Prediction and Analysis of Soil properties in Guntur District, Andhra Pradesh
D.Venkata Revanth Naidu1, Sridevi Sakhamuri2, A.Venkat Vardhan3
1D.Venkata Revanth Naidu, Department of Electronics and Computer Engineering, Koneru Lakshmaih Education Foundation, Vaddeswaram, AP, India.
2Sridevi Sakhamuri, Department of Electronics and Computer Engineering, Koneru Lakshmaih Education Foundation, Vaddeswaram, AP, India.
3A.Venkat Vardhan, Department of Electronics and Computer Engineering, Koneru Lakshmaih Education Foundation, Vaddeswaram, AP, India.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 10511-10514 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4411118419/2019©BEIESP | DOI: 10.35940/ijrte.D4411.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A significant statistical analysis is done over Eleven Thousand and Two hundred soil data samples of thirteen villages in Guntur District of Andhra Pradesh. Useful relationship among major soil parameters was found. An analytical approach is used to assess the properties of the soil using pandas, numpy and matplotlib libraries in python. Hidden patterns among the soil properties are identified. By using Random Forest Regressor soil data of Guntur district is predicted with considerably higher accuracy.
Keywords: Soil Nutrients, Optimum Fertilization Rate, Yield quality, Random Forest Regressor.
Scope of the Article: Regression and Prediction.