of the system can be further improved by reducing the training time by adding more nodes while implementing the process in multi node hadoop cluster. Also higher prediction accuracy can be obtained by combining various suitable fuzzy inference models5 with the proposed neural network mode.
Keywords: Artificial Neural Network, Hadoop, MIN-MAX Algorithm, Rainfall Data, Storm Analysis
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