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.     

2006年美国进口车新技术一览(下)

2006年美国的进口车带着新技术浪潮到达美国海岸。本田(Honda)本田推出了全新的Civic系列——四门、双门、Si双门和混合动力轿车。由于Civic每年销售超过30万辆,你可以想到将来需要多少维护!混合动力车进行了非常聪明的再设计,因此虽然它在结构配置上没有什么实质的改变,但却将