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Abstract
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Article Information:
A Hybrid Fresh Apple Export Volume Forecasting Model Based on Time Series and Artificial Neural Network
Lihua Yang and Baolin Li
Corresponding Author: Baolin Li
Submitted: November 30, 2014
Accepted: January 8, 2015
Published: April 25, 2015 |
Abstract:
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Export volume forecasting of fresh fruits is a complex task due to the large number of factors affecting the demand. In order to guide the fruit growers’ sales, decreasing the cultivating cost and increasing their incomes, a hybrid fresh apple export volume forecasting model is proposed. Using the actual data of fresh apple export volume, the Seasonal Decomposition (SD) model of time series and Radial Basis Function (RBF) model of artificial neural network are built. The predictive results are compared among the three forecasting model based on the criterion of Mean Absolute Percentage Error (MAPE). The result indicates that the proposed combined forecasting model is effective because it can improve the prediction accuracy of fresh apple export volumes.
Key words: Artificial neural network, forecasting, fresh apple, time series, , ,
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Abstract
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Cite this Reference:
Lihua Yang and Baolin Li, . A Hybrid Fresh Apple Export Volume Forecasting Model Based on Time Series and Artificial Neural Network. Advance Journal of Food Science and Technology, (12): 966-970.
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ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
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