Rainfall based Crop Production Identification by using Different Algorithm Technique

Rohan Pawar; Isha Bhalchandra; Yashraj Singh; Prashobh Praveen; Prof Asmita Kalamkar

Rainfall based Crop Production Identification by using Different Algorithm Technique

Author(s)	Rohan Pawar, Isha Bhalchandra, Yashraj Singh, Prashobh Praveen, Prof Asmita Kalamkar
Country	-
Abstract	Rainfall depends on various factors such as temperature, humidity, cloudiness, wind speed, etc. Rainfall prediction is a major concern for many fields like the meteorological department, agriculture department, etc which is directly associated with the economy and sustenance of human life. In the proposed system we are going to predict the rainfall and after this prediction, estimate the yield, solutions for fertilizing or growing alternative crops. A further step in the process also consists of finding out if the crop has certain kind of disease or not. Agriculture study is growing rapidly, due to innovation in technologies and upcoming challenges. It has been proven to play a crucial role in improving the overall growth rate of any country. Agriculture matters a lot in economic growth. Very wide work is going on from several years to improve productivity by using data mining & evolutionary techniques. The losses incurred in crop production are a large issue for agriculture as they come in the way of sufficient produce. There is a very limited analysis performed on the loss of crops, due to the changing environmental conditions. The correct prediction of loss in crops helps the farmer to apply suitable actions to overcome these issues and maintain the expected production. As agriculture matters a lot in economic growth, to overcome this issue, we have used the data mining approach i.e classification. The objective of the system is to calculate the produce of a particular crop, based on the rainfall patterns. Data mining techniques help in agriculture for the exclusion of manual jobs and for decision making which enables to decrease the production cost and improve productivity.
Keywords	Crop, Classification, Naïve Bayes, KNN, RF
Field	Engineering
Published In	Volume 2, Issue 3, May-June 2020
Published On	2020-06-12
Cite This	Rainfall based Crop Production Identification by using Different Algorithm Technique - Rohan Pawar, Isha Bhalchandra, Yashraj Singh, Prashobh Praveen, Prof Asmita Kalamkar - IJFMR Volume 2, Issue 3, May-June 2020.

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Rainfall based Crop Production Identification by using Different Algorithm Technique

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