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Agricultural Price Forecasting Based on Variational Mode Decomposition and Time-Delay Neural Network

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Title Agricultural Price Forecasting Based on Variational Mode Decomposition and Time-Delay Neural Network
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Creator Kapil Choudhary
Girish K. Jha
Ronit Jaiswal
P. Venkatesh
Rajender Parsad
 
Subject Agricultural price forecasting
Empirical mode decomposition
Intrinsic mode function
Time-delay neural network
Variational mode decomposition
 
Description Not Available
Agricultural commodities prices are very unpredictable and complex, and thus, forecasting these prices is one of the research hotspots. In this paper, we propose a new hybrid VMD-TDNN model combining variational mode decomposition (VMD) and time-delay neural network (TDNN) to improve the accuracy of agricultural price forecasting. Specifically, the VMD decomposes a price series into a set of intrinsic mode functions (IMFs), and the obtained IMFs are modelled and forecasted separately using the TDNN models. Finally, the forecasts of all IMFs are combined to provide an ensemble output for the price series. VMD overcomes the limitation of the mode mixing and end effect problems of the empirical mode
decomposition (EMD) based variants. The prediction ability of the proposed model is compared with TDNN, and EMD based variants coupled with TDNN model using international monthly price series of maize, palm oil, and soybean in terms of evaluation criteria like root mean squared error, mean absolute percentage error and, directional prediction statistics. Additionally, Diebold-Mariano test and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a ranking system, are used to evaluate the accuracy of the models. The empirical results confirm that the proposed hybrid model is superior in terms of evaluation criteria and improves the prediction accuracy significantly.
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Date 2023-11-30T07:11:46Z
2023-11-30T07:11:46Z
2023-11-28
 
Type Research Paper
 
Identifier Kapil Choudhary, Girish K. Jha, Ronit Jaiswal, P. Venkatesh and Rajender Parsad (2023). Agricultural Price Forecasting Based on Variational Mode Decomposition and Time-Delay Neural Network. Statistics and Applications, 21(2), 237-259. https://ssca.org.in/media/14_SA44052022_R3_SA_21032023_Girish_Jha_FINAL_Finally.pdf
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http://krishi.icar.gov.in/jspui/handle/123456789/80951
 
Language English
 
Relation Not Available;
 
Publisher Statistics and Applications, Society of Statistics and Computer Applications