An understanding of the walking patterns of groups of pedestrians in an evacuation is critical for the establishment of policies, procedures, and organizational structures to respond effectively to emergencies. Groups of pedestrians compose a crowd in which pedestrian motions are significantly constrained to maintain cohesion. On the basis of behavior theory, this paper proposes a multiagent model for the simulation of crowds of pedestrians. The main innovative aspect of this model is the genuine representation of the patterns of movement of groups of pedestrians. Patterns of movement consisting of the line-abreast pattern, the chain pattern, and the mixed pattern were investigated, and their influences on evacuations were evaluated quantitatively by taking into account the discrepant densities, disparate distributions of the proportions of pedestrian groups of different sizes, and heterogeneous velocities of groups of pedestrians. The simulation results show that the walking patterns of groups of pedestrians have a significant influence on the dynamics of pedestrian evacuation. The chain pattern was safer when the time of evacuation under high-density conditions was considered, and the mixed pattern had a better performance under moderate-density conditions. Moreover, the influence of patterns of movement was distinct with different distributions of pedestrian groups of different sizes; the chain pattern had the highest evacuation efficiency among the three patterns of pedestrian movement. In addition, a homogeneous velocity condition had a higher evacuation efficiency than a heterogeneous velocity condition. Thus, a chain pattern with a homogeneous velocity is recommended as the optimal pattern of movement in pedestrian evacuations when the safety and efficiency of plans and designs for the evacuation of pedestrian traffic with the different patterns of movement are considered.

The transport hub is an important component of the national and regional transportation system, and it is also the key node in the public transportation network. A reasonable site of the transportation hub determines the transfer efficiency directly, and affects the management of the whole traffic network. To reduce traffic congestion, rational hub sites should be considered. In order to evaluate the hub site, the contact number triangular fuzzy decision model was used, which is a theory based on the connection number and triangular fuzzy numbers. Weights and evaluation by the value of triangular fuzzy judgement will be used to reduce the deviation caused by personal preferences or statistical errors. This new method is more accurate given the merits of alternative hubs' sorting, by reducing subjective and objective factors to allow decision-makers to choose the best option.

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The mining process of traditional market equilibrium competition strategy is difficult to deal with massive data, resulting in the inability to accurately classify customer data in the process of competition strategy customization. Therefore, this paper proposes a strategy formulation method of balanced competition in the financial market based on computer data mining. Firstly, the process of the k-means clustering algorithm was optimized, and Murkowski distance and Markov distance were used as classification basis to find some potential information hidden in the data. Based on the optimized K-means clustering algorithm for data processing, in order to achieve effective data analysis, design customer behavior data mining process and analyze customer value matrix and customer pyramid. Finally, the layout framework of a balanced competition strategy in the financial market is established. The results show that the classification accuracy of the design method is higher than that of the traditional method in different states.