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Author(s):

Rajesh Kumar | Dr. Sunil Sugandhi
Keywords:

Seismic Damage Estimation, Statistical Models. Machine Learning, Mean Absolute Percentage Error, Mean Squared Error.
Abstract:
With Rapid Advances In Statistical Modelling And Data Analysis, Analysis Of Bridge Failure And Damage Is Also Being Considered Under The Purview Of Statistical Models. It Is Ubiquitous That Manual Inspection Of Bridge Damage And Estimations Are Time Consuming And May Not Be Practically Feasible In Cases Where The Experts Are Not Readily Available And/or Sites Of Huge Mass Calamities Such As Earthquake Prone Cites. Thus A Quick Estimation And Evaluation Of The Damages Is Necessary So As To Immediately Stop The Cascading Effect Of The Possible Failure And Casualties. In This Paper, A Comprehensive Review On The Various Statistical Techniques Being Employed For The Evaluation Of Bridge Failure Have Been Discussed Along With The Salient Points. Previous Work In The Domain Has Also Been Cited So As To Garner Attention Towards The Recent Trends In The Domain. The Evaluation Metrics Commonly Employed For The Analysis Of The Statistical Systems Have Also Been Defined. It Is Expected That This Comprehensive Review Would Pave The Path For Further Research Domains In The Field.