概率蚁群优化算法与某些迭代方法在求解含卡普托型分数阶导数模型的反问题中的应用比较
Comparison of the Probabilistic Ant Colony Optimization Algorithm and Some Iteration Method in Application for Solving the Inverse Problem on Model With the Caputo Type Fractional Derivative.
作者信息
Brociek Rafał, Chmielowska Agata, Słota Damian
机构信息
Department of Mathematics Applications and Methods for Artificial Intelligence, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, Poland.
出版信息
Entropy (Basel). 2020 May 15;22(5):555. doi: 10.3390/e22050555.
This paper presents the algorithms for solving the inverse problems on models with the fractional derivative. The presented algorithm is based on the Real Ant Colony Optimization algorithm. In this paper, the examples of the algorithm application for the inverse heat conduction problem on the model with the fractional derivative of the Caputo type is also presented. Based on those examples, the authors are comparing the proposed algorithm with the iteration method presented in the paper: Zhang, Z. An undetermined coefficient problem for a fractional diffusion equation. 2016, .
本文提出了用于求解含分数阶导数模型反问题的算法。所提出的算法基于实数蚁群优化算法。本文还给出了该算法应用于具有卡普托型分数阶导数模型的逆热传导问题的实例。基于这些实例，作者将所提出的算法与论文《Zhang, Z. An undetermined coefficient problem for a fractional diffusion equation. 2016, .》中提出的迭代方法进行了比较。
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