A Structural Optimization Design Method Accelerated by Generative Adversarial Networks
A network acceleration and optimization design technology, applied in biological neural network models, neural learning methods, design optimization/simulation, etc., can solve problems such as taking a long time, achieve improved discrimination ability, fast calculation, and reduce computational complexity Effect
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[0025] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments;
[0026] The invention provides a structure optimization design method accelerated by applying generative adversarial network; such as figure 1 As shown, a structure optimization design method using generative adversarial network acceleration includes the following steps: step 1: use SIMP algorithm to prepare data; step 2: use data enhancement technology to expand the data set; step 3: use encoder-decoding step 4: use a deep convolutional network to build a discriminator; step 5: use the deformed pix2pix model for training; step 6: use the final model; the present invention has the advantages of accurately generating an optimized structure, greatly reducing computational complexity, The advantage of reducing computational overhead.
[0027] The steps of the structure optimization design method accelerated by generative adversarial network are as follow...
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