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| 广义Sierpiński网络拓扑指数信息熵的研究 |
| Research on Topological Index Information Entropy of Generalized Sierpiński Network |
| 投稿时间：2025-05-14 修订日期：2025-06-19 |
| DOI： |
| 中文关键词: Sierpiński网络 拓扑指数 信息熵 |
| 英文关键词: Sierpiński networks topological indices information entropy |
| 基金项目:安徽省教育厅自然科学基金项目（KJ2020A0478） |
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| 中文摘要: |
| 为理解网络变化规律，本文对广义Sierpiński网络边基于度的划分，运用拓扑指数及信息熵的定义，得到十类拓扑指数信息熵的精确表达，分析其拓扑指数信息熵的特性。结果表明：十类拓扑指数信息熵均随网络演化呈上升趋势，表明网络扩展过程中拓扑复杂性显著增加，整体结构复杂性提升。 |
| 英文摘要: |
| To understand the evolution patterns of networks, this study investigates the degree-based edge partitioning of the generalized Sierpiński network. By applying the definitions of topological indices and information entropy, the exact expressions of ten types of topological index-based information entropies are derived, and their characteristics are analyzed. The results show that all ten types of topological index information entropy exhibit an increasing trend with network evolution, indicating a significant increase in topological complexity and an overall rise in structural complexity during the network expansion process. |
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