Predicting the price of Vietnamese shrimp products exported to the US market using machine learning

Khiem, Nguyen Minh; Takahashi, Yuki; Dong, Khuu Thi Phuong; Yasuma, Hiroki; Kimura, Nobuo

doi:10.1007/s12562-021-01498-6

Cited by 11 publications

(9 citation statements)

References 24 publications

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“…This work enhanced the previous predictions presented by [ 33 ]. A high accuracy and stable prediction were obtained using the super learner, which outperformed the single approaches of the random forest and gradient boosting.…”

Section: Discussionsupporting

confidence: 88%

“…The combination of candidate algorithms makes the ensemble model powerful, overcoming the dependence of each algorithm on the dataset. This work enhanced the previous predictions presented by [33]. A high accuracy and stable prediction were obtained using the super learner, which outperformed the single approaches of the random forest and gradient boosting.…”

Section: Discussionsupporting

confidence: 60%

“…Due to the super learner being developed using a stacked generalization technique, it uses a new model to combine the predictions from multiple candidate models that are already trained. To predict the accuracy of Vietnamese export prices, random forest and gradient boosting were selected as the best single machine learning approaches [ 33 ]. Therefore, these two algorithms were first chosen for use in the super learner.…”

Section: Methodsmentioning

confidence: 99%

“…To interpret the prediction, SHAP was used to determine how each predictor influenced the export price and then suggested solutions for the development of the Vietnamese shrimp industry. This study provided a new approach to make accurate Vietnamese price predictions based on information from competitors rather than the use of information solely from Vietnam, as in previous research [ 33 ]. It also provided a method to interpret the predicted result.…”

Section: Introductionmentioning

confidence: 99%

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A novel machine learning approach to predict the export price of seafood products based on competitive information: The case of the export of Vietnamese shrimp to the US market

et al. 2022

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Predicting the export price of shrimp is important for Vietnam’s fisheries. It not only promotes product quality but also helps policy makers determine strategies to develop the national shrimp industry. Competition in global markets is considered to be an important factor, one that significantly influences price. In this study, we predicted trends in the export price of Vietnamese shrimp based on competitive information from six leading exporters (China, India, Indonesia, Thailand, Ecuador, and Chile) who, alongside Vietnam, also export shrimp to the US. The prediction was based on a dataset collected from the US Department of Agriculture (USDA), the Food and Agriculture Organization of the United Nations (FAO), and the World Trade Organization (WTO) (May-1995 to May-2019) that included price, required farming certificates, and disease outbreak data. A super learner technique, which combined 10 single algorithms, was used to make predictions in selected base periods (3, 6, 9, and 12 months). It was found that the super learner obtained results in all base periods that were more accurate and stable than any candidate algorithms. The impacts of variables in the predictive model were interpreted by a SHapley Additive exPlanations (SHAP) analysis to determine their influence on the price of Vietnamese exports. The price of Indian, Thai, and Chinese exports highlighted the advantages of being a World Trade Organization member and the disadvantages of the prevalence of shrimp disease in Vietnam, which has had a significant impact on the Vietnamese shrimp export price.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 60%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel machine learning approach to predict the export price of seafood products based on competitive information: The case of the export of Vietnamese shrimp to the US market

et al. 2022

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“…Minh Khiem et al (2021) developed a model that predicts the price of shrimp products exported from Vietnam to the USA using ML algorithms. A data set covering the years 1995-2019 was used in the study.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting of Export Volume Using Artificial Intelligence Based Algorithms

Özden

2022

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

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Technological breakthroughs have transformed communication and taken transportation, health, and commerce to an unprecedented level. In this way, sudden developments have rapidly affected all countries. In this context, analysis methods are changing compared to the past, and annual analyses fail to catch the trend even for macroeconomic indicators. In this paper, new artificial intelligence-based estimation methods were used to see the future trend of export volume, and their estimation performances were compared by adding them to the classical econometric method. Historical quarterly data from 2013 to 2021 were used in the training and testing phases of the models. For this purpose, the variables of gross domestic product, foreign direct investment, and dollar exchange rate, which affect the export volume, were determined as inputs in estimating the export volume. According to the analysis results, support vector machine model for predicting export volume in Turkey. This study can provide an essential basis for policymakers to export estimation and formulate their export-enhancing policies effectively.

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Risks and adaptation dynamics in shrimp and prawn-based farming systems in southwest coastal Bangladesh

et al. 2023

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Predicting the price of Vietnamese shrimp products exported to the US market using machine learning

Cited by 11 publications

References 24 publications

A novel machine learning approach to predict the export price of seafood products based on competitive information: The case of the export of Vietnamese shrimp to the US market

A novel machine learning approach to predict the export price of seafood products based on competitive information: The case of the export of Vietnamese shrimp to the US market

Forecasting of Export Volume Using Artificial Intelligence Based Algorithms

Risks and adaptation dynamics in shrimp and prawn-based farming systems in southwest coastal Bangladesh

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