Financial Early Warning System Model Combining Hybrid Semantic Hierarchy with Group Method of Data Handling Neural Network for Detection of Banks’ RisksRead the full article
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Modelling the Spatial Distribution Differences of Compulsory Education Resource
This paper aimed to explore the difference in the spatial distribution of compulsory education resource allocation. Raw data were collected from the 2020 China Statistical Yearbook (county/district level) and Guangxi Province Statistical Yearbook of China. Data analysis was conducted using the entropy method, comprehensive evaluation method, K-means clusters analysis, analysis of variance, and spatial statistical analysis (Moran’s I index). It was determined that there were significant differences in the spatial distribution of compulsory education. The equilibrium degree to mandatory education resource allocation was divided into three classes: high level, medium level, and low level, and each class presented a spatial aggregation effect in the spatial distribution. Compared with the primary schools, the equilibrium degree of junior secondary school was higher. However, the equilibrium fluctuation of junior secondary schools was more significant among different counties/districts. The equilibrium of educational resources of junior secondary schools in the urban areas was higher than that in the rural areas, but there was no significant difference for the primary school.
Bifurcation, Traveling Wave Solutions, and Stability Analysis of the Fractional Generalized Hirota–Satsuma Coupled KdV Equations
In this paper, the bifurcation, phase portraits, traveling wave solutions, and stability analysis of the fractional generalized Hirota–Satsuma coupled KdV equations are investigated by utilizing the bifurcation theory. Firstly, the fractional generalized Hirota–Satsuma coupled KdV equations are transformed into two-dimensional Hamiltonian system by traveling wave transformation and the bifurcation theory. Then, the traveling wave solutions of the fractional generalized Hirota–Satsuma coupled KdV equations corresponding to phase orbits are easily obtained by applying the method of planar dynamical systems; these solutions include not only the bell solitary wave solutions, kink solitary wave solutions, anti-kink solitary wave solutions, and periodic wave solutions but also Jacobian elliptic function solutions. Finally, the stability criteria of the generalized Hirota–Satsuma coupled KdV equations are given.
Equivalent Conditions of Complete th Moment Convergence for Weighted Sums of I. I. D. Random Variables under Sublinear Expectations
We investigate the complete th moment convergence for weighted sums of independent, identically distributed random variables under sublinear expectations space. Using moment inequality and truncation methods, we prove the equivalent conditions of complete th moment convergence of weighted sums of independent, identically distributed random variables under sublinear expectations space, which complement the corresponding results obtained in Guo and Shan (2020).
A Data-Driven Method for Predicting the Cutterhead Torque of EPB Shield Machine
The prediction of cutterhead torque of earth pressure balance (EPB) shield machine is mainly studied. First, the idea of shield tunneling stage division is proposed. The process of shield tunneling from start to stop (or pause) is divided into start-up and stationary driving stages. Using the change point detection method based on linear regression, the separation points between start-up stage and stationary driving stage are identified from the original construction data, and the datasets of the two stages are extracted, respectively. Then, for the start-up stage, the linear regression method is suggested for the cutterhead torque prediction, since there is a strong linear correlation between the key parameters such as the cutterhead torque and the thrust force. Meanwhile, for the stationary driving stage, considering the fact that the key parameters vary smoothly and show obvious inertia, the long short-term memory (LSTM) network method can be used to establish the relationship model between cutterhead torque and other key parameters, such as the thrust force. Through the test experiments of construction data in Zhengzhou, Luoyang, and Dalian shield projects, the results show that the proposed segmented modeling method possesses good adaptability and the cutterhead torque prediction model has high prediction accuracy.
The Influence of Core Technology Capability of High-Tech Industry on Sustainable Competitive Advantage
In order to explore how the core technological capabilities of the high-tech industry affect the sustainable competitive advantage of an enterprise, by consulting a large number of literature studies on sustainable competition, the characteristics of high-tech enterprises were summarized through analysis and sorting and a sustainable competition model was proposed based on market, management, marketing, strategy, and organizational innovation. Through factor analysis, correlation analysis, and structural equations of 266 survey data of related companies, the effectiveness of the model based on the impact of core capabilities of high-tech companies on sustainable competitive advantage was confirmed. The results show that the core competencies of high-tech enterprises’ market recognition, strategic planning, management and operation, full-person marketing, and dynamic marketing directly affect the company’s sustainable competitive advantage. The most important influence on a company’s sustainable competitive advantage is market awareness, and the organizational innovation of the company can also influence the sustainable competitive advantage indirectly, while dynamic marketing can increase the other four capabilities to improve the sustainable competitive advantage of the enterprise. The theoretical model is established to identify the core technological capabilities of high-tech enterprises that can help enterprises effectively identify the core technological capabilities that can form a sustainable competitive advantage and then provide ideas for enterprises to build theoretical research on core technological capabilities.
Director Networks and Cost of Equity Capital: Based on “Busy Director Hypothesis” Analysis
This paper uses the data of Shanghai and Shenzhen A-share-listed companies from 2008 to 2018 to construct the director networks as an indicator to explore the relationship between the company’s director networks and the cost of equity capital and the influence of nature of property rights and the ownership structure on the aforementioned relationship. The research results demonstrate that director networks cannot effectively reduce the cost of equity capital. This conclusion verifies the “busy director hypothesis.” With the increase in the director networks centrality, the increase in the cost of equity capital in non-state-owned listed companies is more significant compared with state-owned listed companies; equity concentration plays a significant negative regulatory role in the director networks centrality and affects the cost of equity capital. Compared with the networks centrality of independent director, the networks centrality of nonindependent director has a stronger negative effect on the cost of equity capital. This article broadens the perspective of corporate governance research and provides new ideas for listed companies to make financing decisions.