To solve the problems of single prediction state and insufficient prediction accuracy of the traditional coal spontaneous combustion prediction model，a prediction model based on RBF neural network optimized by SSA was proposed. Firstly，the temperature programmed test was used to analyze the variation characteristics of the index gas of coal samples with temperature. The coal spontaneous combustion process was divided into slow oxidation stage (80≤t_i<120 ℃)，accelerated oxidation stage (120≤t_i<160 ℃) and intense oxidation stage (t_i≥160 ℃) with coal temperature as the node. At the same time，the grey correlation degree between the index gas and coal temperature in each stage of coal spontaneous combustion was analyzed. Secondly，the performance of Particle Swarm Optimization (PSO)，Grey Wolf Optimization (GWO) and SSA algorithm was tested by different dimension test functions. Finally，the superiority of the RBF neural network optimized by SSA algorithm to the coal spontaneous combustion prediction model was verified by using six mining area data. The results show that the grey correlation coefficients of CO/ΔO₂，CO and C₂H₄ with coal temperature are the largest in the slow oxidation stage. The grey correlation coefficient between C₂H₄/C₂H₆，CO/ΔO₂，CO₂/CO and coal temperature is the largest in the accelerated oxidation stage. The test results of three different dimensional functions show that SSA has better global search ability，stability and faster convergence speed compared with PSO and GWO. When the number of neurons is 5 and the number of iterations is 300，the prediction accuracy of the SSA-RBF neural network prediction model for the slow and accelerated oxidation stages reaches 99% and 93% respectively.

To establish a comprehensive evaluation system for urban waterlogging risk，three dimensions were selected: water accumulation risk，overload risk，and lateral inflow. This system aims to provide a reference for the optimal placement of storage tanks. Firstly，a mixed MCDM framework including the improved analytic hierarchy process (IAHP)，anti-entropy weight method (AEW)，and technique for order preference by similarity to ideal solution (TOPSIS) was designed. Then，the IAHP-AEW-TOPSIS model was compared with IAHP-TOPSIS and AEW-TOPSIS model respectively，and the ranking consistency was verified by Spearman ranking correlation coefficient. The performance of IAHP-AEW-TOPSIS model was confirmed by calculating variation coefficient，relative range and sensitivity. Finally，a model based on MCDM-BPNN was established and verified by a waterlogging-prone area in Shanxi Province. The results show that water accumulation risk has the most significant influence in the evaluation system of urban waterlogging risk，with the weight of 0.46，followed by the overload risk with the weight of 0.36. The location of the node and the number of connecting pipes greatly affect the risk of waterlogging of the node，and waterlogging occurs more frequently at the junction of pipes or in larger confluence areas. There was better performance exhibited by the IAHP-AEW-TOPSIS model. In the 5-year and 10-year return periods，the accuracy of MCDM-BPNN model verification set is 93.3% and 100% respectively，which can accurately and rapidly simulate and predict urban floods. After the application case is set up，the number of high，medium and low risk nodes are 7，9，30 and 6，19，21 respectively，and the effect of reducing waterlogging overflow is remarkable.

To explore the influence of the lithology and cross-section shape on spalling failure properties of deep hard rock tunnels，indoor true triaxial tests on spalling failure were performed. Firstly，two types of rock samples (marble and granite) and two typical cross-section shapes (high side wall gate arch shape and horseshoe shape) samples in practical applications were selected. Then，the failure characteristics under the influence of different lithology and cross-section shapes were analyzed from the three aspects including spalling failure mode，spalling rock plate characteristics，and the characteristic stress during spalling. Finally，numerical simulation was conducted to explore the corresponding displacement and stress distribution characteristics during the development and propagation of the cracks. Furthermore，the spalling failure characteristics of deep hard rock tunnels were investigated. The results indicated that the slab peeling and opening failure phenomenon for the marble sample was more significant than the granite one in terms of spalling failure mode during the test process. Moreover，the cross-sectional contour range involved in spalling failure for the horseshoe shape sample was smaller than the high-side wall gate arch shape. Different lithologies presented different flaked rock slab shapes for different flaked rock slab characteristics. Compared with the high-side wall gate shape，the flaked rock slabs near the outer layer relevant to the curved wall arch sample were more slender. For the characteristic stress during spalling，the granite sample had a larger threshold at the beginning of the spalling and a faster rate for the evolution process of the spalling failure compared with the marble one. Furthermore，compared with the horseshoe shape sample，the characteristic stresses of the high-side wall gate arch sample were higher from the beginning of plate cracking to the occurrence of obvious plate cracking failure. The area with large displacement in the numerical simulation was mainly observed on the side wall of the hole. The farther away from the side wall，the smaller the displacement. Moreover，the major reason the spalling occurs can be attributed to the tangential stress concentration.

