Forecasting Monthly Export Volume of Frozen White Shrimp with Hybrid Model of Holt and Support Vector Regression Emphasizing on Systematic Error Reduction
Keywords:
Export, White shrimp, Hybrid model, Error reduction, Support Vector RegressionAbstract
Frozen white shrimp export plays a significant role in agricultural commodities in Thailand. However, agriculturists still encounter high production costs, which affect export competitiveness of Thailand. More than 90% of total production cost is variable cost, which corresponds to volume of white shrimp cultivation. The appropriate forecast of future export quantity of white shrimp can be useful information to support critical decision making on production planning. In this research, a hybrid model of Holt and support vector regression is developed emphasizing on systematic error reduction to improve accuracy of forecast. Moreover, the hybrid model is compared to conventional models (i.e., ARIMA and Holt-Winters) based on five accuracy measures. The empirical results indicated that the hybrid model outperforms other forecasting models. Furthermore, the forecasting performance of hybrid model approximates to the forecasting performance in test data used in cross-validation, although some new hidden observations are used. Consequently, the hybrid model can be a useful tool to support decision making on production of white shrimp in Thailand.
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