| 摘要: |
| 将复杂网络视为振子网络，对小世界（WS）网络、Barabasi&Alber（BA）网络和实际的酿酒酵母蛋白质相互作用（PPI）网络的内能和熵进行了分析.分析结果表明：随着网络节点数、连边概率、热浴温度等参数的变化，不同网络的内能和熵的变化趋势差异很大，可以以这种差异来判别网络的类型. |
| 关键词: 振子网络 内能 熵 |
| DOI：10.3969/J.ISSN.1000-5137.2019.05.002 |
| 分类号:N941 |
| 基金项目:上海市自然科学基金（16ZR1447200） |
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| Exploration of the internal energy and entropy in the oscillator network: a case study of small world network and BA network |
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XIAO Qin1, XU Qingxiang2, YANG Huijie3, YAN Jiebing3
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1.College of Sciences, Shanghai Institute of Technology, Shanghai 201418, China;2.Mathematics and Science College, Shanghai Normal University, Shanghai 200234, China;3.Business School, University of Shanghai for Science and Technology, Shanghai 200090, China
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| Abstract: |
| By considering the complex network as oscillator network,the internal energy and entropy were analyzed for small world network,Barabasi & Alber(BA) network,Logistic chaotic series visibility graph and the real saccharomyces cerevisiae protein-protein interaction (PPI) network.The analysis results showed that the variation trends of internal energy and entropy for different networks were changed greatly with parameters such as the number of network nodes,the probability of connecting edges and the hot-bath temperature.Furthermore,the type of the network could be discriminated by such differences. |
| Key words: neton network internal energy entropy |
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