In order to prevent coal spontaneous combustion disasters under high-temperature environment and clarify the spontaneous combustion characteristics，coal samples from the 1306 working face of the VI coal seam in Barapukuria coal mine were selected. The coal samples were subjected to constant temperature treatment at 40，50，and 60 ℃ for 30 days，and pore structure analysis and thermogravimetry(TG) were performed on the raw coal samples and high-temperature pretreated coal samples to test the oxidation kinetic parameters. The results show that after high-temperature treatment，the proportion of small pores decreases while the proportion of medium pores and large pores increases. After treatment at 60 ℃，the specific surface area of the coal sample increases from 2.351 m²/g of raw coal to 3.285 m²/g，and the total pore volume increases from 0.007 88 mL/g of raw coal to 0.010 01 mL/g. In addition，compared with raw coal，the ignition temperature and burnout temperature of the coal sample significantly decreased after high-temperature treatment，and the maximum weight loss and the maximum weight loss rate increased by 6.1% and 23.3%，respectively. The calculation results of oxidation kinetics show that the activation energy and pre-exponential factor of the coal sample after high-temperature treatment are lower than those of the raw coal，indicating that the high-temperature environment significantly improves the oxidation reaction activity and increases the risk of spontaneous combustion of coal.

In order to ensure the normal operation of wastewater treatment plants and prevent equipment failures，an improved FMEA risk assessment model was proposed. Firstly，the FMEA method was used to identify the failure modes of wastewater treatment plant equipment，and it was combined with PFS to portray the uncertainty assessment information. Secondly，the subjective and objective weights were calculated using the stepwise weight assessment ratio analysis (SWARA) method and the maximum deviation method，and the comprehensive weights of the three risk factors were calculated through the game theory combination weights. Thirdly，the multi-objective optimization on basis of ratio analysis (MOORA) method was used for the equipment failure mode risk ranking. Finally，taking Changchun City Z wastewater treatment plant equipment failure risk assessment as an example，the model proposed in this paper was compared with traditional FMEA，Pythagorean fuzzy technique for order preference by similarity to ideal solution (PF-TOPSIS)，and Pythagorean fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (PF-VIKOR)，and the feasibility and effectiveness of the model were verified. The results show that the top 3 failure modes of wastewater plant equipment are that the grit extracted by the grit remover contains excessive organic matter，the diaphragm is dislodged or broken，and large foreign objects enter the pump.

To solve the current safety risk issues of UAV operations in low-altitude urban environments，a FBN was used to identify and analyze the key risk factors of low-altitude UAV operations. Firstly，risk factors were analyzed from the perspective of human-machine-environment-management based on operation process of low-altitude UAVs. GeNIe software was used to develop a Bayesian network(BN) for risk assessment of low-altitude UAV operations，and the prior probabilities of the underlying events were analyzed using expert prior knowledge and fuzzy sets. Finally，univariate，bivariate，and sensitivity analyses were performed，and the network feasibility was validated. The results indicated that the key risk factors for low-altitude UAV operation were UAV battery failure，environmental obstacles on the operation route，and UAV operation supervision technology. FBN reverse inference showed that environment-related risk (79%) and UAV equipment risk (60%) were the main risk factors in the UAV operation process.

