IEEE

Identifying Corporate Financial Fraud using Pearson Universal Kernel function-based Support Vector Machine

Abstract: Corporate Financial fraud has significantly affected the endurable development of the financial industries as the critical issue globally. However, it is slightly difficult to determine the ...
Scientific Research Publishing

Saha, A. (2023). An Empirical Comparison of Linear and Non-linear Classification Using Support Vector Machines. International Journal of Computer Sciences and Engineering, 11 ...

ABSTRACT: Support vector machines are recognized as a powerful tool for supervised analysis and classification in different fields, particularly geophysics. In summary, SVMs are binary classifiers.
Scientific Research Publishing

Kim, H.-C., Pang, S., Je, H. M., Kim, D., & Bang, S. Y. (2003). Constructing Support Vector Machine Ensemble. Pattern Recognition, 36, 2757-2767.

ABSTRACT: Support vector machines are recognized as a powerful tool for supervised analysis and classification in different fields, particularly geophysics. In summary, SVMs are binary classifiers.
IEEE

Research on the Liquor Yield Prediction Model Integrating Hybrid Kernel Support Vector Regression and Dung Beetle Optimizer

Abstract: To enhance the efficiency of liquor production and reduce subjective errors caused by manual operations, this study explores the relationship between production process parameters and yield ...