CROP RECOMMENDATION SYSTEM USING MACHINE LEARNING ALGORITHMS

Autor: Vaibhav Sharma, Sweety Bharti
Rok vydání: 2022
Předmět:
DOI: 10.5281/zenodo.6826905
Popis: In India agriculture holds an incredibly predominant position in the expansion of our country’s financial system. It is one of the fields which generates most of the employment opportunity in our country. Farmers, due to lack of their knowledge about different soil contents and environment conditions, do not opt the exact crop for nurturing, which results into a major hinder in crop production. To eliminate this barrier, we have provided a system which offers a scientific approach to assist farmers in predicting the ample crops to be cultivated based on different parameters which affects the overall production. It also suggests them about several deficiencies of nutrients in the soil to produce a specific crop. It is in context of a website. We used the crop dataset which include parameters like temperature, rainfall, pH, and humidity for specific crops and applied different ML techniques to recommend crops with high accuracy and efficiency. Hence, it can be supportive for farmers to be furthermore extra versatile.
Databáze: OpenAIRE