To address the bottleneck issues in vehicle access efficiency for horizontal shifting mechanical parking garages, an access vehicle scheduling optimization model based on the PSO-OBL algorithm was proposed. The model aims to shorten vehicle access operation time and reduce user average waiting time by precisely controlling vehicle access strategies and time management. To enhance the optimization performance and convergence rate of the traditional particle swarm optimization algorithm, an innovative approach incorporating inter-particle collaboration and information exchange mechanisms was embedded into the algorithm framework, along with the integration of an opposition-based learning mechanism for efficient problem-solving. Experimental data indicates that, compared to the traditional particle swarm optimization algorithm, the PSO-OBL algorithm achieves significant improvements in customer average waiting time, average service time, average queue length, and average energy consumption. The findings of this study are expected to provide theoretical support and practical reference for optimizing access efficiency in horizontal shifting mechanical parking garages.

In order to evaluate the quality of professional athletes in martial arts, the camera array based measurement and multi-view geometry were combined to develop a refined recognition method of human movements under the constraints of human parametric model, and a quantitative evaluation method system of martial arts movements was established based on the obtained joint position and angle information, and the technical movements of athletes of different levels in the five-step boxing event were measured and evaluated. The results show that the method developed in this paper can effectively realize the identification and quality evaluation of athletes’ movements in Wushu events, and the research results can also be extended to other competitive sports and public health, so as to provide support for scientific training and sports rehabilitation.

During the geothermal development of dry hot rock, the high temperature rock mass is subjected to repeated cold and thermal cycles. It leads to the rupture of thermal reservoirs and the change of physical and mechanical properties. In order to further explore the mechanism of the influence of temperature and cooling-heating cycle on rock characteristics, the granite specimens subjected to different high temperature nodal heat treatment were treated with natural cooling, fresh water cooling and seawater cooling respectively. The physical and mechanical indexes and microstructure were studied. The damage constitutive equations of granite under uniaxial compression with three cooling cycles were established. The results show as follows. With the increase of temperature and cycle times, the mass loss rate is in the order of freshwater cooling > natural cooling > seawater cooling, but at 600 ℃, serious particle breakup and shedding cause the mass loss of seawater cooling rock sample to exceed that of natural cooling. The elastic modulus, compressive strength and tensile strength are decreasing. The damage of water cooling to high temperature rock is greater than that of natural cooling. The damage effect of high temperature is more obvious than that of cycle times. The micro-cracks of seawater cooling rock sample are more developed. The damage variables consider the effects of temperature and cycle times, and add the damage coefficient to consider the damage effects of freshwater cooling and seawater cooling. The uniaxial compressive stress-strain curves combined with damage analysis under load are compared with the experimental results in a high degree of fitting, which reflects the rationality of the model.

In order to analyze the influence of uncertain factors on power system, PCA (polynomial chaos approximation) method, which is both fast and accurate, is widely used in probabilistic power flow calculation. The polynomial chaotic approximation method requires that the probability density function of the random input variable is known, and the random input variable must satisfy the independent condition. A probabilistic power flow method based on DDPCA (data driven polynomial chaos approximation) was proposed for the known random input variables which are historical data. First, DDPCA selects the optimal orthogonal polynomial according to the historical data, and then determines the Gaussian sample considering the nonlinear correlation of random input variables, and then computes the weights with Monte Carlo integral. Then, a small amount of power flow was calculated based on Gaussian samples, and the approximation coefficient was solved according to the power flow results and weights, and then the statistical characteristics of the random output variables were obtained. The proposed method was compared with the point estimation method, and the effectiveness of the proposed method was verified by the results of three examples.

In order to improve the trajectory tracking accuracy and stability of the aircraft in the traction process, taking the four-wheel steering aircraft traction system as the research object, the kinematics model of the aircraft traction system is established, and the four-wheel steering trajectory tracking control method of the tractor based on the model predictive control was proposed. Taking the double lane changing condition as the reference trajectory, the motion control simulation model of the aircraft traction system was built in MATLAB/Simulink, and the four-wheel steering trajectory tracking controller was established by combining the speed of the tractor and the angular distribution relationship of the four wheels. The controller was compared and analyzed with the traditional PID control to derive the superiority of the controller, and the tractor four-wheel steering and front-wheel steering trajectory tracking controllers were simulated and compared and analyzed at the speeds of 1.5 m/s, 3 m/s and 4 m/s, respectively. The designed controller was simulated and verified by changing the initial positional attitude of the aircraft traction system at a speed of 1.5 m/s. The results show that at three different speeds, the airplane lateral error, the heading angle error, and the tractor heading angle error under the four-wheel steering trajectory tracking control of the tractor are smaller than those under the front-wheel steering trajectory tracking control. In the case of initial deviation, the four-wheel steering trajectory tracking controller can enable the aircraft to complete the correction of the initial deviation in time, reduce the trajectory tracking error, and at the same time improve the stability of the aircraft's traction system in the driving process.

