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Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India.

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Title Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India.
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Creator Md. Yeasin
Pramod Kumar
Prabhakar Kumar
M. Balasubramanian
H. S. Roy
A. K. Paul
Ajit Gupta
 
Subject Price forecasting
agricultural commodities
Generalized Neural Network
 
Description Not Available
Price forecasting of perishable crop like vegetables has importance implications to the farmers, traders as well as consumers. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. The farmers can use the information to make choices around the timing of marketing. For forecasting price of agricultural commodities, several statistical models have been applied in past but those models have their own limitations in terms of assumptions.
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Date 2022-08-02T15:46:08Z
2022-08-02T15:46:08Z
2022-07-06
 
Type Research Paper
 
Identifier Paul RK, Yeasin M, Kumar P, Kumar P, Balasubramanian M, Roy HS, et al. (2022) Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India. PLoS ONE 17(7): e0270553. https://doi.org/10.1371/journal.pone.0270553
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http://krishi.icar.gov.in/jspui/handle/123456789/73674
 
Language English
 
Relation Not Available;
 
Publisher Not Available