用于固定设备盖的高压密封

一种新型受压自紧密封环被设计用于各种实际应用,这包括近海平台的管道系统,满足现有换热器的最小化改造     

Georgia Ports Authority： Faster to Market, Better for Business

The Port of Savannah is the fourth largest container port of the ＂five＇global U.S. ports.     

顶部驱动技术向前推进

更强有力的顶部驱动和革新的下套管技术一包括液体冷却、永磁式同步电机一正在帮助钻井人员在印度海上执行任务     

Book reviews

Road haulage licensing and EC Transport Policy. By K. J. Button. (Aldershot: Gower Publishing Co., 1984.) [Pp.127.] £14.50.

Bicycles and Public Transportation: New Links to Suburban Transit Markets. By Michael A. Replogle. (Bicycle Federation, Washington DC, 1983.) [Pp. 171.] US$15.95.

Urban Transport in ASEAN. By V. Setty Pendakur. (Institute of Southeast Asian Studies — Research Notes and Discussions Papers Series No. 43, 1984.) [Pp. 65] $4.50 ISBN 9971–902–67–2.

The World Railway System. By Bernard de Fontgalland (Cambridge Univerisity Press, 1984.) [Pp. 209.] £16.00.     

Residents’ expectations for new rail stops: optimistic neighborhood perceptions relate to subsequent transit ridership

Transportation - Although complete street policies are proliferating, little is known about how nearby residents perceive and act on their new active transportation opportunities. We survey the...     

A genetic algorithm-based method for improving quality of travel time prediction intervals

The transportation literature is rich in the application of neural networks for travel time prediction. The uncertainty prevailing in operation of transportation systems, however, highly degrades prediction performance of neural networks. Prediction intervals for neural network outcomes can properly represent the uncertainty associated with the predictions. This paper studies an application of the delta technique for the construction of prediction intervals for bus and freeway travel times. The quality of these intervals strongly depends on the neural network structure and a training hyperparameter. A genetic algorithm–based method is developed that automates the neural network model selection and adjustment of the hyperparameter. Model selection and parameter adjustment is carried out through minimization of a prediction interval-based cost function, which depends on the width and coverage probability of constructed prediction intervals. Experiments conducted using the bus and freeway travel time datasets demonstrate the suitability of the proposed method for improving the quality of constructed prediction intervals in terms of their length and coverage probability.