首页|Hunan University of Science and Engineering Researcher Discusses Research in Mac hine Learning (Compressive strength of wastederived cementitious composites usi ng machine learning)
Hunan University of Science and Engineering Researcher Discusses Research in Mac hine Learning (Compressive strength of wastederived cementitious composites usi ng machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news originating from Yongzhou, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Marble cement (MC) i s a new binding material for concrete, and the strength assessment of the result ing materials is the subject of this investigation.” Our news journalists obtained a quote from the research from Hunan University of Science and Engineering: “MC was tested in combination with rice husk ash (RHA) and fly ash (FA) to uncover its full potential. Machine learning (ML) algorithm s can help with the formulation of better MC-based concrete. ML models that coul d predict the compressive strength (CS) of MC-based concrete that contained FA a nd RHA were built. Gene expression programming (GEP) and multi-expression progra mming (MEP) were used to build these models. Additionally, models were evaluated by calculating R ~2 values, carrying out statistical tests, creating Taylor’s diagram, and comparin g theoretical and experimental readings. When comparing the MEP and GEP models, MEP yielded a slightly better-fitted model and better prediction performance (R ~2 = 0.96, mean absolute error = 0.646, root mean square error = 0.900, and Nash-S utcliffe efficiency = 0.960).”
Hunan University of Science and Engineer ingYongzhouPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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