An Automatic Pareto Classifier for the Multiobjective Optimization of an Electrostimulative Acetabular Revision System
An Automatic Pareto Classifier for the Multiobjective Optimization of an Electrostimulative Acetabular Revision System
复制标题
用于电刺激髋臼翻修系统多目标优化的自动帕累托分类器
DOI：
10.1109/tmag.2013.2282993
复制
发表时间：
2014
影响因子：
2.1
通讯作者：
U. van Rienen
中科院分区：
文献类型：
--
作者：
U. Zimmermann;U. van Rienen
在本文中，我们提出了一种用于多目标进化算法的帕累托分类器，用于优化电刺激髋臼修正系统的数值模型。该分类器基于超径向可视化方法，使我们能够从帕累托最优解决方案中自动选择最有效的刺激电极排列，以在髋关节翻修手术后治疗骨盆骨。它基于两个标准：1）所有优化目标的平均性能，2）每个目标函数中为实现该性能而进行权衡的总体强度。
In this paper, we present a Pareto classifier for a multiobjective evolutionary algorithm used to optimize the numerical model of an electrostimulative acetabular revision system. This classifier is based on the hyper-radial visualization method and enables us to automatically choose the most efficient stimulation electrode arrangement from a Pareto amount of optimal solutions to treat the pelvic bone after a hip revision surgery. It is based on two criteria: 1) the average performance concerning all optimization goals and 2) the general strength of tradeoffs in each goal function to achieve this performance.