Coastal environmental management by fuzzy system modeling

Environmental data often need to be analyzed in order to obtain information necessary for environmental management decision. The main task today is to shift what is natural and atrophic variability and the assessment of trophic status to forecast the future ecosystem behavior. Sometimes it is necessary to use the data to build a model of the environmental processes that we want to manage. In other cases, we must identify and understand the interrelationships of different physical, chemical and biological parameters. The case studied is the algal community growth in coastal upwelling area of Cabo Frio Island at Rio de Janeiro state, southeastern of Brazil as a bioindicator since this place is becoming a operational support base of a oil drilling companies. We used a machine learning approach to elicit regularities/dependences that include both numerical and logical conditions.