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This paper develops a mapping approach to explore the relationship between different layers of a multilayer air transport network composed of airway, route, and flight network. A two-step methodology is adopted to investigate the hierarchical structure and mapping relationship of the integrated network. First, the relationship between airway and route network is characterized by a multisource multisink shortest path method based on a generalized incidence matrix. Second, the relationship between route and flight network is formulated by a two-dimension array. A case study of an en route airspace in Lanzhou air traffic control area in China verifies the feasibility of the proposed two-step methodology. [ABSTRACT FROM AUTHOR]

In the study presented in this paper, we built a nonlinear binary integer programming model of a flexible scheduling problem for the Department of Zhejiang Provincial Local Tax Services. One difference between our model and typical ones is that whereas in the latter the number of open windows within each working day is fixed, in our model it is not. We used a variety of integer programming software in an attempt to solve our scheduling model; however, unfortunately we could not find an optimal solution. Thus, we tested all the combinations of different numbers of employees to construct the optimal solution. When we tested our model in the tax office of Lishui City, China, the average waiting time of taxpayers was less than 15 min and the employees working hours were clearly reduced. Thus, a noteworthy improvement in the quality of the service is achieved by the model. [ABSTRACT FROM AUTHOR]

The interacting impact between the crude oil prices and the stock market indices in China is investigated in the present paper, and the corresponding statistical behaviors are also analyzed. The database is based on the crude oil prices of Daqing and Shengli in the 7-year period from January 2003 to December 2009 and also on the indices of SHCI, SZCI, SZPI, and SINOPEC with the same time period. A jump stochastic time effective neural network model is introduced and applied to forecast the fluctuations of the time series for the crude oil prices and the stock indices, and we study the corresponding statistical properties by comparison. The experiment analysis shows that when the price fluctuation is small, the predictive values are close to the actual values, andwhen the price fluctuation is large, the predictive values deviate from the actual values to some degree. Moreover, the correlation properties are studied by the detrended fluctuation analysis, and the results illustrate that there are positive correlations both in the absolute returns of actual data and predictive data. [ABSTRACT FROM AUTHOR]

Based on the stochastic concept for freeway capacity, the procedure of capacity estimation is developed. Due to the fact that it is impossible to observe the value of the capacity and to obtain the probability distribution of the capacity, the product-limit method is used in this paper to estimate the capacity. In order to implement estimation of capacity using this technology, the lifetime table based on statistical methods for lifetime data analysis is introduced and the corresponding procedure is developed. Simulated data based on freeway sections in Beijing, China, were analyzed and the results indicate that the methodology and procedure are applicable and validated. [ABSTRACT FROM AUTHOR]

Data insufficiency has become the primary factor affecting research on income disparity in China. To resolve this issue, this paper explores Chinese income distribution and income inequality using distribution functions. First, it examines 20 sets of grouped data on family income between 2005 and 2012 by the China Yearbook of Household Surveys, 2013, and compares the fitting effects of eight distribution functions. The results show that the generalized beta distribution of the second kind has a high fitting to the income distribution of urban and rural residents in China. Next, these results are used to calculate the Chinese Gini ratio, which is then compared with the findings of relevant studies. Finally, this paper discusses the influence of urbanization on income inequality in China and suggests that accelerating urbanization can play an important role in narrowing the income gap of Chinese residents. [ABSTRACT FROM AUTHOR]

We establish a decision making model for evaluating hydrogen production technologies in China, based on interval-valued intuitionistic fuzzy set theory. First of all, we propose a series of interaction interval-valued intuitionistic fuzzy aggregation operators comparing them with some widely used and cited aggregation operators. In particular, we focus on the key issue of the relationships between the proposed operators and existing operators for clear understanding of the motivation for proposing these interaction operators. This research then studies a group decision making method for determining the best hydrogen production technologies using interval-valued intuitionistic fuzzy approach. The research results of this paper are more scientific for two reasons. First, the interval-valued intuitionistic fuzzy approach applied in this paper is more suitable than other approaches regarding the expression of the decision maker's preference information. Second, the results are obtained by the interaction between the membership degree interval and the nonmembership degree interval. Additionally, we apply this approach to evaluate the hydrogen production technologies in China and compare it with other methods. [ABSTRACT FROM AUTHOR]

At present, the gap of agricultural talents in China is continuously widening, and most enterprises lack agricultural core talents, which has caused great impact on the social economy. To solve this problem, an improved AHP-KNN algorithm is proposed by combining the analytic hierarchy process (AHP) and the optimized K-nearest neighbor algorithm, and an agricultural talent training model is proposed based on this algorithm. The results show that the classification accuracy and classification time of the improved AHP-KNN algorithm are 96.2% and 27.5 seconds, respectively, both of which are superior to the comparison algorithm. The result shows that the classification accuracy of agricultural talents can be improved by using this algorithm. Therefore, the model can be used to classify agricultural talents with the same characteristics into one class, carry out targeted training, and train all-round agricultural talents efficiently and quickly, so as to improve the serious shortage of agricultural talents at present. [ABSTRACT FROM AUTHOR]

