A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model

Author:

Rye Sara1,Aktas Emel2ORCID

Affiliation:

1. School of Social Sciences, Faculty of Management, Law and Social Sciences, University of Bradford, Richmond Rd., Bradford BD7 1DP, UK

2. Cranfield School of Management, Cranfield University, College Road, Cranfield MK43 0AL, UK

Abstract

Background: This paper proposes a framework to cope with the lack of data at the time of a disaster by employing predictive models. The framework can be used for disaster human impact assessment based on the socio-economic characteristics of the affected countries. Methods: A panel data of 4252 natural onset disasters between 1980 to 2020 is processed through concept drift phenomenon and rule-based classifiers, namely the Moving Average (MA). Results: Predictive model for Estimating Data (PRED) is developed as a decision-making platform based on the Disaster Severity Analysis (DSA) Technique. Conclusions: comparison with the real data shows that the platform can predict the human impact of a disaster (fatality, injured, homeless) with up to 3% error; thus, it is able to inform the selection of disaster relief partners for various disaster scenarios.

Publisher

MDPI AG

Subject

Information Systems and Management,Management Science and Operations Research,Transportation,Management Information Systems

Reference73 articles.

1. Humanitarian aid logistics: Supply chain management in high gear;J. Oper. Res. Soc.,2005

2. Identifying challenges in humanitarian logistics;Spens;Int. J. Phys. Distrib. Logist. Manag.,2009

3. Drabek, T.E. (1986). Human System Responses to Disaster An Inventory of Sociological Findings Series, Springer.

4. Relief demand forecasting based on intuitionistic fuzzy case-based reasoning;Shao;Socioecon. Plann. Sci.,2021

5. Emergency resources demand prediction using case-based reasoning;Liu;Saf. Sci.,2012

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