alexa Numerical Simulation of a Tumor Growth Dynamics Model U
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
Open Access

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Research Article

Numerical Simulation of a Tumor Growth Dynamics Model Using Particle Swarm Optimization

Zhijun Wang* and Qing Wang
Department of Computer Science, Mathematics and Engineering, Shepherd University, Shepherdstown, USA
Corresponding Author : Zhijun Wang
Department of Computer Science
Mathematics and Engineering
Shepherd University, Shepherdstown
WV 25443, USA
Tel: 1-304-876-5070
E-mail: [email protected]
Received November 20, 2015; Accepted December 01, 2015; Published December 04, 2015
Citation: Wang Z, Wang Q (2015) Numerical Simulation of a Tumor Growth Dynamics Model Using Particle Swarm Optimization. J Comput Sci Syst Biol 9:1 001-005. doi:10.4172/jcsb.1000213
Copyright: © 2015 Wang Z, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Tumor cell growth models involve high-dimensional parameter spaces that require computationally tractable methods to solve. To address a proposed tumor growth dynamics mathematical model, an instance of the particle swarm optimization method was implemented to speed up the search process in the multi-dimensional parameter space to find optimal parameter values that fit experimental data from mice cancel cells. The fitness function, which measures the difference between calculated results and experimental data, was minimized in the numerical simulation process. The results and search efficiency of the particle swarm optimization method were compared to those from other evolutional methods such as genetic algorithms.


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