Jiangxi University of Finance and Economics

About: Jiangxi University of Finance and Economics is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Fuzzy logic & China. The organization has 2865 authors who have published 3556 publications receiving 41567 citations.

Subjective quality assessment of Screen Content Images

Abstract: Research on Screen Content Images (SCIs) becomes important as they are increasingly used in multi-device communication applications. In this paper, we present a study of subjective quality assessment for distorted SCIs, and investigate which part (text or picture) contributes more to the overall visual quality. We construct a large-scale Screen Image Quality Assessment Database (SIQAD) consisting of 20 source and 980 distorted SCIs. The 11-category Absolute Category Rating (ACR) is employed to obtain three subjective quality scores corresponding to the entire image, textual and pictorial regions respectively. Based on the subjective data, we investigate the applicability of 12 state-of-the-art Image Quality Assessment (IQA) methods for objectively assessing the quality of SCIs. The results indicate that existing IQA methods are limited in predicting human quality judgement of SCIs. Moreover, we propose a prediction model to account for the correlation between the subjective scores of textual and pictorial regions and the entire image. The current results make an initial move towards objective quality assessment of SCIs.

A new trapezoidal fuzzy linear programming method considering the acceptance degree of fuzzy constraints violated

Abstract: The fuzzy linear program has various applications in knapsack problem, investment problem, capital budgeting problem, and transportation problem, etc. Considering the acceptance degree of decision maker that the fuzzy constraints may be violated, this paper develops a new method for the fuzzy linear program in which all the objective coefficients, technological coefficients and resources are trapezoidal fuzzy numbers (TrFNs). The order relationship for TrFNs is firstly given by using the interval expectation of TrFNs. According to the order relationship of TrFNs, the trapezoidal fuzzy linear program is transformed into the interval objective program. Combined with the ranking order relation between intervals and the acceptance degree of fuzzy constraints violated, the interval objective program is further transformed into the bi-objective linear program which is solved by the proposed goal programming approach. The proposed method of this paper is not only mathematically rigorous, but also can sufficiently consider the acceptance degree of the fuzzy constraints violated. The effectiveness and superiority of the proposed method are verified with a fuzzy knapsack problem and an investment problem. Finally, a decision support system is developed for the proposed method.

Exploring the mechanisms of ecological land change based on the spatial autoregressive model: a case study of the Poyang Lake Eco-Economic Zone, China.

Abstract: Ecological land is one of the key resources and conditions for the survival of humans because it can provide ecosystem services and is particularly important to public health and safety. It is extremely valuable for effective ecological management to explore the evolution mechanisms of ecological land. Based on spatial statistical analyses, we explored the spatial disparities and primary potential drivers of ecological land change in the Poyang Lake Eco-economic Zone of China. The results demonstrated that the global Moran’s I value is 0.1646 during the 1990 to 2005 time period and indicated significant positive spatial correlation (p < 0.05). The results also imply that the clustering trend of ecological land changes weakened in the study area. Some potential driving forces were identified by applying the spatial autoregressive model in this study. The results demonstrated that the higher economic development level and industrialization rate were the main drivers for the faster change of ecological land in the study area. This study also tested the superiority of the spatial autoregressive model to study the mechanisms of ecological land change by comparing it with the traditional linear regressive model.

Possibility degree and divergence degree based method for interval-valued intuitionistic fuzzy multi-attribute group decision making

Abstract: This paper investigates an order relation of interval-valued intuitionistic fuzzy values (IVIFVs) based on possibility degree and divergence degree and applies it to multi-attribute group decision making (MAGDM) problems. Firstly, based on the possibility degree of intuitionistic fuzzy values, the possibility degree and divergence degree of IVIFVs are defined to provide a new order relation of IVIFVs. Subsequently in interval-valued intuitionistic fuzzy MAGDM, an intuitionistic fuzzy linear programming model is constructed to derive decision makers' weights. Depending on the construction of membership and non-membership functions, three approaches are developed to solve the constructed intuitionistic fuzzy linear programming model, including the optimistic, pessimistic and mixed approaches. Utilizing decision makers’ weights, the collective decision matrix is obtained. Combining the possibility and divergence degrees of alternatives on attributes, the adjusted possibility distribution matrix for each attribute is constructed and proved to be an interval fuzzy preference relation. Then the attribute weights are determined by the negative distances and the positive distances of adjusted possibility distribution matrices. Using the interval-valued intuitionistic weighted arithmetic aggregation operator, the collective comprehensive values of alternatives are obtained. The ranking order of alternatives is generated according to the proposed order relation of IVIFVs. Therefore, an interval-valued intuitionistic fuzzy MAGDM method is proposed. Finally, the proposed method is implemented on some examples. Validation discussion and comparative analyses of this method is also done to show the effectiveness of the proposed method.