Anhui University of Finance and Economics

About: Anhui University of Finance and Economics is a education organization based out in Bengbu, China. It is known for research contribution in the topics: China & Hopf bifurcation. The organization has 933 authors who have published 1070 publications receiving 11500 citations. The organization is also known as: AUFE.

Hurwicz model of uncertain optimal control with jump

Abstract: How to choose the optimization criterion of the objective function is an important issue for uncertain optimal control. The Hurwicz criterion is a flexible optimization criterion attempting to find the intermediate area between the extremes posed by the optimistic and pessimistic criteria. Based on uncertainty theory, in this paper, we establish a new uncertain optimal control model with jump by making use of Hurwicz criterion to optimize an uncertain objective function. By applying Bellman's principle of optimality, the principle of optimality for the proposed model is presented and then the equation of optimality is derived. Finally, an example is given to show the the effectiveness of the results obtained.

Energy consumption and economic growth from perspective of spatial heterogeneity: statistical analysis based on variable coefficient model

Abstract: The contradiction between economic development, resources and environment is becoming more and more important every day. Based on the proposed energy conservation, this paper will study whether reducing energy consumption hinders economic growth. This article considers the spatial heterogeneity factors and the different energy consumption levels between different areas. Through empirical analysis, we discuss the quantitative relationship between energy consumption and economic growth from different areas. Finally, we propose long- and short-term strategic arrangements for energy consumption in order to facilitate sustainable development.

High-Quality Economic Development in Huaihe Economic Zone Level Measurement and Evaluation

Abstract: This article constructs a comprehensive evaluation index system from four aspects: economic vitality, innovation efficiency, green development, and people’s lives. Use the entropy method to comprehensively measure the urban competitiveness level of 25 counties and cities in the economic zone, clarify the differences in their high-quality development levels, and use spatial econometric analysis methods to study the spatial agglomeration and dispersion and spatial convergence of regional urban competitiveness. The results show that the following: (1) the overall high-quality development level of the Huaihe River Eco-Economic Zone is not high, and the overall time and space characteristics is “high in the east and low in the west”; (2) there is a positive spatial autonomy in urban competitiveness and the spatial distribution of the Huaihe River, and relevantly, the degree of closeness of spatial associations between cities is generally low; (3) the gap between the level of urban competitiveness in Jiangsu Province is shrinking, the development of other provinces has a time lag effect, and there are differences in the level of urban competitiveness. Finally, to promote the high-quality development of the Huaihe Economic Zone, we must follow the law of the basin and the characteristics of spatial distribution and implement targeted strategies.

Neighborhood Preprocessing SVM for Large-Scale Data Sets Classification

Abstract: Support vector machine (SVM) has been a promising method for data mining and machine learning in recent years. However, the training complexity of SVM is highly dependent on the size of a data set. A preprocessing support vector machines (P-SVM) method for large-scale data set classification is presented to speed up SVM training. By analyzing the neighbor classification feature for each sample in training data set, a decision criterion was built to keep or delete this sample from the original data set without losing the classification. The new method can provide an SVM with high quality samples. Experiments with random data and UCI databases show that SVM with our new preprocessing method retains the high quality of training data set and the classification accuracy very well.

Market segmentation and industry overcapacity considering input resources and environmental costs through the lens of governmental intervention.

Abstract: The problems with China’s regional industrial overcapacity are often influenced by local governments. This study constructs a framework that includes the resource and environmental costs to analyze overcapacity using the non-radial direction distance function and the price method to measure industrial capacity utilization and market segmentation in 29 provinces in China from 2002 to 2014. The empirical analysis of the spatial panel econometric model shows that (1) the industrial capacity utilization in China’s provinces has a ladder-type distribution with a gradual decrease from east to west and there is a severe overcapacity in the traditional heavy industry areas; (2) local government intervention has serious negative effects on regional industry utilization and factor market segmentation more significantly inhibits the utilization rate of regional industry than commodity market segmentation; (3) economic openness improves the utilization rate of industrial capacity while the internet penetration rate and regional environmental management investment have no significant impact; and(4) a higher degree of openness and active private economic development have a positive spatial spillover effect, while there is a significant negative spatial spillover effect from local government intervention and industrial structure sophistication. This paper includes the impact of resources and the environment in overcapacity evaluations, which should guide sustainable development in emerging economies.