Analysis on Present Mathematical Model for Predicting the Crop Production
Neetu Sharma1, Saurabh Kumar2, Naveen Mani3
1Neetu Sharma*, Research Scholar, Department of Mathematics, Sandip University, Nashik, Maharashtra, India.
2Saurabh Kumar, FPM, EDII, Ahmedabad, Gujrat, India.
3Naveen Mani, Assistant Professor, Department of Mathematics, Sandip University, Nashik, Maharashtra, India.
Manuscript received on September 11, 2020. | Revised Manuscript received on September 23, 2020. | Manuscript published on October 10, 2020. | PP: 168-170 | Volume-9 Issue-12, October 2020 | Retrieval Number: 100.1/ijitee.L79461091220 | DOI: 10.35940/ijitee.L7946.1091220
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Abstract: India is a worldwide agriculture business powerhouse. Future of agriculture-based products depends on the crop production. A mathematical model might be characterized as a lot of equations that speak to the conduct of a framework. By using mathematical model in agriculture field, we can predict the production of crop in particular area. There are various factors affecting crops such as Rainfall, GHG Emissions, Temperature, Urbanization, climate, humidity etc. A mathematical model is a simplified representation of a real-world system. It forms the system using mathematical principles in the form of a condition or a set of conditions. Suppose we need to increase the crop production, at that time the mathematical model plays a major role and our work can be easier, more significant by using the mathematical model. Through the mathematical model we predict the crop production in upcoming years. .AI, ML, IOT play a major role to predict the future of agriculture, but without mathematical models it is not possible to predict crop production accurately. To solve the real-world agriculture problem, mathematical models play a major role for accurate results. Correlation Analysis, Multiple Regression analysis and fuzzy logic simulation standards have been utilized for building a grain production benefit depending model from crop production. Prediction of crop is beneficiary to the farmer to analyze the crop management. By using the present agriculture data set which is available on the government website, we can build a mathematical model.
Keywords: Crop Production Prediction, Mathematical Model, Regression Analysis, Fuzzy Logic Model.
Scope of the Article: Fuzzy Logics