Prediction of Blood Glucose Level Using Nonlinear System Identification Approach

Author:

Aljamaan IbrahimORCID,Al-Naib IbraheemORCID

Funder

Deputyship for Research and Innovation, Ministry of Education, Saudi Arabia, through Imam Abdulrahman Bin Faisal University/College of Engineering

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Generative adversarial network-based data augmentation for improving hypoglycemia prediction: A proof-of-concept study;Biomedical Signal Processing and Control;2024-06

2. Nonlinear system identification using modified variational autoencoders;Intelligent Systems with Applications;2024-06

3. Monitoring and Identification of Various Glucose Levels of Diabetes Patients Using Edge Based Machine Learning Approach;Journal of Electrical Engineering & Technology;2023-08-18

4. Nonlinear Identification for Control by Using HARMAX Models;2023 9th International Conference on Control, Decision and Information Technologies (CoDIT);2023-07-03

5. Large‐scale system identification using self‐adaptive penguin search algorithm;IET Control Theory & Applications;2023-06-19

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