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@article{156212,
        author = {Yamini.k and Madhushree.V and B.Anitha and Pooja.H.R. and Anupama P V and Aruna M G.},
        title = {Automated Crop Yeild Prediction(ACYP) using Machine learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {3},
        pages = {26-30},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156212},
        abstract = {Agriculture is the pillar of the Indian economy and more than 50% of India’s population are dependent on agriculture for their survival. Variations in weather, climate, and other such environmental conditions have become a major risk for the healthy existence of agriculture. Machine learning (ML) plays a significant role as it has decision support tool for Automated Crop Yield Prediction (ACYP) including supporting decisions on what crops to grow and what to do during the growing season of the crops. The present research deals with a systematic review that extracts and synthesize the features used for ACYP and furthermore, there are a variety of methods that were developed to analyze crop yield prediction using artificial intelligence techniques.},
        keywords = {Agriculture, Crop Yield Prediction, Machine Learning Methods},
        month = {},
        }