An Artificial Intelligence-based Crop Recommendation System using Machine Learning

نویسندگان

چکیده

Agriculture is the backbone of Indian economy and a source employment for millions people across globe. The perennial problem faced by farmers that they do not select crops based on environmental conditions, resulting in significant productivity losses. This decision support system assists resolving this issue. In our study, AI helps precision agriculture improve overall crop harvest quality accuracy. research feature selection, Industry 4.0, proposes one solution, such as recommendation system, using family machine learning algorithms. data set used work downloaded from Kaggle, andlabeled. It contains total 08 features with 07 independent variables, including N, P, K, Temperature, Humidity, pH, rainfall. Then SMOTE balancing technique applied to achieve better results. Additionally, authors optimization techniques tune performance further smart factories. Cat Boosting (C-Boost) performed best an accuracy value 99.5129, F-measure-0.9916, Precision-0.9918, Kappa-0.8870. GNB, other hand, outperformed ROC-0.9569 MCC-0.9569 classification, regression, boosting algorithms

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ژورنال

عنوان ژورنال: Journal of Scientific & Industrial Research

سال: 2023

ISSN: ['0022-4456']

DOI: https://doi.org/10.56042/jsir.v82i05.1092