Time Series Forecasting with Quantum Neural Networks

被引：0
|
作者：
Cuellar, M. P. [1 ]
Pegalajar, M. C. [1 ]
Ruiz, L. G. B. [2 ]
Cano, C. [1 ]
机构：
[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada, Spain
[2] Univ Granada, Dept Software Engn, Granada, Spain
来源：
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2023, PT I | 2023年 / 14134卷
关键词：
Quantum Neural Networks; Quantum Machine Learning; Time Series Forecasting;
D O I：
10.1007/978-3-031-43085-5_53
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work we explore the use of Quantum Computing for Time Series forecasting. More specifically, we design Variational Quantum Circuits as the quantum analogy of feedforward Artificial Neural Networks, and use a quantum neural network pipeline to perform time series forecasting tasks. According to our experiments, our study suggests that Quantum Neural Networks are able to improve results in error prediction while maintaining a lower number of parameters than its classical machine learning counterpart.
引用
收藏
页码：666 / 677
页数：12
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