Determining Frictional Characteristics of Human Ocular Surfaces by Employing BSG-Starcraft of Particle Swarm Optimization
Determining Frictional Characteristics of Human Ocular Surfaces by Employing BSG-Starcraft of Particle Swarm Optimization
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利用粒子群优化的 BSG-Starcraft 确定人眼表面的摩擦特性
DOI：
10.11159/jbeb.2017.005
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Y. Ohashi
中科院分区：
文献类型：
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作者：
S. Pranoto;S. Okamoto;Jae Hoon Lee;A. Shiraishi;Yuri Sakane;Y. Ohashi
本研究的主要目的是确定人类眼表的摩擦特性。提出了摩擦系数的数学模型。模型的参数确定的计算算法采用BSG（太空堡垒卡拉狄加）-星际争霸的粒子群优化（PSO）。本研究也旨在显示有效性的计算算法采用BSG-星际的PSO和算法采用遗传算法和最小二乘法在作者的前期研究中开发的。利用自行研制的物理装置，对健康人眼表的法向力、摩擦力和探针速度进行了同步测量。然后，利用现有的计算算法和已有的计算算法计算了人眼表面的摩擦特性曲线。最后，通过比较两种算法在角膜和球结膜摩擦特性上的计算结果，验证了两种算法的有效性。作者成功地确定了人眼表面的摩擦特性。
The main purpose of this research is to determine frictional characteristics of human ocular surfaces. A mathematical model for frictional coefficients was proposed. Parameters of the model were determined by a computational algorithm employing BSG (BattleStar Galactica)-Starcraft of PSO (Particle Swarm Optimization). This research also aims to show validities the computational algorithm employing the BSG-Starcraft of PSO and the algorithm employing the genetic algorithm and least-squares method developed in the authors’ previous research. The physical apparatus developed by the authors in the previous research was used to measure the normal forces, frictional forces and velocities of the probe on eye surfaces of healthy subjects simultaneously. Then, the frictional characteristic curves of human ocular surfaces were calculated by using the present and previous computational algorithms. Finally, both computational algorithms were validated by comparing both results on the frictional characteristics of cornea and bulbar conjunctiva. The authors have succeeded in determining the frictional characteristics of human ocular surfaces.