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Developing an Integrated System Using Machine Learning Tools and Techniques in Enhancing the Effectiveness of Forecasting Crop Yields

Shourya Gupta

Delhi Public School, R.K. Puram, New Delhi

24-26

Vol: 12, Issue: 3, 2022

Receiving Date: 2022-05-29 Acceptance Date:

2022-07-25

Publication Date:

2022-08-04

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http://doi.org/10.37648/ijrst.v12i03.005

Abstract

As an agriculture based nation, India's monetary standing is dependent on it. Computation of this country's rural results is a significant test. Rural yield is impacted by Causes, including natural, financial, and occasional elements. Considering the ongoing populace circumstance, the individuals that develop these and comparative things incorporate. Because of the abruptness of the creation, it is very temperamental. Ecological factors, for example, climate and an absence of groundwater assets. The significant objective is to gather the information that can use to decide. Put away and investigated for crop yield expectations: Machine learning strategies for rural production forecast executed. This helps farmers in choosing the best products. Fitting yield, what's more, this study attempts to give an improvement in the realm of horticulture by further developing yield creation expectation precision. A measurable model is built utilizing AI procedures and great advancements to deliver clear and exact choices. The aftereffects of this exploration will help ranchers choose the best harvests to develop, given qualities like season and accessible land, with minimal chance.

Keywords: machine learning; agribusiness; Artificial intelligence

References

  1. Aruvansh Nigam, Saksham Garg, Archit Agrawal “Crop Yield Prediction using ML Algorithms”, 2019
  2. Gour Hari Santra, Debahuti Mishra and Subhadra Mishra, Applications of Machine Learning Techniques in Agricultural Crop Production, Indian Journal of Science and Technology, October 2016
  3. Ramesh Medar, Vijay S, Shweta, “Crop Yield Prediction using Machine Learning Techniques”, 2019
  4. Sangeeta, Shruthi G, “Design And Implementation Of Crop Yield Prediction Model In Agriculture”, 2020
  5. data.gov.in
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