基于多目标优化的病态逆问题求解

针对科学和工程研究中的病态逆问题,提出了基于多目标优化的求解方法.该方法将各次观测所得问题方程组残差作为多目标,并进一步将该多目标转化为单一目标,通过遗传算法寻求问题最优解,从而利用多次观测的有效信息,达到稳定病态逆问题解的目的.数值算例表明,该方法在参数反演精度和抗噪方面,显著优于最小二乘法(LS);在中、低噪声水平上的相关性态优于Tikhonov正则化方法.     

雷克萨斯LS400型轿车防盗报警系统

介绍雷克萨斯（凌志）LS400型轿车防盗报警系统的设定及消除方法,以及该系统工作状态的检查方法和常见故障诊断。     

城轨车辆LS型锁闭机构外挂密封门研究与分析

介绍了国内城轨车辆LS型锁闭机构外挂密封门的结构和原理,从门扇占用空间、乘客拥挤受力等方面对其与外挂移门和塞拉门进行了分析比较,归纳了该门的特点,为车门选型提供了参考。     

Automatic calibration of fundamental diagram for first‐order macroscopic freeway traffic models

Despite its importance in macroscopic traffic flow modeling, comprehensive method for the calibration of fundamental diagram is very limited. Conventional empirical methods adopt a steady state analysis of the aggregate traffic data collected from measurement devices installed on a particular site without considering the traffic dynamics, which renders the simulation may not be adaptive to the variability of data. Nonetheless, determining the fundamental diagram for each detection site is often infeasible. To remedy these, this study presents an automatic calibration method to estimate the parameters of a fundamental diagram through a dynamic approach. Simulated flow from the cell transmission model is compared against the measured flow wherein an optimization merit is conducted to minimize the discrepancy between model‐generated data and real data. The empirical results prove that the proposed automatic calibration algorithm can significantly improve the accuracy of traffic state estimation by adapting to the variability of traffic data when compared with several existing methods under both recurrent and abnormal traffic conditions. Results also highlight the robustness of the proposed algorithm. The automatic calibration algorithm provides a powerful tool for model calibration when freeways are equipped with sparse detectors, new traffic surveillance systems lack of comprehensive traffic data, or the case that lots of detectors lose their effectiveness for aging systems. Furthermore, the proposed method is useful for off‐line model calibration under abnormal traffic conditions, for example, incident scenarios. Copyright © 2015 John Wiley & Sons, Ltd.