An Innovative Approach Involves Machine Learning Algorithms to Forecast Future Farmer Revenue

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 8

Year of Publication : 2024

Authors : Saikat Banerjee, Abhoy Chand Mondal

10.14445/23488379/IJEEE-V11I8P106

How to Cite?

Saikat Banerjee, Abhoy Chand Mondal, "An Innovative Approach Involves Machine Learning Algorithms to Forecast Future Farmer Revenue," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 8, pp. 59-71, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I8P106

Abstract:

Agriculture is crucial for meeting essential human needs and creating job opportunities worldwide. Agriculture provides many jobs and is essential to the economy in emerging countries like India. At this very moment, the features of weather patterns are experiencing unexpected changes due to increased pollution, climate change, and urbanization. The weather has a significant effect on how crops develop and grow. Precipitation, temperature swings, atmospheric moisture content, wind speed, and direction are some of the most essential local climatic factors that determine the success or failure of agricultural cultivation. Machine learning is a cutting-edge innovation that can solve real-world problems. Machine learning is a technique that allows computers to mimic human intelligence by learning from experience and analyzing various data sets. At this time, machine learning techniques are being used a lot in the agricultural sector. Using climatic data to predict crop yields, farmers may increase agricultural production, grow various crops, and use machine learning algorithms better. This research focuses on crop forecasting using weather data, including air temperature, humidity, rainfall, and sunshine hours. The suggested model predicts the maximum income in crops using change system agriculture. This paper proposes an intelligent agricultural system that uses machine learning to help farmers increase their income.

Keywords:

Crop, Machine Learning (ML), Economy, Minimum Support Price (MSP), Naïve Bayes (NB).

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