为了解决带预应力的组合结构拓扑优化问题，提出了组合结构优化算法的基本思想。

In order to deal with the problem of combined structural topology optimization, a basic algorithm idea is proposed.

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本文从神经网络模型的结构出发，对学习算法提出了一系列改进和优化措施，以加快网络的学习速度，并增加模型的稳定性。

With the study of neural network model, this paper advances some of improvement and optimization techniques that can accelerate the learning speed of network and increase the stability of model.

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而后结合频率灵敏度，基于渐进结构优化方法，建立了一套优化准则和算法。

Then, a set of optimization criteria and algorithms are set up based on frequency sensitivity and evolutionary structural optimization methods.

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