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中文摘要：
在复杂网络的常规社区察觉途径基于一个 priori 决定的优化，即，预先设计的单个优秀功能。这份报纸为社区察觉建议一条 posteriori 决定途径。途径包括二个阶段：在搜索阶段，一个特殊多客观的进化算法被设计寻找在一跑在不同规模揭示社区结构的一套折衷分区；在决定阶段，三个模型选择标准和可能性矩阵方法被建议帮助决定制造者通过根据他们的质量区分最佳的答案的集合选择更好的答案。在五个合成、真实的社会网络的实验说明那，在一跑，我们的方法能获得许多候选人解决方案，它有效地避免在 priori 决定途径存在的分辨率限制。另外，我们的方法能比那些 priori 决定来临的发现更真、全面的社区结构。
英文摘要：
Conventional community detection approaches in complex network are based on the optimization of a priori decision,i.e.,a single quality function designed beforehand.This paper proposes a posteriori decision approach for community detection.The approach includes two phases：in the search phase,a special multi-objective evolutionary algorithm is designed to search for a set of tradeoff partitions that reveal the community structure at different scales in one run;in the decision phase,three model selection criteria and the Possibility Matrix method are proposed to aid decision makers to select the preferable solutions through differentiating the set of optimal solutions according to their qualities.The experiments in five synthetic and real social networks illustrate that,in one run,our method is able to obtain many candidate solutions,which effectively avoids the resolution limit existing in priori decision approaches.In addition,our method can discover more authentic and comprehensive community structures than those priori decision approaches.
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Hybrid Designing of a Neural System by Combining Fuzzy Logical Framework and PSVM for Visual Haze-Fr
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