Predicting cervical hyperextension injury: A covariance guided sine cosine support vector machine

• Main Authors: Liu, G., Jia, W., Wang, M., Heidari, A.A., Chen, H., Luo, Y., Li, C.
• Other Authors: INSTITUTE OF SYSTEMS SCIENCE
• Format: Article
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Subjects: cervical hyperextension injury; covariance; opposition-based learning; sine cosine algorithm; Support vector machine
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/200534
• Institution: National University of Singapore

10.1109/ACCESS.2020.2978102