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Enhancing crop yield prediction through machine learning regression analysis

S. Sharma, Anupriya Jain, Sachin Sharma, Pawan Whig

2024International Journal of Sustainable Agricultural Management and Informatics38 citationsDOIOpen Access PDF

Abstract

The economic prosperity of any nation hinges significantly on its agricultural output, a cornerstone of sustained growth.The integration of advanced technology plays a pivotal role in enhancing agricultural productivity.Farmers today are leveraging breakthroughs in data mining, the internet of things (IoT), artificial intelligence (AI), and machine learning to optimise their practices.This paper is dedicated to the exploration of this transformative field, offering insights into its multifaceted applications.It delves into the assessment of diverse parameters to facilitate the cultivation of specific crops in a given region.Moreover, it collaborates closely with farmers, tailoring these parameters to maximise crop yields and diversify agricultural produce.The study also incorporates the deployment of AI algorithms, such as logistic regression and multiple regressions, to bolster decision-making processes in agriculture.

Topics & Concepts

Machine learningYield (engineering)Regression analysisComputer scienceRegressionArtificial intelligenceStatisticsAgricultural engineeringMathematicsEngineeringMaterials scienceMetallurgySmart Agriculture and AI
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