In order to evaluate the development of muscle fatigue during drilling operations in the hand-over-head posture，a simulated drilling test was conducted to measure the maximum voluntary contraction (MVC) of muscles before the test，the maximum residual muscle strength (MRF) after the test，the degree of strength output attenuation (ΔF)，and ratings of perceived exertion (RPE) of wrists，elbows，and shoulders. MET was recorded. By setting different combinations of three operating surfaces (front，side，and bottom) and three operating heights as experimental variables，the effects of different operating methods on muscle fatigue during drilling operations under hand head posture were compared. Subsequently，the effects of three operating surfaces (front，side，and bottom) and three operating heights on MET，MRF，ΔF，as well as RPE of wrist，elbow，and shoulder were analyzed. Research has shown that using frontal manipulation and reducing arm lift height can effectively alleviate muscle fatigue. Different operating surfaces significantly affect MET，MRF，and ΔF，as well as RPE of the wrist，elbow，and shoulder. Different operating heights significantly affect MET，MRF，and RPE of the elbow. MET prediction model established in this article can reflect the muscle fatigue status of personnel during drilling operations in the hand-head posture.

In order to investigate the effect of EA on the process of coal oxidation spontaneous combustion，EA was uniformly mixed with long-flame coal in Xiashijie at the mass ratios of 2%，4%，6%，8% and 10% to experiment. The contents of active functional groups and the variation characteristics of thermal transport characteristics of each sample were studied using the microscopic infrared spectroscopy test and laser thermal conductivity test. The optimal mass ratio was determined to be 8% through the evaluation of the inhibitory effect of coal oxidation spontaneous combustion. The coal spontaneous combustion temperature-programmed test was used to compare the influence of four inhibitors on the gas release of coal oxidation spontaneous combustion，and the degree of inhibition of EA on coal oxidation spontaneous combustion was further determined. The results showed that the peak areas of -CH₃，-CH₂，-OH and -C=O- in EA-tc are reduced，but the peak area of C-O is increased compared with RC. At the same coal temperature，the thermal diffusivity and thermal conductivity of the RC are higher than those of EA-tc，and its specific heat is lower than those of EA-tc. The average inhibition rates of thermal diffusivity，specific heat capacity and thermal conductivity of 8% EA on low-temperature oxidation process of coal samples are 20.8%，9.8% and 13.1%，respectively. Compared with RC，CO release amount of 8% EA-tc is reduced by 52.3% at 170 ℃，and the resistance rate of EA on coal oxidation spontaneous combustion is maintained at 50.5% to 72.5% at 30 to 170 ℃. The inhibitory effect of EA on coal oxidation spontaneous combustion is better than that of the other three inhibitors.

In order to explore the negativity and universality of security incidents，a reverse thinking paradigm based on Negative Systems Theory in safety science was first applied in conjunction with the Ecosystem Theory from systems science. This approach identified the characteristics of intelligent systems—openness，inclusivity，interactive coupling，and dynamic balance—and clarified the logical framework for intelligent system security analysis. Subsequently，the sources of security incident hazards were identified from the perspective of negative systems theory，and the mechanisms behind security incidents were explained. The concept of cohesive coupling was introduced，and an s-shaped framework model was proposed to analyze the stability of subsystems within intelligent systems and investigate their underlying technological support. Finally，using the concepts of producers，transmitters，consumers，and decomposers，the dynamic balance of information flow throughout the entire process in intelligent systems was analyzed，collectively shaping the security analysis framework under the negative systems theory perspective. The results indicated that the security analysis framework established under the negative systems theory perspective could effectively analyze the secure and stable operation as well as the dynamic balance of information flow throughout intelligent systems，ensuring the comprehensiveness and reliability of intelligent system security analysis.

To investigate the effects of different incidental emotions on low sensation seekers' unsafe behavior decision-making process from a neural level，ERPs technique was used. The Chinese version of the Sensation Seeking Questionnaire for College Students was used to select low and medium sensation seekers (control group). Then，video clips were used as emotional stimulus materials to induce positive and negative emotions before the experiment，and a risk scenario task was set to perform risk decision-making experiments. The results indicated that when the emotional stimulus variable was not considered，there was no significant difference in safe behavior decision-making between the low sensation-seeking and the control groups. Under positive emotion，low sensation seekers maintained risk aversion. However，low sensation seekers were more likely to make unsafe behavior decisions regarding behavioral performance under negative emotion. Under negative emotion，the latency of LPP induced by low sensation seekers was delayed，indicating that the interference of negative emotion made it more difficult for individuals to classify and evaluate risks. Therefore，the intrinsic reasons for their external behavioral performance can be explained from a neural level. Therefore，emotions play a moderating role in the process of sensation seeking affecting safe behavior decision-making.