Research on Credit Risk Early-Warning for Listed Companies in Chengyu Economic Zone Based on Best Fuzzy Support Vector Machine
Kai Xu, Zongfang Zhou
Available Online November 2016.
- https://doi.org/10.2991/rac-16.2016.82How to use a DOI?
- enterprise credit risk; FSVM; kernel function; Chengyu economic zone; early- warning
- Taking listed companies in Chengyu Economic Zone as an example, this paper introduces the fuzzy algorithm into support vector machine (SVM), constructing the model of fuzzy support vector machine (FSVM) for Credit risk early-warning, which based on four different kernel functions (linear, polynomial, sigmoid and Gauss radial basis) are compared as well as compared with traditional statistical models and other artificial intelligent models. The result of investigation illustrates that FSVM based on Gauss radial basis kernel function is not only superior to that based on other three kernel functions, but also better significantly than traditional statistical models and other artificial intelligent models.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Kai Xu AU - Zongfang Zhou PY - 2016/11 DA - 2016/11 TI - Research on Credit Risk Early-Warning for Listed Companies in Chengyu Economic Zone Based on Best Fuzzy Support Vector Machine BT - 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC-2016) PB - Atlantis Press SP - 513 EP - 518 SN - 1951-6851 UR - https://doi.org/10.2991/rac-16.2016.82 DO - https://doi.org/10.2991/rac-16.2016.82 ID - Xu2016/11 ER -