RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

Abstract

Due to safety issues when passengers get on and off the subway and spend a lot of time on the subway, this makes subway station signs very important. Moreover, in case of fire and other dangerous situations and emergency evacuation, the guiding signs must be able to guide passengers to leave the station and dangerous areas efficiently and orderly, so as to protect the personal and property safety of passengers. The purpose of this study was to analyze the decision response of subway evacuation signs using the characteristics of the brain components. In this study, subway model is constructed. When you perform simulation using software, you need to fine tune the parameters to get the best simulation effect. A questionnaire survey was made on the components of the subway sign. The results show that the number of people who think that the standard font of the blackboard logo is the most representative of the emergency exit, accounting for 78.2% of the total number of people, taking the image as the first choice accounted for 52.9% of the total number of people, and the green sulfur powder logo as the first choice accounted for 69.8% of the total number. This study makes an important contribution to the research of subway traffic safety problems.

Smart Community Emergency Evacuation Management System and Risk Assessment Based on Mobile Big Data

“…The realization of GIS technology is based on data collection technology, communication technology, software technology, information security technology, virtual reality technology, etc. GIS technology can not only effectively manage various resource and environmental information with spatial attributes, conduct rapid and repeated analysis and testing of resource and environmental management and practice models, facilitate decision-making, and conduct scientific and policy standard evaluations but also can effectively dynamic monitoring, analysis, and comparison of resource and environmental conditions, and changes in production activities during the period, data collection, spatial analysis, and decisionmaking processes can also be integrated into a common information flow, which can significantly improve work efficiency and economic benefits and provide technical support to ensure sustainable development [20,21].…”

Special issue on neural computing challenges and applications for industry 4.0

“…Lou [5] uses the Gaussian mixture model of machine vision to build the mapping relationship between the observed variables of the object and the robot joint variables. Huang and Cao [6] was to analyze the decision response of subway evacuation signs using the characteristics of the brain components. Huang et al [7] propose the application of research of FFR based on deep learning in the diagnosis of coronary heart disease complicated with diabetes mellitus.…”