CLASSIFICATION OF MEDICINAL PLANTS WITH LEAVES SUITABLE FOR CONSUMPTION IN INFUSIONS WITH THE HELP OF THE 2-TUPLE MODEL

Abstract

The lack of knowledge of recurrent diseases, the preventive specificity of plants and the presence of heavy metals such as cadmium (Cd) and lead (Pb) in the leaves are factors that limit the use of medicinal plants in the infusion industry. In this context, the objective of this article is to classify the leaves of medicinal plants suitable for preventing or treating recurrent diseases. The Regional Health Directorate provided six recurrent diseases of the Ucayali Region. Through a survey, the herbs, shrubs and trees that the population uses in the treatment of each disease were recognized. The respondents are generally people with an empirical knowledge of the properties of plants, that is why the survey should be as simple and affordable as possible so that they can answer it effectively. One method that has become important within Computing with Words is the 2-tuple model. It combines the use of linguistic scales with the accuracy of a numerical value. Computing with Words is part of Artificial Intelligence and has as its object the use of words instead of numbers to classify. Because the use of natural language is part of the daily practice of all human beings, this method is relevant to aggregate the survey results.