An improved prediction of high-performance concrete compressive strength using ensemble models and neural networks

HIGHLIGHTS

• What: The aim of this strategy is to create reliable and accurate predictive models for HPC compressive strength, which is a crucial variable for building engineering. The machine_learning models proposed in this study demonstrate their effectiveness as valuable tools for predicting the CS of HPC.
• Who: Umar Jibrin Muhammad from the (UNIVERSITY) have published the research work: An improved prediction of high-performance concrete compressive strength using ensemble models and neural networks, in the Journal: (JOURNAL)
• How: The authors employed Generalized Regression Neural Network (GRNN) Nonlinear AutoRegressive with exogenous inputs (NARX neural network . . .
  

   

  

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