针对节点增加的动态网络，提出一种对应的动态网络社群结构探测算法CDD（Community Struc-ture Detection Algorithm for Dynamic Networks）。CDD算法依据节点加入引起模块性指标变化的情况，对网络节点进行社群划分，从而可以发现网络社群结构随时间的动态变化过程。利用计算机生成数据、Ucinet和Pajek提供的有关网络数据，通过社群结构探测试验表明，CDD算法不但可以对动态网络的社群结构变化进行探测，同样也可以实现静态网络的社群结构探测；与N。G算法和A。N算法等社群结构探测算法相比，算法的速度快，所获得的模块性指标也基本相当。

An algorithm is proposed to detect community structures in social networks. The algorithm begins with a community division based on prior knowledge of the degrees of the nodes and then combines the communities until a clear partition is obtained. In applications such as a computer-generated network, Ucinet networks, and Chinese rural-urban migrants' social networks, the algorithm can achieve higher modularity and greater speed than others in the recent literature.

从故障诊断的模式识别本质出发，利用网络表示故障数据结构，通过网络结构反映故障状态及其特征，把故障诊断聚类问题建模为子网络探测问题，提出基于网络结构分析的故障诊断策略。为了解决子网络划分中数据间相似度测度和划分测度设计这两个重要问题，引入复杂网络社群结构分析中的模块性概念，设计状态区分准则函数，并采用自底向上模块合并层次过程优化准则函数实现故障状态聚类，提出一种基于模块合并的故障诊断聚类算法。通过算法在标准数据集分类和真实压缩机故障系统诊断上的应用，分析相似度测度对算法的影响并验证了算法的性能。试验结果表明，与遗传算法，人工免疫网络等人工智能诊断方法相比，本文提出的算法能以较少的计算耗时，有效提取故障特征，获得理想的诊断正确率。

针对简单小世界算法在优化麓杂函数时出现的停滞现象，提出时搜索进行跟踪、对停滞节点进行更替的策略。对每个搜索节点。从搜索的第1代开始进行跟踪，记录节点在每个传递位置停留的次数，当停滞次数超出设定值时便认为该节点进入停滞状态，在搜索空间中随机生成一个节点替代该停滞节点，以保证搜索的高效性。仿真试验表明，改进算法有效地克服了原算法的停滞现象，与原算法相比，改进算法种群多样性好、优化效率高、鲁棒性强，并具备解决更复杂工糕优化问题的潜能。

Based on tile clonal selection theory and immune memory mcchanism in the natural immune system a novel artificial imnltmc system algorithnl，Clonal Strategy Algorithm based on the Immune Memory(CSAIM)，is proposed in this paper The Mgorithm realizes tile evolution of antibody population and tile evolution of nlenlory unit at the Same time and by using clonal selection operator the global optimal computation can be combined with tile local searching According to amibody antibody(Ab-Ag)affinity and antibody antigen(Ab-Ag)affinity．tile algorithm can allot adaptively the scales of memory unit and antibody population It is proved theoretically that CSAIM is convergent with probability 1 And with the conlputer simulations of eight benchmark functions and one instance of traveling salcsillan problem(TSP)．it is shown thm CSAIM has strong abilities in having high convergence speed enhancing the diversity of the population and avoiding the prenlature convergence to some extent.