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中文摘要：
提出了一种基于试验数据的多目标直接优化方法，该方法采用均匀设计原理安排试验方案，利用三维CAD模型的参数化驱动特点，完成虚拟试验过程和数据获取，以试验数据为训练样本，建立了CAD模型参数与目标之间的非线性映射关系的神经网络模型，运用Pareto遗传进化算法和小生境技术对CAD模型进行多目标参数优化，可在指定区域内找出CAD模型的Pareto最优解集。
英文摘要：
A multi-objective direct optimization method based on uniform design and NN-GA was proposed. This method dealed with test project using uniform design principle, utilizing drive characteristics about 3D CAD model, accomplished virtual testing course and data collecting. On the basis of this, taking these data as training sample, a neural network model of nonlinear mapping rela tions between parameter and object of CAD model was established. Applying Pareto genetic algorithm and niche technique, Multi-Objective Parameters Optimization of CAD model was done. A Paretooptimal set of CAD model can be found in specific extent.
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Synchronization of two non-identical coupled exciters in a non-resonant vibrating system of linear m
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