首页|Research on Machine Learning Published by Researchers at Putian University (Adva nced Predictive Modeling of Concrete Compressive Strength and Slump Characteristics: A Comparative Evaluation of BPNN, SVM, and RF Models Optimized via PSO)
Research on Machine Learning Published by Researchers at Putian University (Adva nced Predictive Modeling of Concrete Compressive Strength and Slump Characteristics: A Comparative Evaluation of BPNN, SVM, and RF Models Optimized via PSO)
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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 reporting out of Putian, People’s Repub lic of China, by NewsRx editors, research stated, “This study presents the devel opment of predictive models for concrete performance, specifically targeting the compressive strength and slump value, utilizing the quantities of individual ra w materials in the concrete mix design as input variables. Three distinct machine learning approaches-Backpropagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF)-were employed to establish the prediction models independently.”
Putian UniversityPutianPeople’s Repu blic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSupport Vector Machines