摘要
Logistic方程是研究有限空间内种群增长规律的重要工具之一．本文运用遗传算法拟合logistic曲线，并且比较了各种方法的拟合结果，证明遗传算法具有较强的拟合非线性方程的能力，对生物实验及生态、生理学中诸多非线性曲线的参数估计具有普遍意义．
Logistic equation is one of the most important tools for the study on species growth regularity in a limited space．In this paper，the genetic algorithm is used to determine the values of parameters in Logistic equation that will give the best least-quares fit to a set of data．The comparison of present method with the past shows that the genetic algo rithm has strong ability for fitting non-linear equations,and therefore it may have a wider use in determining the values of parameters of nonlinear curve，in the field of ecology and physiology．
出处
《生物数学学报》
CSCD
北大核心
1995年第1期59-63,共5页
Journal of Biomathematics
