Abstract
Cow husbandry is one of the main agricultural development sectors in many countries. However, cow diseases problem results in low productivity and restricts the development of this kind of agriculture. Raisers highly depends on a veterinarian to cope with cow disease issues. Unfortunately, there is a lack of veterinarians to serve this sector demands. Therefore, it is necessary to develop innovative solutions focused on solving problems such as the cow disease diagnosis. This work proposes an expert system for cow disease diagnosis. This system allows diagnosing a cow disease based on a set of symptoms provided by the user. For this purpose, the proposed system relies on a set of SWRL-based rules that represent expert knowledge on cow diseases. Our proposal was evaluated by real users from the cow husbandry domain. In this evaluation, the system had to diagnose a cow disease based on a set of symptoms provided by users. The system got promising evaluation results based on the accuracy metric.
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Alarcón-Salvatierra, A., Bazán-Vera, W., Espinoza-Moran, W., Arcos-Jácome, D., Burgos-Herreria, T. (2019). A Rule-Based Expert System for Cow Disease Diagnosis. In: Valencia-García, R., Alcaraz-Mármol, G., Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) ICT for Agriculture and Environment. CITAMA2019 2019. Advances in Intelligent Systems and Computing, vol 901. Springer, Cham. https://doi.org/10.1007/978-3-030-10728-4_4
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DOI: https://doi.org/10.1007/978-3-030-10728-4_4
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