To accurately forecast energy consumption plays a vital part in rational energy planning formulation for a country. This study applies individualmodels (BP, GM(1, 1), triple exponential smoothingmodel, and polynomial trend extrapolationmodel) and combination forecastingmodels to predict China's energy consumption. Since area correlation degree (ACD) can comprehensively evaluate both the correlation and fitting error of forecastingmodel, it ismore effective to evaluate the performance of forecastingmodel. Firstly, the forecastingmodel's performances rank in line with ACD. Then ACD is firstly proposed to choose individualmodels for combination and determine combination weight in this paper. Forecast results show that combination models usually have more accurate forecasting performance than individual models. The new method based onACDshows its superiority in determining combination weights, compared with some other combination weight assignment methods such as: entropy weight method, reciprocal of mean absolute percentage error weight method, and optimal method of absolute percentage error minimization. By using combination forecasting model based on ACD, China's energy consumption will be up to 5.7988 billion tons of standard coal in 2018. [ABSTRACT FROM AUTHOR]

The Chinese commodity futures markets neglect the existence of the risk hedge and diversification between futures contracts, thus leading to overcharge futures portfolio holders' maintenance margins. To this end, this paper proposes a new method, namely, the multivariate t-Copula-POT-PSRM method, which combines three models, that is, the multivariate t-Copula, the peaks over threshold (POT), and the power spectral risk measures (PSRM), to set futures portfolios' maintenance margins. In the empirical analysis, we first construct four kinds of futures portfolios and set their maintenance margins by using the new method. Then, we introduce two evaluation indicators, namely, the prudence index (PI) and the opportunity cost index (OCI), to assess the effectiveness of the proposed method. We also compare the outcomes of the two evaluation indicators of the new method with those of the widely used linear additive model. The empirical results show that the new method can, respectively, lower the OCI value of all four kinds of futures portfolios for the In-sample period and theOut-of-sample period without significantly reducing the PI value as against the traditional model, which implies that the proposed method can be used to balance security and investment efficiency in the futures market. [ABSTRACT FROM AUTHOR]

As China's electricity market is facing many problems, the research on power producer's bidding behavior can promote the healthy and sustainable development of China's electricity market. As a special commodity, the "electricity" possesses complicated production process. The instable market constraint condition, nonsymmetric information, and a lot of random factors make the producer's bidding process more complex. Best-response dynamic is one of the classic dynamic mechanisms of the evolutionary game theory, which applies well in the repeated game and strategy evolution that happen among a fewbounded rational players with a quick learning capability. The best-response dynamic mechanism is employed to study the power producer's bidding behavior in this paper, the producer's best-response dynamic model is constructed, and how the producers would engage in bidding is analyzed in detail. Taking two generating units in South China regional electricity market as the example, the producer's bidding behavior by following the producer's best-response dynamic model is verified. The relationships between the evolutionarily stable strategy (ESS) of power producer's bidding and the market demand, and ceiling and floor price as well as biding frequency are discussed in detail. [ABSTRACT FROM AUTHOR]

In order to improve the application area and the prediction accuracy of GM(1,1) model, a novel Grey model is proposed in this paper. To remedy the defects about the applications of traditional Greymodel and buffer operators inmedium- and long-termforecasting, a Variable Weights Buffer Grey model is proposed. The proposed model integrates the variable weights buffer operator with the background value optimized GM(1,1) model to implement dynamic preprocessing of original data. Taking the maximum degree of Grey incidence between fitting value and actual value as objective function, then the optimal buffer factor is chosen, which can improve forecasting precision, make forecasting results embodying the internal trend of original data to the maximum extent, and improve the stability of the prediction. To verify the effectiveness of the proposed model, the energy consumption in China from 2002 to 2009 is used for the modeling to forecast the energy consumption in China from 2010 to 2020, and the forecasting results prove that the GVGM(1,1) model has remarkably improved the forecasting ability of medium- and long-term energy consumption in China. [ABSTRACT FROM AUTHOR]

This paper proposes an estimation method of time-varying beta of price limits. It uses China stock market trading data to estimate time-varying beta and researches on systemic risk in China stock market. By comparing prediction errors of market model, SS market model, and Censored-SS market model, it verifies the effectiveness of Censored-SSmarketmodel. Furthermore it has some meaningful conclusions in China stock market. [ABSTRACT FROM AUTHOR]