基因表达编程技术的180度弯曲浸没导向板附近腐蚀范围确定研究（英文）

Submerged vanes are installed on rivers and channel beds to protect the outer bank bends from scouring. Also, local scouring occurs around the submerged vanes over time, and identifying the effective factors on the scouring phenomena around these submerged vanes is one of the important issues in river engineering. The most important aim of this study is investigation of scour pattern around submerged vanes located in 180° bend experimentally and numerically. Firstly, the effects of various parameters such as the Froude number(Fr), angle of submerged vanes to the flow(α), angle of submerged vane location in the bend(θ),distance between submerged vanes(d), height(H), and length(L) of the vanes on the dimensionless volume of the scour hole were experimentally studied. The submerged vanes were installed on a 180° bend whose central radius and channel width were 2.8 and 0.6 m, respectively. By reducing the Froude number, the scour hole volume decreased. For all Froude numbers, the biggest scour hole formed at θ = 15°. In all models, by increasing the Froude number, the scour hole volume significantly increases. In addition, by increasing the submerged vanes' length and height, the scour hole dimensions also grow. Secondly,using gene expression programming(GEP), a relationship for determining the scour hole volume around the submerged vanes was provided. For this model, the determination coefficients(R~2) for the training and test modes were computed as 0.91 and 0.9,respectively. In addition, this study performed partial derivative sensitivity analysis(PDSA). According to the results, the PDSA was calculated as positive for all input variables.     

A behavioral housing search model: Two-stage hazard-based and multinomial logit approach to choice-set formation and location selection

Residential location search has become an important topic to both practitioners and researchers as more detailed and disaggregate land-use and transportation demand models are developed which require information on individual household location decisions. The housing search process starts with an alternative formation and screening stage. At this level households evaluate all potential alternatives based on their lifestyle, preferences, and utilities to form a manageable choice set with a limited number of plausible alternatives. Then the final residential location is selected among these alternatives. This two-stage decision making process can be used for both aggregate zone-level selection as well as searching disaggregate parcel or building-based housing markets for potential dwellings. In this paper a zonal level household housing search model is developed. Initially, a household specific choice set is drawn from the entire possible alternatives in the area based on the average household work distance to each alternative. Following the choice set formation step, a discrete choice model is utilized for modeling the final residential zone selection of the household. A hazard-based model is used for the choice set formation module while the final choice selection is modeled using a multinomial logit formulation with a deterministic sample correction factor. The approach presented in the paper provides a remedy for the large choice set problem typically faced in housing search models.     

Travellers’ perceptions of travel time reliability in the presence of rare events

Transportation - Travellers account for variability in transport system performance when they make choices about routes, modes and destinations. Modellers try to quantify travel time reliability...     

Household travel attributes transferability analysis: application of a hierarchical rule based approach

This paper presents a system of hierarchical rule-based models of trip generation and modal split. Travel attributes, like trip counts for different transportation modes and commute distance, are among the modeled variables. The proposed framework could be considered as an alternative for several modules of the traditional travel demand modeling approach, while providing travel attributes at the highly disaggregate level that can be also used in activity-based micro-simulation modeling systems. Nonetheless, the modeling framework of this study is not considered as a substitute for activity-based models. The explanatory variables set ranges from socio-economic and demographic attributes of the household to the built environment characteristics of the household residential location. Another important contribution of the study is a framework in which travel attributes are modeled in conjunction with each other and the interdependencies among them are postulated through a hierarchical system of models. All the models are developed using rule-based decision tree method. Moreover, the models developed in this study present a useful improvement in increasing the practicality and accuracy of the rule-based travel data simulation models.