首页|Study Findings from Zhejiang University of Technology Update Knowledge in Machin e Learning (Prediction of free chloride concentration in fly ash concrete by mac hine learning methods SVR, MLP and CNN)
Study Findings from Zhejiang University of Technology Update Knowledge in Machin e Learning (Prediction of free chloride concentration in fly ash concrete by mac hine learning methods SVR, MLP and CNN)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting from Hangzhou, People’s Republic of China, by NewsRx journalists, research stated, “Free chloride concen tration distribution is important for assessing the corrosion risk of steel bars in reinforced concrete structures under chloride environment.” Our news reporters obtained a quote from the research from Zhejiang University o f Technology: “In this study, a group of 3150 free chloride concentration data s ets were obtained. Afterwards, three machine learning methods, including Support Vector Regression (SVR), Multilayer Perceptron (MLP) and One- Dimensional Convol utional Neural Network (1D-CNN) were adopted to construct models to predict chlo ride concentration distribution. Results show that 1D-CNN and MLP models are bet ter at predicting the chloride concentration in fly ash concrete, whereas the pr ediction capability of SVR is relatively poor. Moreover, free chloride concentra tion prediction based on unmeasured parameters was conducted. Results show that the 1D-CNN and MLP models both have high prediction abilities, i.e., predicted r esults are consistent with experimental measurements, performing generally bette r than the time-varying model constructed based on Fick’s second law.”
Zhejiang University of TechnologyHangz houPeople’s Republic of ChinaAsiaAnionsChloridesCyborgsEmerging Tech nologiesHydrochloric AcidMachine Learning
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