Estudio comparativo de las técnicas de inteligencia artificial para el diagnóstico de enfermedades en la agricultura

Abstract

The diagnostic process using complementary criteria and methods is a very complex art applied to identifying the disease responsible for the condition or estimating the risk of complications. Diagnosis, both human, animal and plant, is a task that requires precision, given the importance that a wrong decision can have. Thanks to the development of information and communication technologies and the inexhaustible advances in information technology, phytosanitary diagnosis in agriculture is currently based on the applications of artificial intelligence, which it sees as a reference in several of its main techniques, as well as expert systems, fuzzy logic, neural networks, data mining.