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Integrating multiple adaptation results by utilization of support vector regression in case-based mechanical product design:

机译:在基于案例的机械产品设计中利用支持向量回归来整合多个适应结果:

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Case adaptation is crucial for a good and reasonable case-based design which is a common method in computer-aided design, because the solution of old case is not always the exact answer for the encountered new designing problem. Recently, a statistical feature-oriented adaptation method in the principle of k-nearest neighbors has been employed widely in case-based design because of its easily understandable mechanism for designers, but its adaptation accuracy is relatively low compared with knowledge-intensive method. This article presents a new method by integrating with multiple adaptation values from statistical feature-oriented adaptation methods to improve the adaptation accuracy. First, two simple statistical feature-oriented adaptation methods including mean and median approaches and other four statistical feature-oriented adaptation methods based on Euclidean distance, Manhattan distance, Gaussian transformation, and gray coefficient are used as individual statistical feature-oriented adaptation m...
机译:案例修改对于良好且合理的基于案例的设计至关重要,这是计算机辅助设计中的一种常用方法,因为旧案例的解决方案并不总是解决遇到的新设计问题的确切答案。近年来,基于k近邻原理的面向统计特征的自适应方法由于其对于设计者的易于理解的机制而被广泛应用于基于案例的设计中,但是与知识密集型方法相比,其自适应精度相对较低。本文提出了一种新方法,该方法通过与面向统计特征的自适应方法中的多个自适应值相集成来提高自适应精度。首先,将两种简单的面向统计特征的自适应方法(包括均值和中值方法)以及其他四种基于欧氏距离,曼哈顿距离,高斯变换和灰度系数的面向统计特征的自适应方法用作个体统计面向特征的自适应m。 。

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