免疫算法优化的大气质量评价模型及其应用

Atmospheric Quality Assessment Model Based on Immune Algorithm Optimization and Its Applications

针对传统免疫克隆选择算法搜索精度不高的不足,提出了一种改进的免疫克隆选择算法,即引入疫苗接种策略和局部高斯变异算子的免疫克隆选择算法.在疫苗提取、选取和接种过程中引入轮盘赌选择、二进制位基因位选取和接种策略,克服了传统免疫克隆选择算法没有抗体基因交叉的现象,提高了产生优良抗体的比率;通过引入局部高斯变异算子,利用高斯变异的小步长不断地自适应调整,提高了算法的局部搜索能力.此外,算法还采用了扩大搜索空间策略,避免算法陷入局部极值,提高了算法的全局搜索能力.在此基础上,提出了基于免疫克隆选择算法的大气质量评价模型,并将其应用于大气质量评价领域.实验结果表明,该算法有效地提高了求解问题的精度和执行效率,提出的评价模型具有较好的实用性和应用前景.

Owing to the low search precision of the traditional immune clonal selection algorithm, an improved immune clonal selection algorithm is proposed in this paper, which introduces vaccination strategy and local Gaussian mutation operator. The roulette selection, binary digit gene bit selection and inoculation strategies are all used during the vaccine pick-up, selection, and inoculation. Thus the phenomena without crossover for the genes of the antibody in the traditional immune clonal selection algorithm could be overcome, and the rate of the choiceness antibodies is improved. The local Gaussian mutation operator is also introduced into the improved algorithm. The step of Gaussian mutation operator is applied by self-adaptively adjusting continuously to improve the performance of local search. Besides, expanding search space strategy is applied to avoid getting into the local extremum, so the whole search capability of the proposed algorithm is greatly improved. Furthermore, an atmospheric quality assessment model based on immune clonal selection algorithm is proposed and it is applied to the field of atmospheric quality assessment. The experimental results show that the proposed algorithm could improve the precision and efficiency effectively for the problems to be solved. The proposed assessment model has good practicability and application perspective.