2023
DOI: 10.1061/joeedu.eeeng-6986
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Predicting Fecal-Indicator Organisms in Coastal Waters Using a Complex Nonlinear Artificial Intelligence Model

Abstract: High levels of faecal indicator organisms (FIOs) at bathing water sites can cause disease and impose threats to public health. There is a need for predicting FIO levels to inform the public and reduce exposure. Data-driven models are one of the main tools being considered as predictive models. However, identifying the main inputs of the data-driven models is a major challenge in developing FIO predictor models. This paper develops a data-driven model for FIO concentration prediction based on a limited number o… Show more

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