In order to reduce the occurrence of safety accidents in coal mine production，from the perspective of emotion control，based on Valence-Arousal (V-A) emotional model，combined with emotional arousal methods and physiological measurement techniques，a cognitive experiment of miners' safety behavioral competence was conducted. Attention and decision-making time under different emotional states were measured. The regression analysis was used to investigate the continuous effects of degree-of-arousal on attention and risk preference under different emotional valence. The results show that in low degree-of-arousal and positive emotions，decreasing degree-of-arousal leads to weaker attention and more risk aversion in decision making in miners. In the high degree-of-arousal and positive emotions，with the increase of degree-of-arousal，the level of attention and risk aversion of miners in decision-making first increases and then decreases，until it is lower than neutral emotions. In low degree-of-arousal and negative emotions，decreasing degree-of-arousal would make miners pay less attention and have lower risk aversion in decision-making. In the high degree-of-arousal and negative emotions，an increase in degree-of-arousal increases and then decreases the attention and risk aversion in decision making，even until they are lower than the level of neutral emotions. By contrast，in the high degree-of-arousal range，increasing degree-of-arousal in positive emotion is more likely to reduce miners' safety behavioral competence to lower than the level of neutral emotional.

In order to explore the mechanism of rock burst induced by the instability of coal rock combinations under different dip angles，a particle discrete element program was used to conduct uniaxial compression tests on five sets of coal and rock combination models with different dip angles: 0，15，30，45 and 60°. The research results indicate that coal is the main cause of instability and failure in coal-rock combinations. When the dip angle of the coal-rock combination increased from 0° to 30° and from 30° to 60°，the uniaxial compressive strength of the coal-rock combination decreased by 2.01% and 9.59%，and the number of microscopic cracks decreased by 22.9% and 4.0%，respectively. The appearance time of the acoustic emission signal is advanced，indicating that the increase in dip angle led to a decrease in the uniaxial compressive strength of the coal-rock combination，and the instability failure time is advanced，but the degree of failure is reduced. In the early stage of uniaxial loading，the movement of coal and rock particles at the interface of different dip angle combinations led to an expansion trend at the interface. The dip angle affected the movement of coal and rock particles near the interface，leading to a gradual transition of the failure area of the combination from the coal body to the coal-rock interface. When the cracks in the coal body extend to the coal-rock interface，the interface slip effect generated by the high dip angle coal-rock combination causes its failure mode to change from compression shear failure to slip failure，with a 30° dip angle as the boundary.

To effectively optimize the shield construction parameters and achieve the goals of safety，efficiency，and energy-saving in the large-diameter slurry shield tunneling process，a hybrid intelligent algorithm combining categorical boosting (CatBoost) and decomposition was proposed based on a multi-objective evolutionary algorithm (MOEAD). The main shield construction parameters were set as the major research objects considering shield construction parameters and geological conditions，and the surface settlement，penetration rate，and tunneling-specific energy were determined as the prediction and control objectives. Moreover，the selected shield construction parameters were optimized，and a line of Wuhan rail transit was used to validate the hybrid algorithm performance. The results showed that the proposed CatBoost algorithm had great prediction performance for large-diameter slurry shields with the fitting accuracy (R²) of the three control objectives more than 0.9. The model's importance rank indicated that the total propulsion force and propulsion speed of the large-diameter slurry shield had significant influences on surface settlement，penetration，and tunneling-specific energy. The proposed CatBoost-MOEAD hybrid intelligent algorithm had an obvious optimization effect on the three control objectives，and the optimization ranges of surface settlement，penetration rate，and tunneling-specific energy reached 12.35%，7.47%，and 10.70%，respectively. Moreover，the control ranges of corresponding shield construction parameters were presented.

