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1篇 您的检索式：作者名="Muhammad Noman Hasan"

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		题名	作者	年代	出处	被引量
	1	Lifetime Prediction of LiFePO_(4) Batteries Using Multilayer Classical-Quantum Hybrid Classifier显示文摘This article presents a multilayer hybrid classical-quantum classifier for predicting the lifetime of LiFePO_(4) batteries using early degradation data.The multilayer approach uses multiple variational quantum circuits in cascade,which allows more parameters to be used as weights in a single run hence increasing accuracy and provides faster cost function convergence for the optimizer.The proposed classifier predicts with an accuracy of 92.8%using data of the first four cycles.The effectiveness of the hybrid classifier is also presented by validating the performance using untrained data with an accuracy of 84%.We also demonstrate that the proposed classifier outperforms traditional machine learning algorithms in classification accuracy.In this paper,we show the application of quantum machine learning in solving a practical problem.This study will help researchers to apply quantum machine learning algorithms to more complex real-world applications,and reducing the gap between quantum and classical computing.	Muhammad Haris Muhammad Noman Hasan Abdul Basit Shiyin Qin	2021	Journal of Quantum Computing2021，3，3：	0

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