Open AccessComputer Simulation Evaluation of Financial Risk Based on Cuckoo Search and SVM Algorithm
Author(s) -
Yuze Ma
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1533/3/032045
Subject(s) - cuckoo search , cuckoo , support vector machine , finance , algorithm , computer science , warning system , financial risk , machine learning , data mining , business , particle swarm optimization , zoology , telecommunications , biology
With the rapid development of science and technology, there are more and more large-scale transnational enterprises, which also cause many financial risks. The financial risk level of listed companies will directly affect the sound development of the financial market, which requires listed companies to do a good job in financial risk assessment. However, most of the current financial risks rely on financial statements and other forms, which will be difficult to form a good early warning mechanism. Through the cuckoo search algorithm and SVM algorithm, we can form a new intelligent evolutionary algorithm, which can carry out multi group search and adaptive step size. Through the improved method, we can optimize the parameters of SVM model, which will be applied to the company financial risk assessment. Through the improved cuckoo search algorithm, we can improve the accuracy of financial data classification and prediction, which will better improve the financial environment. First of all, this paper analyzes the algorithm based on cuckoo. Then, this paper analyzes the SVM algorithm. Finally, some suggestions are put forward.