摘要
粒子群优化算法（PSO）是一种带有全局随机性质的群体搜索演化算法,鲁棒性强,通过微粒群优化算法同BP算法的结合,解决BP算法收敛速度慢,容易陷入局部最小值的问题,并实验证明PSOBP算法其收敛性能,学习速度和稳定性要优于BP算法。再结合实际需求,以印第安人肝癌疾病为例对PSOBP算法在医学中的应用进行探讨。
Particle swarm optimization algorithm（PSO） is a random search with the global qualitative group evolution algo rithm,,robust,through the particle swarm optimization algorithm with the combination of BP algorithm,BP algorithm to solve slow convergence speed,easy to fall into local minimum problem,and experiment PSOBP algorithm its convergence perfor mance,learning speed and stability is superior to BP algorithm.Combined with the actual demand to Indian liver disease as an ex ample to PSOBP algorithm in the application of medicine were discussed.
作者
叶财智
唐德玉
YE Cai-zhi,TANG De-yu（College of Medical Information Engineering,Guangdong Pharmaceutical University,Zhongshan 510000,China）
出处
《电脑知识与技术》
2013年第3期1689-1693,共5页
Computer Knowledge and Technology
关键词
粒子群算法
BP算法
PSOBP算法
印第安人肝癌
医学应用
Particle swarm optimization algorithm
BP algorithm
PSOBP algorithms
Indian liver cancer
medical applications
