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@article{166722,
        author = {Mallyala Nissie and Kasarla Sai Anirudh},
        title = {Crop production optimisation: a blended technique using XGBoost and Simulated Annealing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {1729-1734},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166722},
        abstract = {India's economy thrives mainly because of agriculture, which takes care of billions of people. Even so, it requires a new way to help improve crop production since there exist problems like over population, changing weather patterns or need for sustainable practices. The authors of this paper decided to introduce a different technique for boosting crop yields in different parts of India through a combination of Simulated Annealing (SA) and Extreme Gradient Boosting (XGBoost) models. The methodology aims at making crop management approaches better suited.},
        keywords = {Farming, Machine learning, Stimulated Annealing, XGBoost},
        month = {July},
        }