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@article{151476,
        author = {Yogini  Jawale and Akshay thakare and Aditya shinde and Govind waghmare and A.G.Said},
        title = {Efficient Covid 19 Forecasting for worldwide countries using ANN},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {133-139},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151476},
        abstract = {The sudden emergence of the Covid-19 Pandemic has been one of the most problematic scenarios experienced by the global community in the recent decades. This has been especially devastating due to the large death toll and increasing economical strain due to the successive lockdowns and restrictions in place to combat the epidemic. This has been highly problematic to contain the spread of the pandemic which his highly unpredictable. The losses that have been incurred by the governments across the world have been due to problems arising by the lack of effective prediction of the Covid-19 infection rates. The predictions would allow the health sector to be better prepared for the infection number which can provide a significant boost to their efforts. Therefore, an effective approach for the prediction of Covid-19 infection rates has been illustrated in this research article. The presented approach utilizes Linear Regression along with Artificial Neural Networks and Fuzzy Classification. The extensive experimentation has been performed to determine the performance of the approach which has led to satisfactory results. },
        keywords = {Linear Regression, Artificial Neural Network, and Fuzzy Classification.},
        month = {},
        }