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Nature Inspired Computational Technique for the Numerical Solution of Nonlinear Singular Boundary Value Problems Arising in Physiology

机译:生理学中非线性奇异边值问题数值解的自然启发计算技术

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摘要

We present a hybrid heuristic computing method for the numerical solution of nonlinear singular boundary value problems arising in physiology. The approximate solution is deduced as a linear combination of some log sigmoid basis functions. A fitness function representing the sum of the mean square error of the given nonlinear ordinary differential equation (ODE) and its boundary conditions is formulated. The optimization of the unknown adjustable parameters contained in the fitness function is performed by the hybrid heuristic computation algorithm based on genetic algorithm (GA), interior point algorithm (IPA), and active set algorithm (ASA). The efficiency and the viability of the proposed method are confirmed by solving three examples from physiology. The obtained approximate solutions are found in excellent agreement with the exact solutions as well as some conventional numerical solutions.
机译:我们为生理学中出现的非线性奇异边值问题的数值解提供了一种混合启发式计算方法。推导近似解为一些对数S形基础函数的线性组合。拟定了一个表示给定非线性常微分方程(ODE)的均方误差和其边界条件之和的适应度函数。通过基于遗传算法(GA),内部点算法(IPA)和活动集算法(ASA)的混合启发式计算算法对适应度函数中包含的未知可调参数进行优化。通过从生理学上解决了三个例子,证实了所提方法的效率和可行性。发现获得的近似解与精确解以及一些常规数值解非常吻合。

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