基于改进型交互式遗传算法的医疗机械优化设计

Optimization of Design Medical Machine Based on Improved Interactive Genetic Algorithm

针对当前医疗机械设计过程中人性化设计能力差,医疗机械数据库检索能力滞后的问题,提出了新型的医疗机械优化设计方案。该方案通过构建改进型交互式遗传算法模型,融入了极限学习机(ELM)算法,构建出包括数据输入层、隐藏层和输出层的数据架构,通过设置不同的数据节点,实现医疗机械数据库数据的快速分类。再借助于前馈神经网络结构,在多种医疗器械设计库中经过不断的迭代计算,最终实现了医疗机械数据库数据的最终输出。实验表明,本研究精度提高了20%以上,人性化设计元素检索能力强。

The purpose of this research is to address the problem of poor humanized design capabilities and lagging medical machine database retrieval capabilities in the current medical machine design,and propose a new type of medical machine optimization design scheme,which applies the construction of an improved interactive genetic algorithm model.The extreme learning machine(ELM)algorithm is used to construct a data structure including data input layer,hidden layer and output layer.By setting different data nodes,the rapid classification of medical machine database data is realized.With the help of the feedforward neural network structure,after continuous iterative calculations in a variety of medical device design libraries,the final output of the medical machine database data is realized.Experiments show that the accuracy of this method has increased by more than 20%,and the humanized design element retrieval ability is strong.