Implementación de una red neuronal y un modelo de forrester para la predicción entre factores demográficos y agentes contaminantes.

The greatest problems that has been presented in the world, especially in Colombia, is due to an accelerated population growth generated by the overwhelming increase in migrant circulation or mobility of people due to other causes or eventual situations of nature. These social situations have been significantly affecting the urban order of cities, particularly due to the confinement of the population and the increase in environmental pollution that this increase brings, in addition to unhealthiness, poverty, among other factors. To study population growth based on demographic variables and environmental factors, an Artificial Neural Network was built to carry out a data analysis that incorporated related variables such as CO2 and other pollutants. The purpose was to identify the influence of these toxic agents with the growth of a population. Once the dynamic prediction was verified through the neural network, a mathematical model was built to study a specific case of demographic behavior for a certain Colombian region by means of a Forrester Diagram, where the migratory conditions, birth rate, morbidity, mortality, migratory flow (or mobility of people due to other natural events) and pollutants that affect human health mainly in respiratory diseases. The results delivered predictions and the Forrester Diagram confirming the relationship between toxic agents and demographic aspects. [ABSTRACT FROM AUTHOR]