Hybrid Soft Computing Analytics of Cardiorespiratory Morbidity and Mortality Risk Due to Air Pollution

Abstract

During the last decades, climate change has been contributing significantly to the increase of Ozone and Particulate Matter in major urban centers. This might result in additional enhancement of serious seasonal respiratory and cardiovascular diseases incidents. This research effort introduces an innovative hybrid approach that fuzzifies the involved features. The final target is the development of a Mamdani fuzzy inference system with weighted fuzzy rules. The system’s output comprises of the partial meteorological and air pollution risk indices per season. Fuzzy conjunction T-Norms have been employed to estimate the unified risk index. Moreover, the effect of one to seven days delay regarding high values of the above indices to the morbidity and mortality indicators in the prefecture of Thessaloniki has been studied. Hybrid Fuzzy Chi Square Test has been performed to identify the degree of dependences between the unified air pollution-meteorological risk indices and serious health even mortality cardiorespiratory problems.