Predicción Del Precio De Maíz en México

García, María del Rosario López; Damián, Miguel Ángel Martínez; Coronado, José Jaime Arana

doi:10.47163/agrociencia.v55i8.2665

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…que fueron ex colonias de Francia; existiendo convenios que facilitan el ingreso de la fruta con menor aranceles. Fuente: García-Mata, González-Machorro, García-Sánchez & Mora-Flores (2013).…”

Section: Introductionunclassified

Análisis de rentabilidad económica del plátano (Musa balbisiana AAB Simmond) en el sitio Río Negro, provincia El Oro

Ordoñez,

Vite Cevallos,

Barrezueta-Unda

2019

REMCA

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For Ecuador, bananas represent an important export item and a fundamental crop in the country's food security. In this context, the present investigation proposes: to elaborate a financial analysis by means of a flow of cash and the obtaining of indicators that allow to determine if it is profitable the culture of banana in the site Rio Negro, in the province El Oro (Ecuador). For this purpose, an expost evaluation of a banana plantation of 3.66 ha was carried out. The values taken for the financial analysis were from the local market and several indicators of solidity and indebtedness were estimated, which were obtained from the general balance of the project. A 5-year cash flow was elaborated and the financial viability was projected in three scenarios (optimal, favorable, unfavorable), for this purpose NPV, IRR and IRRM were used. The indicators of solidity, working capital, current ratio and acid test were positive in spite of the fact that current assets have decreased in the last three years. The three proposed scenarios obtained positive NPV, IRR and IRRM values greater than the interest used. These results indicate that the project is viable in the Rio Negro sector.

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Section: Introductionunclassified

Análisis de rentabilidad económica del plátano (Musa balbisiana AAB Simmond) en el sitio Río Negro, provincia El Oro

Ordoñez,

Vite Cevallos,

Barrezueta-Unda

2019

REMCA

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Application of ARIMA Model to Forecast Corn Prices in Mexico

Guzma´n-Anaya

2024

SetP

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Corn is an essential grain in the Mexican culinary, cultural and social heritage. However, the volatility in corn prices brings uncertainty to agricultural farmers and has caused an increase in imports of the grain from other countries. The purpose of this study is to use time-series models regularly applied in finance to an agricultural commodity and forecast corn prices in Mexico. The study employs autoregressive integrated moving average (ARIMA) models to forecast prices in 2024 and 2025 using data on average rural prices of grain corn from the period 1980 to 2023 The results contribute to a theoretical discussion on employing statistical tools to reduce market uncertainty on agricultural commodities and provide empirical practical results on corn prices for decision making. The results are innovative in using the ARIMA statistical tool to analyze a specific commodity (corn) in a specific market (Mexico). The conclusions of the study suggest an upward trend in corn prices for 2024 and 2025, however, price stagnation and uncertainty is observed. Although government policies have introduced price guarantees for corn in Mexico, they only cover less than 3% of total production. Future studies should analyze price divergence by regions or states in Mexico.

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Cloud-based configurable data stream processing architecture in rural economic development

Chen,

Al-Turjman

2024

PeerJ Computer Science

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Purpose This study aims to address the limitations of traditional data processing methods in predicting agricultural product prices, which is essential for advancing rural informatization to enhance agricultural efficiency and support rural economic growth. Methodology The RL-CNN-GRU framework combines reinforcement learning (RL), convolutional neural network (CNN), and gated recurrent unit (GRU) to improve agricultural price predictions using multidimensional time series data, including historical prices, weather, soil conditions, and other influencing factors. Initially, the model employs a 1D-CNN for feature extraction, followed by GRUs to capture temporal patterns in the data. Reinforcement learning further optimizes the model, enhancing the analysis and accuracy of multidimensional data inputs for more reliable price predictions. Results Testing on public and proprietary datasets shows that the RL-CNN-GRU framework significantly outperforms traditional models in predicting prices, with lower mean squared error (MSE) and mean absolute error (MAE) metrics. Conclusion The RL-CNN-GRU framework contributes to rural informatization by offering a more accurate prediction tool, thereby supporting improved decision-making in agricultural processes and fostering rural economic development.

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Predicción Del Precio De Maíz en México

Cited by 3 publications

References 7 publications

Análisis de rentabilidad económica del plátano (Musa balbisiana AAB Simmond) en el sitio Río Negro, provincia El Oro

Análisis de rentabilidad económica del plátano (Musa balbisiana AAB Simmond) en el sitio Río Negro, provincia El Oro

Application of ARIMA Model to Forecast Corn Prices in Mexico

Cloud-based configurable data stream processing architecture in rural economic development

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