Along with the development of intelligent transportation information system, intelligent public transportation system is gradually popularized. Such information system is designed to provide all kinds of real-time information to transit passengers on the conditions of the network, and hence affect passengers’ travel choice behavior and improve passenger travel convenience and flexibility, so as to improve the social benefit and service level of the public transit system. Concerning the particularity of the transit network, with electronic bus stop information of Chengdu as an example, a questionnaire was designed to investigate passengers’ route choice behavior and travel intention. Qualitative and quantitative analysis and random utility theory were adopted，based on Logit model and mixed Logit model, route choice models were established, using characteristic variables of various options and passengers’ personal socio-economic attributes as explanatory variables. The method of Monte Carlo simulation and maximum likelihood were used to estimate parameters. The results indicate that the differences of route choice behavior resulting from individual preferences can be reasonably interpreted by mixed Logit model, which helps us better understand the complexity of transit behavior, so as to guide the application.

Concerning the special nature of the transit network, the generalized path concept that maybe easily describe passenger route choice behavior was put forward. The key cost of each path was considered. Based on the analytical framework of cumulative prospect theory and passengers' perception, a stochastic user equilibrium assignment model was developed. A simple example revealed that the limitations of the traditional method can be effectively improved by this proposed method. The basic assumption of complete rationality in traditional model was improved. It helped us enhance our understanding of the complexity of urban public transportation behavior and the rule of decision-making. The facility layout and planning of the public transportation can be determined with this result, as well as the evaluation of the level of service. In addition, it can also be used as valid data support for traffic guidance.

security devices(e.g.firewalls,IDS’s,anti-virus tools etc) that have been widely adopted in enterprise environments may generate huge amounts of independent,raw attack alerts,which are characterized by high false positive ratio and false negative ratio.As a result,it is difficult for users to understand these alerts and respond correspondingly.Therefore,handling the huge number of alerts produced by security devices is becoming a critical and challenging task in network security research.A general approach for solving this problem is to do some correlation analysis with these alerts and build attack scenario.A general survey of the contemporary alerts correlation algorithms was given in this paper by a straight forward classification paradigm,and some problems for future research were addressed.