Focalization of stages for the evaluation of illnesses they fall in the sustainability of foods
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Abstract
Scenario targeting deploys an orderly process to create a set of possible narratives that describe potential developments in key areas under conditions of uncertainty, often accompanied by graphics. It helps to explore ranges of credible and possible futures. The content of the scenario is based on selected variables and their interaction, and the scenario is defined in terms of these key factors or descriptors. In this sense, the objective pursued is to develop a proposal to apply scenario analysis in the study of the most prevalent livestock diseases that affect the sustainability of food in Cuba in the face of climate change. The key factors used are the number of animals susceptible to diseases that prevail against high levels of average relative humidity, high average temperature of the day, as climatic variables and the total number of sick animals at the end of the disease evolution period. For each scenario, 3 functions are built to show a possible behavior of the disease under study. The process for building the functions is based on artificial intelligence techniques, such as fuzzy sets and metaheuristics. The constructed scenarios show agreement with other mathematical and computational models developed for the national case, which is important because in a modeling under uncertainty conditions, such as this one, the coincidence of models based on focus different is positive and can give more security to lean it takes of decisions.
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