Model for Agricultural Production in Colombia Using a Neuro-Fuzzy Inference System

As mentioned by the Food and Agriculture Organization of the United Nations, agriculture has a primary role in food security. Given the advantageous conditions that Colombia has as a biodiverse country, creating and implementing sustainable and comprehensive agricultural systems is essential to generate agricultural decision-making tools. Therefore, this paper displays the design and deployment (training–validation) of a neuro-fuzzy model for the relevant agricultural production in Colombia. Four different configurations are proposed according to the data collected and the variables identified. The results show that a remarkable prediction of the models (configurations) is achieved by using training and validation data.