Volume 3, Issue 5

The law of start-up, acceleration profile and leave-out for queuing vehicles at signal intersections is a fundamental question for the queuing theory, traffic simulation and etc in traffic engineering. This paper investigates the vehicular flow at two protected left-turns by video cameras installed at signal intersections, and checks the accuracy of speed processing software. Based on the statistical analysis and the method of curve fitting, the research team establishes the model of start-up and speed-time profile for the queuing vehicles in the protected left-turns at signal intersections. Then the leave-out time of vehicles is calculated based on the established formulas in these models, which is consistent with the observed leave-out time of vehicles by the video. The developed models proved to be accurate. The paper concludes that the queuing vehicles follow by a linear start after the green light, and the speed-time profile indicates an “S” shape from vehicles starting to reach the stable saturation flow. The speed and the queue sequence of first vehicle of saturation flow are different at different intersections, but the law of start-up of vehicles is the same: The same reaction time for the first vehicle and the same linear start-time interval for the adjacent vehicle in the queue. The relationship of leave-out time and the queue sequence of vehicle is nonlinear before the saturation flow. According to the models developed in this paper, the queue sequence of first vehicle of saturation flow and the law of leave-out time of vehicles can be calculated accurately, which is the fundamental for the queuing theory and the traffic simulation.

The standard semi-supervised support vector machine (S 3 VM) is an unconstrained optimization problem of non-convex and non-smooth, so many smooth methods are applied for smoothing S 3 VM. In this paper, a new smooth semi-supervised support vector machine (SS 3 VM) model , which is based on the biquadratic spline function, is proposed. And, a hybrid Genetic Algorithm (GA)/ SS 3 VM approach is presented to optimize the parameters of the model. The numerical experiments are performed to test the efficiency of the model. Experimental results show that generally our optimal SS 3 VM model outperforms other optimal SS 3 VM models mentioned in this paper.

Considering the fact that China is the world factory, in which the trade of intermediate goods has a relatively high share and especially that the trade of intermediate goods with ASEAN is even higher, it is not suitable to use GDP as the economic mass proxies in the gravity model to estimate trade flows traditionally. This paper, by using the data between China and 10 member states of ASEAN along with other 12 main trading partners of China from 1999 to 2013, constructs China’s bilateral export equation based on the gravity model using new economic mass proxies according to Baldwin and Taglioni, and then calculates the trade potential index of China’s export to the member states of ASEAN by using this equation. The empirical results show that, China’s export trade equation based on new economic mass proxy has stronger explanatory power compared to the standard gravity model by using GDP as economic mass proxy. Therefore, the calculating results of trade potential of China’s export to ASEAN are more convincing.

Based on association rules, this article proposed a method for intelligent recommendation of power supply mode, which helps decision-makers in the selection of many schemes. Firstly, a history database which includes the forecasting models and correlative factors was first built and association rule mining was conducted; then combined with the correlative factors in the designated area, the criteria matching in the rules mined were carried out with CBR technique; finally automatic recommendation of the power supply modes was achieved under the given conditions. By application of an example, it is demonstrated that the proposed method can not only automatically analyze the applicability of power supply modes and the intrinsic relationship between correlative factors but also provide, to some extent, theoretical basis for selection of power supply modes and practical utility for urban distribution network planning.

University-industry collaboration networks consist of heterogeneous subjects; in fact, the interactions among these subjects lead to the emergence of the complex characteristics of university-industry collaboration networks and even to the emergence of the networks themselves. Thus, understanding the behavior that generates university-industry collaboration networks is essential to their construction and optimization. To more fully comprehend this generating behavior, we considered a university-industry collaboration network in the ocean energy industry in China as a case study. Employing the motif analysis method, we analyze the network’s generating behavior from four perspectives: motif characteristics, motif classification, motif combination and motif clustering. Furthermore, we explore agents’ modes of adaptive collaboration — and the causes of such collaborations — and summarize the characteristics and modes of networks’ generating behavior. The results indicate that universities and industries tend to form highly stable and close cooperative relationships. The constraints of the network’s generating behavior — which influences the subjects’ interactions through relational and structural embeddedness — include asymmetric information, resource and cost constraints, risk aversion and geographical constraints. Our research presents the benefits of using the motif analysis method to study the network’s generating behavior and its implications in constructing and optimizing a university-industry collaboration network.

With the transformation of economic growth modes, green growth is becoming the main source of global economic growth for the future. Enterprises are the main carriers of the economic growth in a country or a region, and enterprises’ green growth efficiency determines the regional sustainable growth ability. On this basis, this paper investigates the problem of enterprises’ green growth efficiency in China and identifies the input and output indexes of the green growth using the DEMATEL method. Then, through the super efficiency DEA model, this paper measures the enterprise green growth efficiency of 31 regions in China in the years 2003, 2007 and 2012. In accordance with the four parts, including the East, the Central, the West and the Northeast, this paper completes a spatial and temporal variation analysis. The results show that there is an obvious regional difference in enterprise green growth efficiency in China during the above 3 years. Ranking the average efficiency from high to low, the order is as follows: the West, Central region, the Northeast and the East. Enterprise green growth efficiency shows a rising trend in the Northeast, and other regions show a downward trend. The enterprise green growth efficiency in the East is higher than the national average, and the efficiency in the other regions is less than the national average.

The spatial weights matrix is usually specified to be time invariant. However, when it are constructed with economic/socioeconomic distance, trade /demographic/climatic characteristics, these characteristics might be changing over time, and then the spatial weights matrix substantially varies over time. This paper focuses on power of Moran’s I test for spatial dependence in panel data models with where spatial weights matrices can be time varying (TV-Moran). Compared with Moran’s I test with time invariant spatial weights matrices (TI-Moran), the empirical power of TV-Moran test for spatial dependence are evaluated. Our extensive Monte Carlo simulation results indicate that Moran’s I test with misspecified time invariant spatial weights matrices is questionable; Instead, TV-Moran test has shown superiority in higher power, especially for cases with negative spatial correlation parameters and the large time dimension.

This paper discusses linear quadratic Nash game of stochastic singular time-delay systems governed by Itô’s differential equation. Sufficient condition for the existence of Nash strategies is given by means of linear matrix inequality for the first time. Moreover, in order to demonstrate the usefulness of the proposed theory, stochastic H 2 ∕H ∞ control with multiple decision makers is discussed as an immediate application.