The division of urban functional zones is crucial for understanding urban characteristics and aiding in urban management and planning. Traditional methods, like dividing based on blocks and grids, are insufficient for modern demands. To address this, a knowledge-graph-supported method for building functional category division is proposed. Firstly, the associations between points of interest (POI) and buildings are established using triangulation and buffer zones. Then, a knowledge graph of buildings is constructed through entity and relationship extraction. A functional category classification model supported by the Z-score is designed using the semantic characterizations of surrounding POIs for inference rules. The results demonstrate high accuracy in building functional category division, supporting the refinement and intelligent expression of urban functional zones for urban construction, planning, and management.

Path planning algorithms are crucial for the autonomous navigation and task execution of unmanned vehicles in battlefield environments. However, existing path planning algorithms often overlook the concealment effects of obstacles, which can lead to significant safety risks for unmanned vehicles during operation. To address this issue, we proposed a novel path planning method—Covert Path Planning (CPP)—that incorporated considerations for the shadow occlusion caused by obstacles. By accounting for these concealment effects, CPP aimed to enhance the safety and effectiveness of unmanned vehicles in complex and dynamic battlefield scenarios. It started by designing shadow areas in the configuration environment based on solar azimuth and altitude angles. A gravitational field model was then created using these shadow areas and the target point’s position to guide the path point movement, achieving a path with a higher safety coefficient. The method also dynamically adjusted step length according to gravitational forces to boost planning efficiency. Additionally, a deformed ellipse-based obstacle avoidance technique was introduced to enhance the vehicle’s ability to navigate around obstacles. We simplified the path by considering the relationship between path points and shadows. We also proposed a Minimum-Jerk Trajectory Optimization method with controllable path noise points, which enhanced path smoothness and reduced predictability. Comparative analysis showed that CPP significantly outperformed five other algorithms—RRT, Improved B-RRT, RRT*, Informed RRT*, and Potential Field-by reducing running time by 46.01% to 93.3%, increasing path safety by 10.42% to 83.44%, and improving path smoothness, making it particularly effective for path planning in tactical scenarios involving unmanned vehicles.

The vitality of areas around tourist attractions plays a crucial role in promoting the sustainable development of both tourism and the regional economy. However, there is a lack of comprehensive studies on the methods for mining vitality around attraction perimeters, and existing approaches are often inadequate to meet the evolving needs of contemporary tourism development. To address this gap, we proposed a method for inferring vitality around attractions based on a knowledge graph. Our approach began by analyzing the functional and morphological characteristics of the areas surrounding the attractions, followed by the design of a vitality calculation model for these regions. Next, we developed a knowledge graph structure tailored for vitality reasoning around the attractions and established reasoning rules based on this graph. Finally, we conducted experiments to apply the vitality inference method to the main urban area of Kaifeng City as a case study. The results indicated that our method could effectively reason about vitality around the attractions. Notably, the vitality levels around the attractions in Kaifeng’s main urban area exhibited clear spatial differentiation. Attractions such as the Yang Family’s Tianbo Mansion, the Millennium City Park, and Lord Bao’s Memorial Temple showed higher vitality values, largely due to their advantageous functional integration and synergistic morphological characteristics.