Affiliation:
1. College of Information Science and Technology, Donghua University, Shanghai, P. R. China
Abstract
Ureteral stent tubes are important medical devices used to repair ureteral obstruction or injury. However, relevant experiments of ureteral stent tubes are usually time-consuming and expensive. This research introduces a mechanical model that can simulate the force and deformation of ureteral stents. In addition, a novel optimization algorithm called improved exploration-enhanced gray wolf optimizer (IEE-GWO) is proposed to optimize parameters of the model. In order to balance exploration and exploitation of gray wolf optimizer (GWO), a dimension learning-based hunting (DLH) search strategy and a nonlinear control parameter strategy are integrated into the IEE-GWO. The experimental results show that the proposed IEE-GWO has better performance, such as fast convergence speed and high solution quality. Furthermore, the novel approach can improve the accuracy of the mechanical modal.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Natural Science Foundation of Shanghai
Publisher
World Scientific Pub Co Pte Ltd
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Cited by
1 articles.
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