No abstract

Attribute reduction is viewed as a kind of preprocessing steps for reducing large dimensionality in data mining of all complex systems. A great deal of researchers have proposed various approaches to reduce attributes or select key features in multicriteria decision making evaluation. In practice, the existing approaches for attribute reduction focused on improving the classification accuracy or saving the cost of computational time, without considering the influence of the reduction results on the original data set. To help address this gap, we develop an advanced novel attribute reduction approach combining Pearson correlation analysis with test significance discrimination for the screening and identification of key characteristics related to the original data set. The proposed model has been verified using the financing ability evaluation data of 713 small enterprises of a city commercial bank in China. And the experimental results show that the proposed reduction model is efficient and effective. Moreover, our experimental findings help to locate the qualified partners and alleviate the difficulties faced by enterprises when applying loan.

No abstract

While promoting the global economy and trade, ports impose serious pollution on the global ocean and atmosphere. Therefore, the development of ports is restrained by the policies and measures of governments and international organizations used to cope with climate change and environmental protection. With the development of information technology, the operation and expansion of ports is facing forms of green and intelligent reform. This research aims to link the development of green intelligent ports, government policies, and third-party organizations to find the most suitable evolutionary path for the development of green intelligent ports. This paper assumes that governments will push ports to transform into green intelligent ports from the perspective of benefiting long-term interests, that the goal of ports is to maximize their profits, and that third-party organizations will actively promote the development of green intelligent ports. Based on these assumptions, this paper has established an evolutionary game theory model of “government–port–third-party organization” regarding the development of green intelligent ports. The Jacobian matrix of the game theory system was constructed by using the replicator dynamic equation, and local stability analysis was performed to obtain the equilibrium stability point of the entire system. This research reveals the limitations of the development of green intelligent ports without government involvement and explores the ability of third-party organizations to promote the implementation of policies, confirming the role of government regulation and control in promoting the development of green intelligent ports. This paper may be helpful for the development of green intelligent ports in the future. The results show that: (1) The main factors affecting the choice of port strategy are the benefits of building a green intelligent port, the intensity of government regulation, and the quantitative influence of third-party evaluation results on the port strategy selection. (2) Government decision-making plays an important role in port transformation. If the relevant government chooses the wrong strategy, then the transformation of the port will be delayed. (3) Government regulation and control need to change with the change of the evolution stage. (4) Compared with the macro-control policies of the government, the influence of the third-party organization on the port is significantly smaller.