Affiliations: [a] School of Economics and Management, Northwest University, Post-Doctoral, Xi’An, China
| [b] School of Management, Yulin University, Associate Professor, Yulin, China
Abstract: In order to effectively improve the accuracy of related analysis models in the application of government risk investment, a government risk investment prediction model based on fuzzy clustering discrete algorithm is put forward in this paper. First of all, government risk investment problem is analyzed. Based on Markowitz theory, the general government risk investment model is considered, and the market value constraint and the upper bound constraint are combined to improve the government risk investment model and obtain the mixed constraint government risk investment model. Secondly, the fuzzy clustering discrete algorithm is introduced in the analysis process of government venture investment model, and it is used to solve the mixed constraint analysis model of government venture investment. In addition, to further improve the performance of discrete algorithm based on fuzzy clustering in the model solving process, automatic contraction and expansion of factors is used to carry out adaptive learning of related parameters based fuzzy clustering discrete algorithm, and improve the convergence of the algorithm. Finally, the simulation experiments on some stock samples of investment sector show that the algorithm in this paper can obtain more ideal government venture investment schemes, so as to reduce investment risk and obtain greater investment returns.
Keywords: International perspective, enterprise innovation, fuzzy clustering, discrete equilibrium analysis
