AIMC Topic: Bays

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Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models.

Environmental pollution (Barking, Essex : 1987)
Hybrid artificial intelligence (AI) models are developed for sediment lead (Pb) prediction in two Bays (i.e., Bramble (BB) and Deception (DB)) stations, Australia. A feature selection (FS) algorithm called extreme gradient boosting (XGBoost) is propo...

Modelling the influence of environmental parameters over marine planktonic microbial communities using artificial neural networks.

The Science of the total environment
Guanabara Bay is a tropical estuarine ecosystem that receives massive anthropogenic impacts from the metropolitan region of Rio de Janeiro. This ecosystem suffers from an ongoing eutrophication process that has been shown to promote the emergence of ...

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

Marine pollution bulletin
The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Oce...

Improving real-time forecasting of bay water quality by integrating in-situ monitoring, machining learning, and process-based modeling.

Journal of environmental management
Frequent occurrences of disasters such as red tides significantly threaten bay ecosystems, making near real-time water quality forecasting crucial for disaster warning and decision-making. Conventional techniques, such as process-based modeling and i...