[1] Kang M G, Cho I, Park J et al. High accuracy real-time multi-gas identification by a batch-uniform gas sensor array and deep learning algorithm[J]. ACS Sensors, 7, 430-440(2022).

[2] Wang S T, Wang C B, Pan Z et al. Applications of optical technology in gas concentration detection[J]. Opto-Electronic Engineering, 44, 862-871(2017).

[3] Li J, Yan H, Meng J. Research progress of gas absorption spectrum detection technology based on photonic crystal fiber[J]. Optics and Precision Engineering, 29, 2316-2329(2021).

[4] Bremer K, Pal A, Yao S et al. Sensitive detection of CO2 implementing tunable thulium-doped all-fiber laser[J]. Applied Optics, 52, 3957-3963(2013).

[5] Jiao X F, Sun P, Guan J G et al. Summary of carbon dioxide detection technology based on TDLAS[J]. Measurement & Control Technology, 41, 1-8(2022).

[6] Liu K, Liu T G, Jiang J et al. Investigation of wavelength modulation and wavelength sweep techniques in intracavity fiber laser for gas detection[J]. Journal of Lightwave Technology, 29, 15-21(2011).

[7] Feng S B, Farha F, Li Q J et al. Review on smart gas sensing technology[J]. Sensors, 19, 3760(2019).

[8] Shi Y J, Wu H T, Liu W H et al. Design of wireless electronic nose based on near infrared spectral absorption technology[J]. Infrared and Laser Engineering, 51, 20210374(2022).

[9] Shan J F, Liu K, Jiang J F et al. Application of support vector machine in quantitative analysis of mixed gas[J]. Acta Optica Sinica, 43, 1206001(2023).

[10] Zhao X J, Wen Z H, Pan X F et al. Mixture gases classification based on multi-label one-dimensional deep convolutional neural network[J]. IEEE Access, 7, 12630-12637(2019).

[11] Song L M, Wu H, Yang Y G et al. Application of deep learning in quantitative analysis of the infrared spectrum of logging gas[J]. Applied Optics, 59, E9-E16(2020).

[12] Li C C, Luo Q W, Zhang Y Y. Determination of net photosynthetic rate of plants based on environmental compensation model[J]. Spectroscopy and Spectral Analysis, 42, 1561-1566(2022).

[13] Wang J, Chen B Y, Cheng Y. Rainfall forecast based on multi-task long-short convolution computing network[J]. Computer Engineering and Design, 43, 2686-2693(2022).

[14] Baev V M, Latz T, Toschek P E. Laser intracavity absorption spectroscopy[J]. Applied Physics B, 69, 171-202(1999).

[15] LeCun Y, Boser B, Denker J S et al. Backpropagation applied to handwritten zip code recognition[J]. Neural Computation, 1, 541-551(1989).

[16] Yi J Z, Chen J S, Zhou M N et al. Analysis of stock market public opinion based on web crawler and deep learning technologies including 1DCNN and LSTM[J]. Arabian Journal for Science and Engineering, 48, 9941-9962(2023).

[17] Peng D D, Liu Z L, Wang H et al. A novel deeper one-dimensional CNN with residual learning for fault diagnosis of wheelset bearings in high-speed trains[J]. IEEE Access, 7, 10278-10293(2018).

[18] Wang H C, Liu C, Du W L et al. Intelligent diagnosis of rotating machinery based on optimized adaptive learning dictionary and 1DCNN[J]. Applied Sciences, 11, 11325(2021).

[19] Wang L, Zhang X D, Dai H. Fault diagnosis of pumping unit based on 1D-CNN-LSTM attention network[J]. Computer and Modernization, 1-6(2023).

[20] Caruana R. Learning many related tasks at the same time with backpropagation[EB/OL]. https://www.semanticscholar.org/paper/Learning-Many-Related-Tasks-at-the-Same-Time-with-Caruana/210da45e57f86a50c04bdd7b37d498c8ecc288da

[21] Caruana R. Multitask learning[J]. Machine Learning, 28, 41-75(1997).