A predictive model on post-earthquake infrastructure damage

Title

A predictive model on post-earthquake infrastructure damage

Creator

Paul A.; George J.P.

Description

Disaster management initiatives are employed to mitigate the effects of catastrophic events such as earthquakes. However, post-disaster expenses raise concern for both the government and the insurance companies. The paper provides insights about the key factors that add to the building damage such as the structural and building usage properties. It also sheds light on the best model that can be adopted in terms of both accuracy and ethical principles such as transparency and accountability. From the performance perspective, random forest model has been suggested. From the perspective of models with ethical principles, the decision tree model has been highlighted. Thus, the paper fulfills to propose the best predictive model to accurately predict the building damage caused by earthquake for incorporation by the insurance companies or government agency to minimize the post-disaster expenses involved in such catastrophic event. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

Source

Lecture Notes in Networks and Systems, Vol-132, pp. 267-280.

Date

2021-01-01

Publisher

Springer

Subject

Decision tree; Disaster management; Earthquake; Predictive model; Random forest

Coverage

Paul A., CHRIST (Deemed to be University), Bengaluru, India; George J.P., CHRIST (Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 23673370

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-981-15-5309-7_29

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090370576&doi=10.1007%2f978-981-15-5309-7_29&partnerID=40&md5=ba2acef044ac0dd7058dcedb63bb93b1