Abstract
Enterprise financial crisis warning is on the basis of the existing financial index to construct and run mathematical model to predict the possibility of enterprise financial crisis. Due Based on reviewing research situation of enterprise financial crisis warning both domestic and foreign, a new financial crisis warning model based on support vector data description for risk aversion enterprise is proposed which aims at the ignorance of loss differences caused by model errors from the angle of the usage of financial crisis model by the manager of risk aversion enterprises. The theoretical analysis and empirical study show that the proposed model can reduce the second class of financial crisis warning model errors.
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References
Altman, E.: Financial ratios: discriminant analysis and the prediction of corporate bankruptcy. J. Financ. 23, 589–609 (1986)
Jie, S.: Research on intelligent decision making method of enterprise financial crisis precaution. Doctoral Dissertation of Harbin Institute of Technology (2007)
Tax, D., Duin, R.: Support vector domain description. Pattern Recognit. Lett. 20(11–13), 1191–1199 (1999)
Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. Cambridge University Press, Cambridge (2004)
Chandola, V., Banerjee, A., Kumar, V.: Anomaly detection: a survey. ACM Comput. Surv. (CSUR) 41(3), 15 (2009)
Fiolet, V., Toursel, B.: Distributed data mining. Scalable Comput.: Pract. Exp. 6(1), 99–109 (2005)
Perez, M.S., Sanchez, A., Robles, V., et al.: Design and implementation of a data mining grid-aware architecture. Futur. Gener. Comput. Syst. 23(1), 42–47 (2007)
Baoan, Y., et al.: The application of BP neural network in enterprise financial crisis precaution. 2(2), 50–56 (2001)
Tax, D.M.J., Duin, R.P.W.: Support vector data description. Mach. Learn. 54(1), 45–66 (2004)
Markou, M., Singh, S.: Novelty detection: a review-part 1: statistical approaches. Signal Process. 83(12), 2481–2497 (2003)
Acknowledgment
This work was supported by the National Key research and Development Plan (Grant No. 2018YFB0803504), the National Natural Science Foundation of China under Grant No. 61572153, and the key research topics of economic and social development in Heilongjiang province under Grant No. WY2017048-B.
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Yu, X., Chen, S., Li, Y., Lu, H., Wang, L. (2018). Research on Risk Aversion Enterprise Financial Crisis Warning Based on Support Vector Data Description. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11065. Springer, Cham. https://doi.org/10.1007/978-3-030-00012-7_21
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DOI: https://doi.org/10.1007/978-3-030-00012-7_21
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