Machine Learning Applied to Peruvian Vegetables Imports

• URL: http://arxiv.org/abs/2301.03587v1
• Date: Sun, 8 Jan 2023 21:05:31 GMT
• Title: Machine Learning Applied to Peruvian Vegetables Imports
• Authors: Hugo Ticona-Salluca, Fred Torres-Cruz, Ernesto Nayer Tumi-Figueroa
• Abstract summary: The forecast is made with data from the monthly record of imports of vegetable products from Peru, collected from the years 2021 to 2022. The model with better performance will be selected, evaluating the precision of the predicted values.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The current research work is being developed as a training and evaluation object. the performance of a predictive model to apply it to the imports of vegetable products into Peru using artificial intelligence algorithms, specifying for this study the Machine Learning models: LSTM and PROPHET. The forecast is made with data from the monthly record of imports of vegetable products(in kilograms) from Peru, collected from the years 2021 to 2022. As part of applying the training methodology for automatic learning algorithms, the exploration and construction of an appropriate dataset according to the parameters of a Time Series. Subsequently, the model with better performance will be selected, evaluating the precision of the predicted values so that they account for sufficient reliability to consider it a useful resource in the forecast of imports in Peru.

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