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Comparative Study of Forecasting Model for Price Prediction of Rice

  • Kesari VermaEmail author
  • N. K. Nagwani
  • Shrish Verma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 904)

Abstract

In this paper, we reviewed different forecasting models and proposed a neural network-based regression model for forecasting model price of rice. This study aims to prepare a neural network model that uses some of the existing data as feature and treat some data for defining target value. We also performed experimental evaluation of various forecasting models in real data of rice using time series data (price) of rice of India from 2001 to 2012. The algorithms are evaluated based on evaluation measures such as mean error (ME), root mean square error (MSE), mean absolute error (MAE), mean percentage error (MPE), mean absolute percentage error (MAPE) and mean absolute square error (MASE).

Keywords

Data mining Regression model Neural network model Forecasting price of rice 

Notes

Acknowledgements

This work is supported by Chhattisgarh Council of Science & Technology (CCOST), Raipur, Chhattisgarh under the grant No. 8057/CCOST/MRP/13, Raipur, dated 27.12.2013 and project titled, “Predictive and Visual Analysis of Price Distribution Information of Rice and Wheat across India”. We thank National Institute of Technology Raipur for providing necessary infrastructure and time to carry this research work.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer ApplicationsNational Institute of TechnologyRaipurIndia
  2. 2.Department of Computer Science & EngineeringNational Institute of TechnologyRaipurIndia
  3. 3.Department of ElectronicsNational Institute of TechnologyRaipurIndia

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