Weather Analysis of Guntur District of Andhra Region using Hybrid SVM Data Mining Techniques
N. Rajasekhar1, T.V. Rajini Kanth2
1N.Raja Sekhar, Assistant professor, Department of Computer Science & Engineering, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India.
2Dr. T.V. Rajini Kanth,  Professor, Department of Computer Science & Engineering, Sri Nidhi Institute of Science & Technology, Hyderabad, India.
Manuscript received on March 23, 2014. | Revised Manuscript received on April 17, 2014. | Manuscript published on April 30, 2014. | PP: 133-136  | Volume-3, Issue-4, April 2014. | Retrieval Number:  D2851043414/2013©BEIESP

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Abstract: In the recent years, weather prediction has drawn much attention for research community because it helps in safeguarding human life and their wealth. Apart from that, it is useful in effective prediction of natural calamities, agricultural yield growth, air traffic control, marine navigation, forests growth & military purposes. Literature studies shows that Machine Learning Algorithms proved to be good than the existing techniques / methodologies/traditional statistical methods. Hence development of new Hybrid SVM (Support vector machines) model is required for effective weather prediction by analyzing the given weather data and to recognize the patterns existing in it. SVM comes under the set of supervised learning methods for classifications & regression. It will be yielding good results in predicting the weather than the existing machine learning programming techniques. In this paper, Guntur district weather data sets were considered for analysis using the hybrid SVM data mining techniques.
Keywords: Weather prediction, Machine learning, Data mining techniques, Hybrid SVM.