In order to improve the effectiveness of hidden danger investigation，a reasoning model for hidden danger of explosive accidents of hazardous chemicals was proposed based on BN. First，according to the theory of combustion and explosion and expert experience，the main types of hidden dangers affecting the explosion of hazardous chemicals were determined，and BN model of explosion，leakage and ignition source was constructed. The prior and conditional probabilities of hidden dangers were determined by triangular fuzzy numbers. Then，Bayesian forward reasoning was used to calculate the probability of explosions of hazardous chemicals. Combined with reverse reasoning，the hidden dangers that were most likely to lead to explosion accidents were identified，and the formation of hidden risk factors was traced back. Finally，Bayes sensitivity analysis method was used to determine the key hazards affecting the explosion of hazardous chemicals and the correlation between the accident hazards，and it was verified by an explosion case of oil storage tank. The results show that the explosion probability of the storage tank calculated by causal reasoning is about 4.7%. Equipment overpressure and electric spark have the highest posterior probability，which is the most likely to lead to the explosion of the storage tank. The reason can be traced back to the failure to inspect the storage tank regularly or the failure to use explosion-proof equipment. Electrical spark and valve or flange damage are the key hidden dangers of oil storage tank explosion，and the accident hidden danger is related to the chain of "valve or flange damage → abnormal oil gusher → leakage exceeding limit → fire source (electrical spark) → explosion".

In order to examine the effects of typical optimization measures on the efficiency and safety of evacuating bottlenecks，evacuation tests incorporating pedestrian characteristics were conducted. The test encompassed 28 distinct cases，representing different combinations of optimization measures and pedestrian traits. Parameters such as evacuation time，speed，and local occupant density were measured across all conditions. Our findings reveal that the efficacy of bottleneck optimization measures is influenced by factors such as bottleneck width，the presence of luggage，and fixed evacuation directions. Practical implementation needs a tailored approach，integrating pedestrian characteristics and site-specific control strategies. Specifically，introducing a column in front of the bottleneck significantly benefits pedestrians without luggage，leading to a 15.30% reduction in density during bottleneck navigation with narrower widths，thereby enhancing safety，and concurrently improving evacuation efficiency by 13.18% in scenarios with wider bottleneck widths. Meanwhile，introducing a rail is preferable for pedestrians carrying luggage with wider bottleneck widths，especially when combined with a fixed evacuation direction，significantly enhancing evacuation efficiency by 21.90% while maintaining safety. Among the three bottleneck configuration alterations，incorporating a funnel-shaped passage preceding the bottleneck stands out as the most effective optimization measure，resulting in a notable 9.59% reduction in density，thereby enhancing safety，along with a simultaneous 9.14% decrease in evacuation times. It is noteworthy that the implementation of a straight channel or the combination of a straight channel and a funnel-shaped passage may yield negative impacts on both safety and efficiency.

To effectively assess the various risks faced by the multifunctional reserve general warehouse，a comprehensive safety evaluation method for the multifunctional reserve general warehouse was proposed. First，the integrated risk characteristics of dynamic-static unity，subjective-objective unity，and direct-indirect unity for multifunctional the reserve general warehouse were summarized. Next，based on the combination of a static risk index system and a dynamic risk assessment model，a method for measuring the triggering effects and calculating the residual risks of the multifunctional reserve general warehouse was proposed. Lastly，safety evaluation criteria were delineated. Taking the core area of a logistics hub in China as the application case，the safety risks of the selected district were evaluated. The applicability and shortcomings of the proposed comprehensive evaluation method for the multifunctional reserve general warehouse were discussed. The results indicate that the method can effectively reflect the risks and their changing trends of the studied warehousing system. The practical application demonstrates that it is crucial to determine the trigger relationships and residual risks for accurately characterizing and evaluating the safety status of the multifunctional reserve general warehouse.

In order to improve the reliability of the logistics facility network of railway construction projects in complex environments，scenario reduction techniques were used to generate a minimum subset of disruption scenarios and their disruption probabilities to describe the disruption scenarios of transport channels. The polyhedral uncertainty sets were used to describe the uncertainty of logistics demand. To minimize the combined costs of transport，construction，operation and penalty costs，a two-stage stochastic and robust optimisation technique was applied to construct an uncertainty optimisation model for the location of material reserves bases. The model was solved based on a C&CG algorithm. The validity of the model and the algorithm was verified by taking a C railway construction project in a complex environment as an example. The results show that the cost variation coefficient of the model-acquired solutions is 4.3% of the traditional model in the random disruption scenario，and the cost fluctuation of the model-acquired solutions can be up to 38% of that of the traditional model in the extreme demand fluctuation. The two-stage uncertainty optimisation model given in this paper can effectively reduce the cost variation of the logistics facility network resulting from the disruption of transport channels and demand fluctuations.

In order to improve air traffic controllers' emergency response ability，a reliability model of air traffic controllers' SA was constructed from three aspects: air traffic controllers' personal ability，air traffic control task characteristics and air traffic control equipment. Tower control simulation software and SA Global Assessment Technique (SAGAT) were used to measure the air traffic controllers' SA level in emergency situations. Based on BN，SA reliability was quantitatively analyzed to predict air traffic controllers' level of SA，and based on Bayesian inference，the key factors affecting the reliability of air traffic controllers' SA were analyzed. The results show that the reliability of SA of air traffic controllers is positively correlated with the level of SA in emergency scenarios，and the SA level can be predicted by air traffic controllers' SA reliability. The BN inference analysis reveals that the factors with a higher degree of influence and sensitivity to the reliability of controllers' SA were the deployment of aircraft availability time，the accuracy of the control equipment and the controller's memory. The causal chain that has the greatest impact on the air traffic controllers' SA reliability is the deployment of aircraft availability time→mission characteristics→SA reliability.

