The dynamic optimization of learning parameters can adjust learning parameters dynamically and select optimal learning parameters.

随后，动态优化学习参数算法动态地调整和选取优化的学习参数。

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Before the optimization modeling, the scaling step technique is used to adjust the structural behavior, and the stability of computational convergence is ensured.

在每一步迭代过程建立优化模型之前，采用射线步技术，调整了结构的性态，保证了收敛的稳定性。

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And optimization technology is used to adjust the ventilation structure dimensions, so that the temperature of each part in the machine can be well distributed.

并利用优化技术调整结构尺寸，使各部件中温度分布趋于均匀。

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Power efficiency and optimization calls for an intelligent combination of the automated monitoring of power conditions and the ability to adjust power, temperatures, computer performance and workloads on the fly.

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