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Full-Text Articles in Hydraulic Engineering
Development Of Artificial Intelligence Approach To Nowcasting And Forecasting Vibrio Prevalence In Coastal Waters, Peyman Hosseinzadeh Namadi
Development Of Artificial Intelligence Approach To Nowcasting And Forecasting Vibrio Prevalence In Coastal Waters, Peyman Hosseinzadeh Namadi
LSU Doctoral Dissertations
Vibrio parahaemolyticus (V.p) is an epidemiologically significant pathogen that poses high risks to the human health and shellfish industry, calling for predictive models for management interventions. This study presents an Artificial Intelligence(AI)-based approach to predicting and reducing the risks. The AI-based approach involves the identification of environmental indicators and their optimum variation ranges favoring V.p prevalence, the development of nowcasting and forecasting models for predicting V.p prevalence, and the creation of remote sensing algorithms for mapping concentrations of V.p and its environmental indicators by synergistically combining the Deep Neural Network (DNN) modeling technique, Genetic Programming (GP) method, R …
Development Of Artificial Intelligence Approach To Nowcasting And Forecasting Oyster Norovirus Outbreaks Along The U.S. Gulf Coast, Shima Shamkhali Chenar
Development Of Artificial Intelligence Approach To Nowcasting And Forecasting Oyster Norovirus Outbreaks Along The U.S. Gulf Coast, Shima Shamkhali Chenar
LSU Doctoral Dissertations
Oyster norovirus outbreaks pose increasing risks to human health and seafood industry worldwide. This study presents an Artificial Intelligence (AI)-based approach to identifying the primary cause of oyster norovirus outbreaks, nowcasting and forecasting the growing risk of oyster norovirus outbreaks in coastal waters. AI models were developed using Artificial Neural Networks (ANNs) and Genetic Programming (GP) methods and time series of epidemiological and environmental data. Input variable selection techniques, including Random Forests (RF) and Forwards Binary Logistic Regression (FBLR), were used to identify the significant model input variables among six independent environmental predictors including water temperature, solar radiation, gage height, …