In order to further ensure the safety of railway operation，this article conducted a survey and analysis on the fatigue factors of railway train dispatchers. Firstly，according to the characteristics of the work content of railway train dispatchers，a fatigue causation evaluation index system for railway train dispatchers was established based on extensive literature review，consultation with railway train dispatching experts and human factors engineering experts. The index system consists of four first-level indicators: work content，job rotation arrangement，personnel quality，and external factors，as well as 18 second-level indicators. Secondly，AWAHP method was used to calculate the weight of different experts' own evaluation were calculated and the final weights of the final indicators were obtained. Finally，the dispatch center of a certain railway bureau was taken as an example for a comprehensive evaluation of the impact weights of dispatcher fatigue-cause factors based on AWAHP. The results show that emergency response，operation time period，continuous operation time，railway busy degree，and work complexity are the significant factors affecting dispatcher fatigue. The key factors of railway train dispatcher fatigue were effectively identified，and analysis and countermeasures were proposed for the key factors.

In order to further improve the prediction accuracy of slope stability，a slope stability prediction model based on MISSA optimized SVM was proposed. Six representative indexes，including bulk density (γ)，cohesion (c)，internal friction angle (Ф)，slope angle (φ_f)，slope height (H) and pore pressure ratio (r_u) were selected as the prediction indexes of the model. In response to the problems of slow convergence speed，low accuracy，and susceptibility to local optima in the sparrow optimization algorithm (SSA)，strategies such as one-dimensional composite chaotic mapping，SCA，Levy flight mechanism，and dynamic adjustment of step size factor are introduced for optimization and improvement. A slope stability prediction model based on MISSA-SVM was constructed. The MISSA-SVM model was applied to 9 groups of slope engineering examples，such as the Daxi landslide，for verification. The results show that the accuracy，precision，recall，F₁ score，mean square error (MSE) and area under the curve (AUC) of the MISSA-SVM model reach 96.29%，92.3%，100%，0.96，0.016 and 0.967，respectively，which are better than the SSA-optimized SVM model and BP model，and the prediction results are completely consistent with the actual slope conditions，indicating that the MISSA-SVM model has strong generalization ability.

An early prediction and warning method of offshore drilling overflow based on data model collaboration was proposed to prevent blowout accidents during offshore drilling. Firstly，an overflow risk prediction model based on PSO-LSSVM was established to predict the trend of drilling monitoring parameters in the future，and analyze the correlation between overflow events and characterization parameters. Then，a single-parameter overflow probability estimation prediction model was proposed based on the Naive Bayesian method，and the probabilities of multiple drilling parameters were integrated through the optimized D-S method to realize a hierarchical early warning of overflow events. The results indicated that the overflow characterization parameters simulated by the PSO-LSSVM model had low prediction errors. The overflow event probability represented by a single drilling parameter showed discrepancies due to different sensitivities. The fused early warning model can address the issues of inconsistent early warning times of single parameters and eliminate the possibility of false alarms.

In order to prevent fire accidents in subway stations and deeply understand the internal relations and hierarchical structure among the influencing factors of fire evacuation in subway stations，63 fire evacuation accidents in subway stations were analyzed based on the sixth edition of 24Model，and the interaction among various factors was fully considered，and 19 key factors affecting fire evacuation in subway stations were extracted to establish an index system of influencing factors of fire evacuation in subway stations. C-OWA was used to improve DEMATEL to determine the important influencing factors of fire evacuation in subway stations. On this basis，ISM was used to analyze the hierarchical structure and interaction path of various factors，and a multi-level hierarchical structure model of the influencing factors of subway station fire evacuation was constructed. Research results show that evacuation guidance，panic herd behavior and crowded people are the key influencing factors for the evacuation of people in subway station fires. The evacuation of fire personnel in the subway station is influenced by surface factors，intermediate factors and deep factors. Among them，evacuation education and training，facilities maintenance and inspection，evacuation plan and other factors are the root causes. Paying attention to the improvement of root causes was conducive to preventing and controlling accidents in essence.

In order to solve the problem of secondary disaster risk in coal mines affected by earthquake disasters，firstly，typical cases have been investigated and analyzed，and the types and damage characteristics of secondary disasters in coal mines have been summarized. Based on the comprehensive elements of "man-machine-environment-management"，a three-level indicator system for earthquake-induced secondary disaster risk assessment in coal mines has been constructed. Then，the evaluation method of risk level and importance of hidden danger has been proposed. Finally，a coal mine in a city in Hebei Province was used as an example for practical application. The results show that the types of secondary disasters induced by earthquakes in coal mines can be divided into 6 categories according to the disaster-bearing body. The assessment of the possibility of earthquake-induced coal mine secondary disasters mainly considers six aspects: the earthquake disaster level in the area where the coal mine is located，the risk of coal mine secondary disasters，the hazard of coal seam gas occurrence，the hazard of hydrogeological conditions in the mine，the level of fortification of the disaster-bearing body，and the ability to prevent and mitigate disasters. The assessment of the severity of the consequences mainly considers two aspects: the number of casualties and economic losses that may be caused by disasters. The weak links in seismic fortification of coal mines in this city are ventilation system，shaft support system，and drainage system，which should be targeted to improve seismic fortification level.

