Analysis and Estimation of Crop Yield Using DBSCAN Algorithm

Authors

  • Latha G  B.E Students, Department of ISE, New Horizon College of Engineering, Bangalore, Karnataka, India
  • Anusha S  B.E Students, Department of ISE, New Horizon College of Engineering, Bangalore, Karnataka, India
  • Vikas B O  Assistant Professor, Department of ISE, New Horizon College of Engineering, Bangalore, Karnataka, India

Keywords:

Clustering, DBSCAN, Linear Regression, Agricultural data

Abstract

Agriculture field requires farmers and agriculture businesses to take critical decisions every day and also overcome the complexity and factors that they influence. Approach for accomplishing practical and effective solutions for this problem. Agriculture has been an significant target for big data. The various factors such as production, rainfall, temperature, soil type, fertilizer used, influence the farmer to access information and to make critical farming decision. This paper focuses on the analysis of the agriculture data and finding optimal parameters to maximize the crop production using data mining techniques like DBSCAN and Multiple Linear Regression. The result is the yield estimation and this helps agribusinesses to make future business decisions.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-06-30

Issue

Volume 4, Issue 8, May-June-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Latha G, Anusha S, Vikas B O "Analysis and Estimation of Crop Yield Using DBSCAN Algorithm" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.265-269, May-June-2018.