APLICAÇÃO DE REDES NEURAIS ARTIFICIAIS NA CONSTRUÇÃO DE MODELOS DE FRAGILIDADE AMBIENTAL

Abstract

This paper deals with the challenge in modeling environmental fragility, which implies not only the understanding of the intrinsic and dynamic relationship between the physical, biotic and socio-economic components of environmental systems, but also in trying to translate this knowledge in mathematical models. In order to shed some light on this difficulty, the results generated by two empirical  models of environmental fragility were presented and compared, models that are widely used (CREPANI et al. 2001 and ROSS, 1994). These two models were applied in two thesis-areas with very diverging results. Within this context of uncertainties, this paper tested the feasibility and reliability of a new tool that can be applied in the elaboration of environmental fragility models, the artificial neural networks. For that, were used the knowledge and experience of specialists in this area. The results proved that it is possible to emulate, with reasonable reliability, the evaluation pattern of specialists in the definition of environmental systems fragility, eliminating in this way, the arbitrariness and subjectivity in the elaboration process of environmental fragility models. This work does not present a new model, but rather a methodology for the construction of models using artificial neural networks, taking the first step in the search of new techniques, sometimes feared by the geographers, however necessary for the evolution of the geographic science.