摘要
作者运用改进的遗传算法，拟合了杨州地区１９８５年的麻风年龄患病概率的两极催化模型，并与遗传算法、文献［１］的拟合结果进行比较。结果表明，改进的遗传算法结果较优，可望成为各类医用非线性模型辨识的有效工具。
An improved genetic algorithm was used to fit polarized catalytic model of leprosy age infection rate in Yangzhou region. The results were compared with the fitting ones in reference 1. The result showed that it worked well and was expected to become an effective tool for the discrimination of various medical nonlinear models.
出处
《北京生物医学工程》
北大核心
1995年第1期21-24,共4页
Beijing Biomedical Engineering
关键词
两极催化模型
麻风
流行病学
患病率
Polarized catalytic model
Leprosy age infection rate
Improved genetic algorithm
Fitting.
