References
- Thomas G. Calderon, John J. Cheh. A roadmap for future neural networks research in auditing and risk assessment[J]. International Journal of Accounting Information Systems, 2002, 03: 203–236. doi: 10.1016/S1467-0895(02)00068-4
- André Machado Caldeiraa, Walter Gassenferthb, Maria Augusta Soares Machadoc, Danilo Jusan Santos. Auditing vehicles claims using fuzzy cotg neural networks[J]. Procedia computer science, 2015, 55: 62–71. doi: 10.1016/j.procs.2015.07.008
- Zhang Qing-ling, Zhu Bao-yan, Analysis and control for T-S fuzzy description systems[M],Beijing : National Defense Industry Press, 2010.
- Kim E, Lee H. New approaches to relaxed quadratic stability codition of fuzzy control systems[J]. IEEE Transaction and Fuzzy Systems, 2000, 8(5) : 523–533 doi: 10.1109/91.873576
- Bai Xian-Sheng, Gao Yue-e. Research on the influence of the financial index of listed companies to non-standard audit opinion [J]. Industrial technology and economy, 2009, 06:145–150.
- Gu Meng, Guo Zhi-yong. Research on impact factors of listed companies’ non-standard audit opinion [J]. China business, 2013, 06: 67–68+70.
- Huang Xiao-bo, Song Peng-lin. Empirical research on impact factors of real estate industry listed companies’ non-standard audit opinion [J]. Business accounting, 2014, 08:46–49.
- Lv Xian-pei, Wang Wei. Empirical research on impact factors of CPA non-standard audit opinion: Industrial empirical evidence from China securities market [J]. Auditing Research, 2007, 01:51–58.
- Lu Yu. Prediction of listed companies’ types of audit opinion based on financial indexes [D]. Jilin University, 2007
- Sun Xiao, Zheng Shi-Qiao. Prediction research of Non-standard audit opinion: Manufacturing industry listed companies data [J]. Accounting communications (Academy version). 2008, 06:74–77.
- Tian Jin-yu. Prediction model of listed companies’ types of audit opinion based on BP neural network [J]. Accounting monthly, 2010, 03:109–110.
- Zhang Yu, Lu Wen-xi, Chen She-ming, Gong Lei. Evaluation of groundwater quality based on T-S fuzzy neural network [J]. Water saving irrigation, 2012, 07:35–38.
- Wang Xin-bo, Su XiaoLing. Comprehensive evaluation of Minqin groundwater quality based on T-S fuzzy neural network [J]. Agricultural research of arid areas, 2013, 01: 188–192+198.
- Hou yue, Prediction of traffic flow based on improved T-S fuzzy neural network [J]. computer science and exploration, 2014, 01:121–126.