Application of hybrid kernel function in economic benefit analysis and evaluation of enterprises

[1] Ye Hua. Predicament and Solution of Enterprise Economic Benefit Audit [J]. Times Finance, 2021, (12), 47–49. (in Chinese) Search in Google Scholar

[2] Liu Fengming. Talking about How to Effectively Improve the Economic Benefits of Enterprises by Means of Accounting Audit [J]. Financial and Economic Circle, 2021, (12), 148–149. (in Chinese) Search in Google Scholar

[3] Song Jia. The Application of Multivariate Statistical Analysis in the Economic Benefits of Enterprises [J]. Productivity Research, 2020, (3), 141–143. (in Chinese) Search in Google Scholar

[4] Li Rende, Huang Guoan. Economic Benefit Evaluation of Enterprises Based on Structural Equation Model. Technology and Innovation Management, 2010, (4), 451–454. (in Chinese) Search in Google Scholar

[5] Aminian F, Suarez E D, Aminian M, et al. Forecasting Economic Data with Neural Networks [J]. Computational Economics, 2016, 28(1), 71–88. Search in Google Scholar

[6] Huang H, Jia R, Shi X, et al. Feature Selection and Hyper Parameters Optimization for Short-Term Wind Power Forecast [J]. Applied Intelligence, 2021, 1–19. Search in Google Scholar

[7] Li Guozheng, Wang Meng, Zeng Huajun. Introduction to Support Vector Machine [M]. Electronic Industry Press, 2004, 30–39. (in Chinese) Search in Google Scholar

[8] Han H, Cao Z, Ren B G N. PCA-SVM-Based Automated Fault Detection and Diagnosis (AFDD) for Vapor-Compression Refrigeration Systems [J]. Hvac & R Research, 2010, 16(3). Search in Google Scholar

[9] Liu Ming. Research on Sigmoid Kernel Function in Support Vector Machine [D]. Xidian University Dissertation, 2009. (in Chinese) Search in Google Scholar

[10] Mohamed N. Nounou, Bhavik R. Bakshi, Prem K. Goel, Xiaotong Shen. Improving Principal Component Analysis Bayesian Estimation. Proceedings of the American Control Conference Arlington, 2001, 359–367P. Search in Google Scholar

[11] Dong Yulin, Xia Zunquan, Wang Mingzheng. An MPEC Model for Selecting Optimal Parameter in Support Vector Machines. The First International Symposium on Optimization and Systems Biology, 2007, 351–357. Search in Google Scholar

[12] Li Jingping, Xie Bangchang. Multivariate Statistical Analysis Method and Application [M]. Beijing: China Renmin University Press, 2008. (in Chinese) Search in Google Scholar

[13] Jinbo Bi, Kristin P. Bennett. A Geometric Approach to Support Vector Regression. Neural Computation, 2003, 263–270P. Search in Google Scholar

[14] Zhou Zun. Research on Coal Mine Safety Economic Benefit and Coal Mine Management Countermeasures [J]. Modern Economic Information, 2015, (14). (in Chinese) Search in Google Scholar

[15] Yong Wang, Yan Hong, Li Linfeng. Analysis and Evaluation of Economic Benefits of Enterprise Informatization [J]. Modern Information, 2006, (02), 160–163. (in Chinese) Search in Google Scholar

[16] Shi Luan. Introduction to the Analysis Method of Enterprise Economic Benefit [J]. Breeding Technical Consultant, 2010, (08), 207. (in Chinese) Search in Google Scholar

[17] Yan Kongxiao. Decision-Making and Evaluation Analysis of Economic Benefits of Construction Enterprises [J]. China Collective Economy, 2020, (34), 26–27. (in Chinese) Search in Google Scholar

[18] Chen Hnog-Gunn, Crisp D J, Bongner R E. Target Detection in Radar Imagery Using Support Vector Machines with Training Size Biasing. Proceeding of the Sixth International Conference on Control, Automation, Robotics and Vision, Singapore, 2000, 221–228P. Search in Google Scholar

[19] Li Guozheng, Wang Meng, Zeng Huajun. Introduction to Support Vector Machines. Electronic Industry Press, 2004, 3, 30–39. (in Chinese) Search in Google Scholar

[20] Su In L, Batzoglou S. Application of Independent Component Analysis to Microarrays. Genome Biology, 2003, 189–196P. Search in Google Scholar

[21] Cao Hongcui, Wu Qixun. Principal Component Analysis and Cluster Analysis of Trace Elements in Glycyrrhiza uralensis Fisch. Journal of Gansu Union University, 2010, 24(2), 61–63. (in Chinese) Search in Google Scholar

[22] Smits G F, Jordan E M. Improved SVM Regression Using Mixtures of Kernels. Proceedings of the 2002 International Joint Conference on Neural Networks, 2002, 2785–2790P. Search in Google Scholar