To address the issues of low solving efficiency and susceptibility to local optima in multi-unmanned aerial vehicle (multi-UAV) task allocation algorithms within urban areas, this study constructs a task allocation model aiming to minimize economic costs for material delivery and reduce the urgency of rescue task demands. A multi-strategy clustering ant colony optimization algorithm (KMACO) is proposed for solution. Specifically, the K-means clustering method is utilized to partition the number of rescue tasks assigned to each UAV. In the ant colony optimization algorithm, a pheromone update strategy and a random evolution strategy are introduced to guide population search directions, thereb... More >

This paper explores factors influencing consumer satisfaction in automotive spare parts e-commerce through text mining and sentiment analysis of Taobao reviews. By applying TF-IDF (Term Frequency-Inverse Document Frequency), semantic network analysis, and LDA (Latent Dirichlet Allocation) topic modeling, four core themes are identified: Logistics, Quality, Price, and Customer Service. A domain-specific sentiment lexicon constructed via the SO-PMI method reveals that positive reviews predominantly emphasize product reliability and logistics efficiency, while negative feedback focuses on installation complexity and inconsistent specifications. Based on these findings, targeted recommendations... More >