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Performance Evaluation of Three Kinds of Quantum Optimization

机译:三种量子优化的性能评估

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摘要

Three kinds of quantum optimizations are introduced in this paper as follows: quantum minimization (QM), neuromprphic quantum-based optimization (NQO), and logarithmic search with quantum existence testing (LSQET). In order to compare their fitting ability among three quantum optimizations, the performance evaluation on these methods is implemented for the application of time series forecast. Finally, based on the predictive accuracy of time series forecast the concluding remark will be made to illustrate and discuss these three quantum optimizations.
机译:本文介绍了三种量子优化方法,分别是:量子最小化(QM),神经元基于量子的量子优化(NQO)和带有量子存在性测试的对数搜索(LSQET)。为了在三个量子优化中比较它们的拟合能力,对这些方法的性能进行了评估,以用于时间序列预测。最后,基于时间序列预测的预测准确性,将在结语中说明和讨论这三个量子优化。

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