Evolutionary Method of Population Classification According to Level of Social Resilience

Following the many natural disasters and global socio-economic upheavals of the 21st century, the concept of resilience is increasingly the subject of much research aimed at finding appropriate responses to these traumas. However, most existing work on resilience is limited to a broad cross-discipli...

Full description

Saved in:
Bibliographic Details
Published in:International journal of advanced computer science & applications 2017, Vol.8 (1)
Main Authors: Kpinna, Coulibaly, Konan, Brou, Michel, Babri, Oumtanaga, Souleymane
Format: Article
Language:English
Subjects:
Chromosomes
Classification
Computer science
Genetic algorithms
Methods
Modelling
Mutation
Natural disasters
Population
Resilience
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Following the many natural disasters and global socio-economic upheavals of the 21st century, the concept of resilience is increasingly the subject of much research aimed at finding appropriate responses to these traumas. However, most existing work on resilience is limited to a broad cross-disciplinary panel of non-operational theoretical approaches. Thus, the study of the processes of social resilience is confronted with difficulties of modeling and a lack of appropriate analysis tools. However, the existing stratification methods are too general to take into account the specificities of the resilience and are difficult to use for non-specialists in modeling. In addition, most traditional methods of partition research have limitations including their inability to effectively exploit the research space. In this paper, we propose a classification algorithm based on the technique of genetic algorithms and adapted to the context of social resilience. Our objective function, after penalization by two criteria, allows to explore widely the space of research for solutions while favoring classes quite homogeneous and well separated between them.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2017.080119