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基于进化算法的非线性热传导方程启发式求解方案

Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

作者信息

Ullah Azmat, Malik Suheel Abdullah, Alimgeer Khurram Saleem

机构信息

Junior Engineer (Instrumentation), Oil & Gas Development Company Limited (OGDCL), Islamabad, Pakistan.

Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad, Pakistan.

出版信息

PLoS One. 2018 Jan 19;13(1):e0191103. doi: 10.1371/journal.pone.0191103. eCollection 2018.

Abstract

In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

摘要

本文采用一种基于两种不同基函数(即对数Sigmoid函数和具有未知参数的伯恩斯坦多项式)的混合启发式方案,以有效地求解非线性热传导方程。所提出的技术将给定的非线性常微分方程转化为一个等效的全局误差最小化问题。使用具有未知参数的适应度函数来构造给定非线性微分方程的试探解。选择遗传算法(GA)与内点算法(IPA)的混合方案来求解最小化问题,并获得未知参数的最优值。通过求解非线性热传导方程验证了所提方案的有效性。将所提方案得到的结果与精确解以及哈尔小波 - 拟线性化技术得到的解进行比较,发现两者结果吻合良好,这证明了所提方案的有效性和可行性。此外,还进行了统计分析以研究所提方案的稳定性和可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5652/5774718/80dca38f4716/pone.0191103.g001.jpg

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