Disaster Management in Structural Safety analysis for Post-earthquake using Deep learning Framework

Earthquake is one of the major cause in the disaster management based on the intensity cause by shaking the surface of the ground. Earthquake may cause several damages such as loss of lives, volcanic eruption, and structural damages and so on. Here, were are discuss about the structure safety during the earthquake. They introduce the damage pattern and responses about the concept and for any damage building robust dataset is and generating methodological system with incorporation. Motions in the sequential ground is used for the increment of dynamic analysis which is used for the evaluation of structural damage that has been taken at the time of capacity of residual collapse. Map response has been done by deep learning algorithm and safety of the building structure is carried out by damage pattern is based on capacity of residual collapse that with acceptable threshold. Damaged building in the earthquake are kept under the state of structural safety that can be identify probabilistically under the tree regression, classification and random forest which has been included with predictive model. The frame building that we used in this proposed frame work is 5 story reinforced concrete building. In the damaged building they found damage pattern and response overlapping which has been determined as safe and unsafe. This process achieved with 93% and 90% in high accuracy prediction when they use responsible assessed safety state and responsibility of pattern damage. Rapid evaluation was used for the proposed framework based on the building damage that has been occupied the remaining safety structure after a seismic event and in the evaluation of resilience community subroutine was implemented or assessment performances of lifecycle building and optimization.