The total organic carbon content in shale reservoirs is a crucial parameter for assessing hydrocarbon generation potential and shale gas enrichment. Accurate prediction of TOC(total organic carbon) is essential for oil and gas exploration and development. Conventional linear regression methods are limited in their predictive accuracy due to the complex nonlinear relationships among regional and well logging data. To address this issue, a prediction model based on Adaboost-WOA-BP was proposed for predicting TOC content. This model integrates WOA(whale optimization algorithm) optimized Backpropagation neural networks as weak learners within the Adaboost framework to construct a strong learner. Use of optimal natural gamma, density, acoustic time difference, and other sensitive logging parameters associated with TOC content calculation as inputs for the prediction model. Compared to conventional linear regression, BP neural networks and WOA-BP neural networks, the Adaboost-WOA-BP model demonstrates higher predictive accuracy, achieving a 95% match between predicted and measured TOC values.

In order to study the effect of temperature on the shear strength of fully weathered mudstone with different saturations,fully weathered mudstone specimens from a typical seasonal frozen region were used as the object of study.The GDS dynamic triaxial test system and the GDS unsaturated test system were used to conduct indoor triaxial tests on specimens with different saturations to investigate the trends of the shear strength parameters of fully weathered mudstone in the seasonal frozen region under different temperatures and surrounding pressures, and to compare and analyse the shear strength parameters of the two different saturations of the fully weathered mudstone were compared and analysed. The results show that the fully weathered mudstone is strongly influenced by saturation and temperature.The cohesion of both soil samples increases with decreasing temperature, and the internal friction angle increases and then decreases. The cohesion of the unsaturated mudstone specimens is consistently greater than that of the saturated mudstone specimens when the temperature and test system conditions are consistent. Saturation has a low effect on the internal friction angle of the specimens, which peaks at -5 ℃ and 0 ℃for the two soil samples respectively.

In order to study the effect of basalt fiber on the durability of recycled concrete under the erosion of salt solution, the durability of recycled concrete specimens with different basalt fiber contents after salt-dry-wet cycle coupling erosion was studied. A comprehensive durability index D value was established to evaluate the durability of recycled concrete based on the entropy weight method. The effects of dry-wet cycle period of salt solution and basalt fiber content on D value were analyzed. A GM (1,1) mean model was constructed to reveal the time-varying law of the D-value of recycled concrete, and the predicted life of recycled concrete under different conditions was obtained. The results show that the D value can reflect the influence of different salt solution dry-wet cycle cycles and basalt fiber content on the durability of recycled concrete. As the salt solution's dry-wet cycle increased, the D value of the specimen gradually decreased, indicating a severe change. However, adding basalt fiber to the recycled concrete can effectively enhance its D value and durability. When the content of basalt fiber is 1.0%, the durability of recycled concrete is the best. The GM(1,1) model can more accurately predict the time-varying pattern of D values of recycled concrete under coupled salt-dry-wet cycle erosion when the amount of data is small.

With the rapid development of China's civil aviation, the air traffic flow in terminal areas is experiencing a consistent and significant increase. The accurate forecast of short-term air traffic flow is of great significance for the efficient implementation of air traffic flow management. To enhance the accuracy of short-term air traffic flow forecast, a model combining EMD (empirical mode decomposition) and LSTM (long short-term memory) based on data differential processing was proposed. Firstly, the model performed empirical mode decomposition on short-term air traffic flow sequences. Secondly, to improve prediction accuracy, data difference was utilized to stabilize the time series. Finally, the processed sequences were input into the LSTM network model for prediction, and the final short-term traffic prediction value was obtained through data reconstruction. Experimental verification was conducted using the data from Zhengzhou Xinzheng International Airport. The results demonstrate that the model achieves a significant improvement in prediction accuracy, as indicated by the typical indexes RSME, MAE, and R², which are 0.29, 0.08, and 96.40%, respectively. This approach outperforms other methods and provides valuable reference for short-term air traffic flow prediction.

With the continuous integration of urban Bridges into a variety of traffic forms, various traffic vehicles and pedestrians interfere with each other, affecting the safety and comfort of pedestrians. To research the pedestrian response on single-level rail-cum-road bridges, a pedestrian-road vehicle-train-bridge coupling vibration model was established. The acceleration difference between the bridge panel and pedestrian SMD model was researched, and the influence of trains and road vehicle passing the bridge in different ways on pedestrians was calculated. The results show that, compared with bridge panel, the amplitude of acceleration fluctuation of pedestrian SMD model is smaller, but the walking pedestrian model may experience abrupt and significant acceleration peaks. Each moving subsystem in the coupling model has a speed-sensitive interval, in which the pedestrian acceleration increases significantly. The further vehicles are away from the bridge center, the greater the acceleration of pedestrians become. When train and road vehicle pass the bridge simultaneously, the peak acceleration of pedestrian caused by them will be superimposed, and the peak acceleration caused by road vehicles increases significantly due to the train.