[1] Ping LU, Nageswara LALAM, Mudabbir BADAR et al. Distributed optical fiber sensing: Review and perspective. Applied Physics Reviews, 6, 041302(2019).

[2] Xiaodong SUN, Xiaoxia REN, Lin WANG. Present development situation of optical fiber vibration sensing technology. Industrial Instrumentation and Automation, 21-25(2016).

[3] Xiang ZHONG, Shisong ZHAO, Huaxia DENG. Review of research on Φ-OTDR system based on pulse modulation. Infrared and Laser Engineering, 49, 20200166-202(2020).

[4] Qunjian FU, Miao YU, Tianying CHANG. Summarization of pattern recognition method for phase sensitive optical time domain reflecting system. Infrared and Laser Engineering, 47, 0722001-289(2018).

[5] Isabelle GUYON, André ELISSEEFF. An introduction to variable and feature selection. Journal of Machine Learning Research, 3, 1157-1182(2003).

[6] Yuhua QIN, Xiangqian DING, Huili GONG. High dimensional feature selection in near infrared spectroscopy classification. Infrared and Laser Engineering, 42, 1355-1359(2013).

[7] Aiwu ZHANG, Zhe DONG, Xiaoyan KANG. Feature selection algorithms of airborne LiDAR combined with hyperspectral images based on XGBoost. Chinese Journal of Lasers, 46, 0404003-158(2019).

[8] Kenji KIRA, Larry RENDELL. The feature selection problem: Traditional methods and a new algorithm. Journal of Machine Learning Research, 3, 129-134(1992).

[9] [9] KONONENKO Ig. Estimating attributes: Analysis extensions of RELIEF [C]Proceedings of the European Conference on Machine Learning, 1994: 171182.

[10] [10] HE Xiaofei, CAI Deng, NIYOGI Partha. Laplacian sce f feature ion [C]Proceedings of Advances in Neural Infmation Processing Systems, 2014: 507514.

[11] Hanchuan PENG, Fuhui LONG, Chris DING. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattem Analysis and Machine Intelligence, 27, 1226-1238(2005).

[12] K RON, H J GEORGE. Wrappers for feature subset selection. Artificial Intelligence, 97, 273-324(1997).

[13] Vikas SINDHWANI, Subrata RAKSHIT, Dipti DEODHARE et al. Feature selection in MLPs and SVMs based on maximum output information. IEEE Transactions on Neural Networks, 15, 937-948(2004).

[14] Enzhe YU, Sungzoon CHO. Ensemble based on GA wrapper feature selection. Computers & Industrial Engineering, 51, 111-116(2006).

[15] Jianbo YANG, Kaiquan SHEN, Chongjin ONG et al. Feature selection for MLP neural network: the use of random permutation of probabilistic outputs. IEEE Transactions on Neural Networks, 20, 1911-1922(2009).

[16] Tingting YE, Mingxia LIU, Daoqiang ZHANG. Effective distance based multi-modality feature selection. Pattern Recognition and Artificial Intelligence, 29, 658-664(2016).

[17] Fan HUANG, Xukun ZHANG, Lu SUN. Vibration spectral component analysis based on genetic algorithm and simulated annealing algorithm. Lasers & Optoelectronics Progess, 57, 093001-231(2020).

[18] Min GAN, Li ZHANG. Iteratively local fisher score for feature selection. Applied Intelligence, 51, 6167-6181(2021).