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@article{150228,
        author = {NANDHINI K and Dr.G.TAMILPAVAI and AKILA RAJINI S},
        title = {PREDICTION OF CYCLONE AND ITS CLASSIFICATION USING DEEP LEARNING TECHNIQUES},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {4},
        pages = {201-206},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=150228},
        abstract = {Climate is said to be the long-term average of prevailing weather conditions which are represented using a number of the meteorological variables that are commonly measured in the terms of temperature, humidity, air pressure, wind, and precipitation. Cyclones are the deadliest meteorological phenomenon results in flooding, storm surges, heavy rainfall, significant damages to fisheries, forestry etc. Tropical cyclones originate over ocean, powered by heat transfer from the ocean surface, and stops with cold water of land. The Indian sub-continent is the worst affected part in the world by the cyclone and such cyclones are much weaker in intensity and smaller in size, yet with highest death rate. Tropical cyclones are also known as typhoons, hurricanes etc. based on their origin.  In Indian Ocean, they are called as tropical cyclones. The Dataset used in this work is North Indian Ocean Best track dataset and they are classified using the techniques of Convolutional Neural Network and Recurrent Neural Network.},
        keywords = {Tropical Cyclone, North Indian Ocean Best track dataset, Convolutional Neural Network and Recurrent Neural Network.},
        month = {},
        }