In order to provide reference direction for the research of emergency social mobilization more accurately，taking 296 research papers on social mobilization for emergencies included in Chinese Social Sciences Citation Index(CSSCI) journals in China National Knowledge Infrastructure(CNKI) as samples，this paper comprehensively used bibliometrics，knowledge graphs and other visual analysis methods to analyze the number，distribution，institutions，research topics，hot spots and changing trends of papers in this field over the years. The research shows that since 2003，the number of papers published in the study of social mobilization for emergency response has experienced three stages of development，with the increasingly wide distribution of periodicals and loose publishing institutions. There are more and more research topics，mainly focusing on the trigger scenario，implementation mechanism and functional effect of emergency social mobilization in the emergency response stage. Hot topics are constantly emerging with more breadth and depth，and the research methods are relatively limited. There is much room for further research and development，which can focus on the research contents of multi-methods，the whole process and intelligence of emergency social mobilization.

In order to explore the influence of different learning scenarios on the learning effect of learners in the teaching process of fire emergency fire escape in subway stations，and explore the advantages of virtual reality learning. Questionnaires and MP160 physiological instrument were used to obtain different behavioral response data of learners in paper learning，mobile video learning and virtual reality learning scenarios，and these data were processed and analyzed. The results show that there are significant differences in learners' academic performance under the three learning scenarios. Compared with mobile video learning and paper learning scenarios，virtual reality learning scenarios can promote learners' understanding of subway fire escape knowledge and significantly improve academic performance. Under the three learning scenarios，there are significant differences in learners ' interest in learning. Virtual reality learning scenarios show significant advantages in improving learners ' interest in learning subway fire escape knowledge. The virtual reality learning scene reflects a higher level of physiological arousal in terms of physiologic index.

In order to enhance the stability and safety of railway driving and effectively identify the influence of the dispatcher's fatigue state on the driving organization，a method for identifying the fatigue state of the dispatcher was proposed based on the characteristics of EEG signals. The fatigue state of the dispatcher was divided according to the working time period，and the high-speed rail scheduling simulation experiment was designed to collect EEG data. The three types of brainwave frequency-domain amplitudes of high-speed rail dispatching subjects were extracted as the characteristic value by wavelet series expansion and Fourier transform，and the classification results of fatigue state were verified by combining the operation characteristics and EEG signal characteristics of dispatchers. The ResNet18+SoftMax model and MobileNet V2+SoftMax model were built through the Python language environment. The input features were converted into a three-dimensional rectangular model based on deep learning. The weights were optimized and adjusted to obtain the optimal model，so as to judge the fatigue state of high-speed rail dispatchers. The research results show that the fatigue state recognition accuracy of the participants in the high-speed rail scheduling experiment by ResNet18+SoftMax and MobileNet V2+SoftMax two models is 92.78% and 99.17%，respectively，compared with support vector machines(SVM) model to improve the awake state and fatigue state recognition accuracy，and reduce the model computing time. Among them，the MobileNet V2+SoftMax model can better identify the fatigue state of the dispatcher. With the principle of MobileNet V2+SoftMax model as the core，the potential fatigue risk of high-speed rail dispatchers under long-term working conditions can be identified more quickly and accurately.

In order to improve the situation of network security education and the quality of network security education in colleges and universities，a cognitive-attitude-behavior theoretical model of college students was constructed. Through the distribution and screening of questionnaires，659 valid questionnaires were obtained. SEM was used to test the influence of network security education on network security cognition，network security attitude and network security behavior in the collected data. The results show that network security education can have a significant influence on network security cognition，network security attitude and network security behavior. During the influenced process，network security cognition and network security attitude play an independent and chain intermediary role. Legal and moral education，knowledge education，practical activities，and leading by example can directly affect network security behavior. Legal and moral education has the strongest influence，followed by knowledge education. Practical activities and leading by example are the weakest. In terms of specific paths of process，legal and moral education mainly affects network security behavior through direct effect，while knowledge education，practical activities and leading by example mainly affect network security behavior indirectly through security cognition.

To promote the construction of emergency technology and management majors and strengthen the university talent cultivation of emergency rescue, the majors' characteristics were determined based on the national needs in emergency. Then, a talent development mode for emergency technology and management majors was proposed from aspects of professional ethics, theoretical knowledge systems, and practical technical ability. Firstly, the majors' professional ethics were clarified based on the professional ethics requirements from Teaching Standards for Emergency Rescue Technology and National Vocational Skill Standards for Emergency Rescuers. Secondly, a core curriculum system covering the entire emergency lifecycle was proposed using the PPRR(Prevention, Preparation, Response, Recovery) model including prevention, preparation, response, and recovery. Next, a combination of learning and training, integration of government-industries-research organizations was proposed to advance the cultivation of emergency skills and the enhancement of practical innovation capabilities. Finally, a talent cultivation system was developed from the perspectives of textbooks, faculties, teaching process management, a talent assessment system, and a continuous improvement mechanism. The results indicated that the talent development system integrated with public service and social responsibility attributes, full-cycle work content, disasters, and multi-subjects practical applications. Moreover, the system developed a close connection between talent cultivation and practical work needs and guided for cultivating of high-level applied talents in the emergency field who had moral and professional qualifications and theory and practice capabilities.