变应原免疫治疗(allergen immunotherapy,AIT)被世界卫生组织(world health organization,WHO)证实是唯一可以改变变应性疾病自然进程的治疗方法[1]。AIT由剂量递增和剂量维持两个阶段组成[2]。根据剂量递增阶段的方案不同,又分为传统...变应原免疫治疗(allergen immunotherapy,AIT)被世界卫生组织(world health organization,WHO)证实是唯一可以改变变应性疾病自然进程的治疗方法[1]。AIT由剂量递增和剂量维持两个阶段组成[2]。根据剂量递增阶段的方案不同,又分为传统免疫治疗和快速免疫治疗,后者中集群免疫治疗最为常见。展开更多
Combining the clonal selection mechanism of the immune system with the evolution equations of particle swarm optimization, an advanced algorithm was introduced for functions optimization. The advantages of this algori...Combining the clonal selection mechanism of the immune system with the evolution equations of particle swarm optimization, an advanced algorithm was introduced for functions optimization. The advantages of this algorithm lies in two aspects. Via immunity operation, the diversity of the antibodies was maintained, and the speed of convergent was improved by using particle swarm evolution equations. Simulation programme and three functions were used to check the effect of the algorithm. The advanced algorithm were compared with clonal selection algorithm and particle swarm algorithm. The results show that this advanced algorithm can converge to the global optimum at a great rate in a given range, the performance of optimization is improved effectively.展开更多
文摘变应原免疫治疗(allergen immunotherapy,AIT)被世界卫生组织(world health organization,WHO)证实是唯一可以改变变应性疾病自然进程的治疗方法[1]。AIT由剂量递增和剂量维持两个阶段组成[2]。根据剂量递增阶段的方案不同,又分为传统免疫治疗和快速免疫治疗,后者中集群免疫治疗最为常见。
基金Project(A1420060159) supported by the National Basic Research of China projects(60234030, 60404021) supported by the National Natural Science Foundation of China
文摘Combining the clonal selection mechanism of the immune system with the evolution equations of particle swarm optimization, an advanced algorithm was introduced for functions optimization. The advantages of this algorithm lies in two aspects. Via immunity operation, the diversity of the antibodies was maintained, and the speed of convergent was improved by using particle swarm evolution equations. Simulation programme and three functions were used to check the effect of the algorithm. The advanced algorithm were compared with clonal selection algorithm and particle swarm algorithm. The results show that this advanced algorithm can converge to the global optimum at a great rate in a given range, the performance of optimization is improved effectively.