Modeling and forecasting of nanofecu treated sewage quality using recurrent neural network (rnn)

HIGHLIGHTS

• who: Dingding Cao and collaborators from the Centre for Water Research, Faculty of Engineering and the Built Environment, SEGi University, Petaling Jaya, Malaysia have published the research work: Modeling and Forecasting of nanoFeCu Treated Sewage Quality Using Recurrent Neural Network (RNN), in the Journal: Computation 2023, 11, 39. of /2023/
• what: The aim of this work is to develop a recurrent neural network (RNN) model to estimate the performance of immobilized nanoFeCu in sewage treatment thereby easing the monitoring and forecasting of sewage quality. In this work sewage data was collected from a local sewage . . .
  

   

  

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