A bootstrap aggregation approach for adequate crop fertilizer and nutrition recommendation
نویسندگان
چکیده
Agriculture is the <span>largest workforce of India and biggest contributor to Indian economy. Improving agricultural practices with help modern computer science technologies have great scope. Helping farmers know about their soil fertility, crops which can be grown fertilizers or nutrients required for land will valuable inputs them. Too much too little may harm soil, so right amount fertilization also important. In this paper we discussed bootstrap aggregation regression method, an ensemble machine learning technique recommend optimum level fertilizers. Hence customized recommendation reports could generated suggest adequate quantities. This really beneficial maintain health helpful better crop growth yield. We consider features levels parameters such as nitrogen, phosphorus, potassium (NPK), pH level, organic carbon, electric conductivity, humidity, rainfall other micro predicting nutrients. checked methods compare results based on previous work done in same field.</span>
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ژورنال
عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2022
ISSN: ['2502-4752', '2502-4760']
DOI: https://doi.org/10.11591/ijeecs.v26.i3.pp1773-1780