HEALTH STATUS PREDICTION SYSTEM FOR STRUCTURAL HERITAGES AND BUILDINGS: A COMPARATIVE ANALYSIS USING A DEEP AND MACHINE LEARNING MODEL
ABSTRACT Early detection of structural damage is essential for the maintenance, repair, and rehabilitation of the building. Yet, data science has emerged as a significant and useful technique for a number of civil engineering applications, such as structural health monitoring (SHM). As a result, the goal of this effort was to use a machine and