In order to prevent the risk of uncertainty and extreme impact brought by the black swan，the origin，transmutation and prospect of the black swan were studied in depth under the perspective of metaphor theory. Firstly，the conceptual integration theory was adopted to analyze the cognitive construction mechanism of the black swan risk metaphor from the aspects of historical flow and development trend，summarize the overall development trend of the black swan，and on the basis of this，divide the black swan into three important transmutation stages of founding，exploring development，and innovating and perfecting，so as to put forward the research dilemma and future outlook of the black swan under the background of digital intelligence empowerment. The results show that the risk metaphor meaning of black swan is a risk event with rarity，episodic，unexpected and unpredictable，and extremely negative impact; the development of the black swan risk metaphor will enter the stage of theoretical differentiation of quantitative fluctuation and change，and the direction of the research should be from generalized application to precise application，from single risk to composite risk，and from silo research to group research.

To enhance the driving safety and achieve correct decision planning for autonomous vehicles，a safe driving trajectory prediction method based on EKF-GRU was proposed. By combining learning-based methods with physics-based approaches，the prediction accuracy was improved and the rationality of the predicted trajectories was enhanced. In the first step of this method，a prediction network was constructed based on GRU to predict the longitudinal acceleration and yaw angular velocity of vehicles by extracting historical trajectory features. In the second step，an EKF state estimator was built based on the nonlinear vehicle kinematics to generate the vehicle's future limited-time trajectory，incorporating the observations obtained previously. The trajectory prediction method was validated on the NGSIM I-80 and US-101 multi-vehicle trajectory datasets. Experimental results demonstrate that the final distance errors (FDE)，root mean square errors (RMSE)，and average distance errors (ADE) of the predicted trajectories generated by traditional physics-based methods are 6.48，7.69 and 3.03 meters，respectively. In contrast，trajectories predicted using EKF-GRU exhibit higher accuracy，and the corresponding values are 5.45，6.67 and 2.56 meters，respectively. This represents improvements of 15.90%，13.26% and 15.51%.

In order to solve the problems that some operating conditions could not be automatically identified and the accuracy of abnormal operating condition recognition was low in the process of monitoring the production and operation of multi-product pipeline system，the intelligent operating condition recognition method was applied to construct a multi-product pipeline operating condition recognition model with real-time monitoring capability. First，logic rule discrimination methods and event logs in the multi-product pipeline system were used to supplement the data labels. Second，the data were segmented according to the start and end time of the operating conditions，and the subsequence of different operating conditions were extracted by using the sliding window. Third，the features of subsequence were extracted to construct the model for operating condition recognition of multi-product pipelines，and the recognition effects of six classification models，namely，random forest (RF)，adaptive boosting (AdaBoost)，support vector machine (SVM)，time series forest (TSF)，random interval spectral forest (RISF) and sequence learner (SEQL)，were compared and analyzed. Finally，a real multi-product pipeline was used as an example for model validation. The results show that the TSF model has the highest recognition accuracy for the four operating conditions of valve switching，valve internal leakage，pigging and sling pump，and is more suitable for the recognition of short-term operating conditions. In contrast，the recognition precision of the AdaBoost model has a higher probability of including the true value in the 95% confidence interval.

In order to enhance the efficacious operation of the air traffic control system，a quantitative model was established by focusing on the individual load of controllers. Tests were designed to collect pre-service and post-service data on various indicators from 16 area controllers in the front line. Sensitive variables were selected to describe individual loads based on changes in test data. A comprehensive assessment index system was established that included three dimensions: psychological perception load，physiological reaction load，and mental workload. The controller individual load index model was developed. The optimal weights of the individual load index were determined by the the entropy-critic combination weighting method. The quantitative model of the controller's individual workload was finally derived. Further K-Means clustering analysis was performed based on the controller's individual load composite index. There were evident discrepancies in the workload changes of the controllers due to different individual postures. The results indicate that the post-post individual workload changes of the controllers could be classified into three distinct groups. The first group，comprising 50% of the total number of controllers，exhibited the smallest post-post individual workload growth. The second group，accounting for 43.75% of the total number of controllers，exhibited a moderate post-post individual workload growth. The third group，comprising 6.25% of the total number of controllers，exhibited the largest post-post individual workload increase. These findings align with the instructor's ratings of controller competence.

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 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 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.