首页|Researchers' Work from Zhengzhou University Focuses on Machine Learning (Optimiz ing Hybrid Fibre-reinforced Polymer Bars Design: a Machine Learning Approach)
Researchers' Work from Zhengzhou University Focuses on Machine Learning (Optimiz ing Hybrid Fibre-reinforced Polymer Bars Design: a Machine Learning Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting originating from Zhengzhou, People's Rep ublic of China, by NewsRx correspondents, research stated, "Fiber-reinforced pol ymer (FRP) bars are gaining popularity as an alternative to steel reinforcement due to their advantages such as corrosion resistance and high strength-to-weight ratio. However, FRP has a lower modulus of elasticity compared to steel." Financial support for this research came from Zhengzhou University. Our news editors obtained a quote from the research from Zhengzhou University, " Therefore, special attention is required in structural design to address deflect ion related issues and ensure ductile failure. This research explores the use of machine learning algorithms such as gene expression programming (GEP) to develo p a simple and effective equation for predicting the elastic modulus of hybrid f iber-reinforced polymer (HFPR) bars. A comprehensive database of 125 experimenta l results of HFPR bars was used for training and validation. Statistical paramet ers such as R2, MAE, RRSE, and RMSE are used to judge the accuracy of the develo ped model. Also, parametric analysis and SHAP analysis have been carried out to reveal the most influential factors in the predictive model. Finally, the propos ed model was compared to the available equations for elastic modulus. The result s demonstrate that the developed GEP model performance is better than that of th e traditional formula. Statistical parameters and K-fold cross-validation ensure d the accuracy and reliability of the predictive model."
ZhengzhouPeople's Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningZhengzhou University
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