Expert System to Predict the Harvest of Dry Starchy Corn
- Daysi Manco-Yupari(corresponding author),
- Keyla Vargas-Huertas,
- Universidad Científica del Sur,
Publication Information
Output type
Original language
EnglishPages from-to (Number of pages)
Pages 1609-1614 (6 pages)Publication milestones
- Published - 2024
Publication status
Publisher
Institute of Electrical and Electronics Engineers Inc.Publication series
- Publication series name: 3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024 - Proceedings
ISBN (Electronic)
9798331532420Publication IDs
- Scopus: 85217358634
Host publication title
3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024 - ProceedingsAbstract
Peru has been considered a producer of dry starchy corn for many years, thanks to its location in the Andes of South America, the district of Pariahuanca has been one of the communities with the highest production. In recent years, there has been a low production of dry starchy corn, causing economic losses. These changes are due to climatic factors and lack of technical knowledge on the part of farmers. The present work has the objective of analyzing how the expert system helps in the prediction of dry starchy corn harvest, it is analyzed through the study of the conditions present in 5 farms, working with 52 characteristics that describe the behavior of the corn harvest. The results demonstrated the identification of the 52 critical harvest factors, as well as the design and operation of the expert system, through the implementation of a neural network, achieving a sensitivity (73.3%) and specificity (80%). It is concluded that the expert system helps to improve the prediction of the harvest of dry starchy corn, with which farmers can make the best decisions with the suggested recommendations.
Sustainable Development Goals
- SDG 7 Affordable and Clean Energy
