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中文摘要：
为降低阴性选择算法（NSA）的时间复杂度，提出了一种应用种子个体连续位刺激变异的检测器生成策略：首先随机生成种子检测器集合，根据其与自体的亲和度选定变异个体和变异片段；其次在被选个体的特定基因片段发生刺激。应答变异（SRM），产生新的候选检测器个体；最后应用r位连续匹配准则筛选候选个体生成新的检测器。该策略的算法特点在于利用种子个体和自体集合的模式信息指导变异过程，降低候选检测器与自体的匹配成功率。实验表明，在保持高检测率的同时，种子检测器SRM算法比穷举算法、个体随机变异算法和检测器连续胞体超变异（CSH）算法的生成效率更高。
英文摘要：
A new detector generation strategy, based on seed individuals and contiguous somatic simulating mutation, was proposed to reduce the time complexity of the negative selection algorithm （NSA）. The strategy produces seed detectors and determines the special detectors and gene segment by measuring the affinity between the seed set and the self set, and then a stimulated-response mutation （SRM） occurs in a special gene fragment and the candidate individuals emerge, and finally selects the new competent detectors according to the r-contiguous bit matching rule. The characteristic of the algorithm is that it uses the pattern information to guide the mutation process for reducing the matching rate of candidate individuals. The experimental results show that the algorithm outperforms several similar algorithms based on mutation operator in term of time complexity and coverage.
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