In order to improve pilots' emergency response capability in emergency situations and reduce civil aviation safety accidents，the pilot task process was analyzed based on the decision-making model and stress theory model. The index system of pilot emergency response capability was established from the aspects of pilot operation safety capability and pilot reserve safety capability. FAHP was used to establish the index system including safety operation capability B₁ and reserve safety capability B₂，and the membership degree of the second-level indexes was determined by combing the expert opinions. Then，the core indicators of pilot emergency response capability were obtained. The comprehensive evaluation of pilot emergency response capability by experts in the field of civil aviation safety was integrated through the ER algorithm. 2 crew pilots of an airline were selected for empirical analysis. The results of the study show that the proposed model can reduce the impact of uncertainty on evaluation results，thus significantly improving the reliability of the evaluation results.

In order to effectively evaluate the transportation service performance of HSRN and ensure the reliability of HSRN in the face of emergencies，based on complex network theory，a robustness evaluation method considering temporal and spatial dynamic characteristics was proposed. The dynamic changes of HSRSN was considered，and time information was incorporated into the modeling of HSRSN. Based on empirical operation data of high-speed railways in China，the necessity of considering spatiotemporal dynamic characteristics to evaluate network performance was verified，and the distribution characteristics of HSRN robustness in China were explored from the spatiotemporal dimension. The experimental results show that the train flow passing through different stations is different，and the network robustness exhibits a significant spatial distribution difference. Moreover，the disturbance scenarios are different，and the contribution of train frequency and spatial position of stations to the importance of stations is also different. In addition，the occurrence time and duration of disturbances are two key time factors that affect network robustness. Their different combinations result in significant time distribution differences in network robustness. The impact of disturbances on network performance varies at different time periods，resulting in obvious fluctuations in station importance ranking at different time periods.

In order to effectively prevent the unsafe driving behavior of take-away riders and reduce the traffic accidents caused by take-away riders，based on the work mechanism of take-away platforms' "rush game"，combined with the theory of stress perception evaluation，a theoretical model characterising the effects of time pressure and competitive atmosphere perception on unsafe driving behavior of take-away riders was constructed from the perspective of safety attitude and exemplary norms. A reliable questionnaire was designed through literature review，and 360 valid samples were collected from take-away riders all over the country. The data reliability was analyzed by SPSS 27.0 and AMOS 24.0 data analysis software，and the theoretical model was verified by hierarchical regression analysis using Process 4.0. The results show that time pressure and competitive atmosphere perception have significant positive effects on unsafe driving behavior. Safety attitude can significantly negatively affect the unsafe driving behavior of take-away riders. Safety attitude can mediate the relationship between time pressure and unsafe driving behavior，and also mediate the relationship between competitive atmosphere perception and unsafe driving behavior. Exemplary norms can positively regulate the relationship between safety attitude and unsafe driving behavior.

To address the limitations of evaluating the emergency response capability of port ships for oil spills in a single stage and reasonably allocate resources，the cloud gravity center evaluation method was adopted to evaluate the comprehensive emergency response capability of port ships for oil spill. Facing the entire process of emergency preparedness，early warning，response and recovery，and referring to the theory of "man-machine-environment-management" system and international and domestic regulations，a comprehensive emergency response capability evaluation index system was established. To address the issue that the traditional evaluation indicators were not fuzzy and random，a weighted deviation degree was used to determine the transformation relationship between qualitative indicators and quantitative values. AHP was used to optimize evaluation opinions and compensate for accuracy deficiencies caused by insufficient evaluation samples. Finally，taking Shanghai Port as an example，an empirical study was conducted on the comprehensive emergency response capability evaluation of ship oil spills. The results show that the cloud gravity center evaluation method can reasonably evaluate the comprehensive emergency response capability of port ships for oil spills. This method provides a theoretical basis for improving and perfecting emergency response capability，and provides a new approach for the comprehensive emergency response capability evaluation of port ships for oil spills.

In order to improve the pilot's operational comfort，a combined evaluation method based on FPN and FRA was proposed. First，a multi-factor coupled FPN network topology was established for the uncertainty information of the influencing factors of operational comfort. Then，the optimal combination weights were determined by the game theoretic assignment method. An algorithm combining the inter-layer correlation to determine the critical importance，analytic hierarchy process and fuzzy reasoning was proposed to establish a FRA based on subjective and objective weights. The confidence and state matrices were solved by iterative solution of the library. Finally，combined with the scenario data of ship pilotage in Shanghai harbor，the operational comfort of pilots was evaluated through the application of FRA based on FPN. The results show that the environment and pilotage equipment are the key factors affecting the comfort of their operation. The comfort level of pilotage operation in winter and summer corresponds to "less comfortable"，and "more comfortable" in May. The proposed method fully reflects the coupled nature of the factors influencing the comfort of the system.