Behavioural Factors Based Crowd Evacuation Modelling Using Fuzzy-Neural Approach

Zakaria, Wahida (2020) Behavioural Factors Based Crowd Evacuation Modelling Using Fuzzy-Neural Approach. PhD thesis, Universiti Sains Malaysia.

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Abstract

Crowd studies on evacuation have attracted researchers from many fields of study that aim to simulate reality phenomena of escape panic during the evacuation. The main factor being analyzed is the crowd behaviour. Early studies of crowd behaviour have started to imitate reality behaviour patterns of evacuation such as following, queuing and herding. This studies have a little understanding on the crowd behaviour patterns from the psychological perspective on the emotions influences under stressful situation which may result in different behavioural actions. In addition, the simulations results in earlier studies are shown in a single screen which are then validated qualitatively through observation by interview respond or survey. The main reason for such evaluation is to check on the similarity of the behavioural patterns. In later advancement of technology such as surveillance camera, the simulations of behavioural pattern produced are comparable side by side to the real videos. Nevertheless, the validation method still remain as qualitative due to the challenges in tracking peoples movement during the evacuation which is needed for accuracy validation against the reality evacuation. Therefore, the main goal of this study is to propose a crowd evacuation modelling (CEM) that derived from psychological theory of emotions which incorporated human behavioural factors namely physical, environment, psychology and perception. The emotions considered are panic and confuse which react to the threatening situation using fuzzy logic approach. Fuzzy logic approach is well-known in handling uncertainties and complex problem which suit well in modelling human behaviours.

Item Type: Thesis (PhD)
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis
Depositing User: Mr Mohammad Harish Sabri
Date Deposited: 20 Sep 2022 02:16
Last Modified: 20 Sep 2022 02:16
URI: http://eprints.usm.my/id/eprint/54798

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