首页|Reports from Department of Civil Engineering Advance Knowledge in Machine Learni ng (Integrating Electro-mechanical Impedance Data With Machine Learning for Dama ge Detection and Classification of Blended Concrete Systems)
Reports from Department of Civil Engineering Advance Knowledge in Machine Learni ng (Integrating Electro-mechanical Impedance Data With Machine Learning for Dama ge Detection and Classification of Blended Concrete Systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating from Telangana, India, by NewsRx correspondents, research stated, "In recent years, the assessme nt of structural integrity and durability of concrete systems has significantly advanced with the integration of novel sensing technologies and data-driven tech niques. This study introduces an innovative approach that utilizes electro-mecha nical impedance (EMI) data acquired through embedded piezo sensors (EPS) to moni tor and analyze the condition of blended concrete systems."
TelanganaIndiaAsiaCyborgsEmergin g TechnologiesMachine LearningDepartment of Civil Engineering
NETL
NSTL
