Models of Choosing the Financial Compensation Strategy for Flight Delay

At present, most airlines adopted generally the same amount of compensa- tion strategy when needing to provide financial compensation to all flight delay passengers. However, due to the existence of differences in travel time value, ticket fare, as well as the expectation of compensation for flight delays, the gap between the effect of same amount of compensation and many passengers＇ （especially the high-value ones） expectations is large, it results in that airlines need to pay higher cost of compensation, but the total effect of compensation for passengers are not better. This paper advanced four financial com- pensation strategies for flight delays, summarized their own characteristics, and took into account the interests of both airlines and passengers, built the optimization models of the four financial compensation strategies under the restriction of the airline＇s compensation cost and on the goal of the maximum total effectiveness of the financial compensation to all passengers. Finally, based on the specific circumstances of the flight delays, the paper discussed the method for airline to choose the optimal financial compensation strategy through solving four models and comparing the compensation effectiveness.     

基于递阶遗传算法的一类多旅行商问题优化

针对最小化单个旅行商路程的多旅行商问题,提出了一种递阶遗传算法和矩阵解码方法。该算法根据问题的特点,采用一种递阶编码方案,此编码与多旅行商问题一一对应。用递阶遗传算法优化多旅行商问题不需设计专门的遗传算子,操作简单,并且解码方法适于求解距离对称和距离非对称的多旅行商问题。计算结果表明,递阶遗传算法是有效的,能适用于优化多旅行商问题。     

Robust H∞ filtering for discrete-time systems with Markovian switching and time-delays

The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with modedependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.     

时变时滞系统的灰色预测非线性PID控制

针对时变时滞过程提出一种新的控制结构.在此控制结构中,利用遗传算法自动跟踪系统的时滞变化,由灰色预测模型根据辨识的时滞提前预测出系统的输出,而系统的预测输出与输入的偏差以及偏差变化率为非线性PID控制器的输入.仿真结果验证了这种结构能很好地满足时变时滞系统的快速动态响应和稳定性要求.     

磨矿分级过程多模型智能控制研究

提出了一种非线性多模型控制算法,在若干平衡点附近首先建立多个子模型及相应的控制器,再通过在线计算模型匹配度来适应模型参数的变化,被控对象的最终输入是各控制器输出的加权和.将其应用于磨矿分级非线性系统的控制研究,仿真结果表明,所提算法极大地改善磨矿分级系统的动态响应,并增强了系统的鲁棒性.     

Adaptive broadband beamformer for nonuniform linear array based on second order cone programming

Adaptive broadband beamforming is a key issue in array applications. The adaptive broadband beamformer with tapped delay line (TDL) structure for nonuniform linear array (NLA) is designed according to the rule of minimizing the beamformer's output power while keeping the distortionless response (DR) in the direction of desired signal and keeping the constant beamwidth (CB) with the prescribed sidelobe level over the whole operating band. This kind of beamforming problem can be solved with the interior-point method after being converted to the form of standard second order cone programming (SOCP). The computer simulations are presented which illustrate the effectiveness of our bearaformer.     

Design and performance analysis of networked control systems with random delay

The design and performance analysis of networked control systems with random network delay in the forward channel is proposed, which are described in a state-space form. A new control scheme is used to overcome the effects of network transmission delay, which is termed networked predictive control (NPC). Furthermore, three different ways to choose control input are discussed and the performances are analyzed, respectively. Both real-time simulations and practical experiments show the effectiveness of the control scheme.     

两种带多约束的组播路由算法

组播对其成员节点能够提供服务质量,且组播在未来通信网络当中起到越来越重要的角色.对多约束斯坦利最小树问题,提出了基于Boruvka方法的多约束组播算法(BMCMRA)与基于Kruskal方法的多约束组播算法(KMCMRA).仿真试验表明算法具有良好代价性能,且能够很好地满足多约束条件.     

分段连续型延迟Logistic方程Runge-Kutta方法的稳定性

讨论了用Runge-Kutta方法求解分段连续型延迟Logistic方程的稳定性,分析了直接运用Runge-Kutta方法会产生伪解,从而建立了不产生伪解的Runge-Kutta方法,讨论了该方法的收敛阶,证明了该方法是局部和全局渐近稳定的.数值实验进一步验证了算法理论分析的正确性.     

基于LMKL和OC-ELM的航空电子部件故障检测方法

针对航空电子部件故障样本获取困难以及检测准确率不高的问题,提出基于局部多核学习(localized multiple kernel learning, LMKL)和一类超限学习机(one-class extreme learning machine, OC-ELM)的故障检测方法。仅运用正常状态的小样本数据,给出了LMK-OC-ELM的数学表达形式,并在不同的门模型下推导了LMK-OC-ELM中局部核权重的优化方法;在获取局部核权重的基础上,定义了离线故障检测所需的统计检验量与阈值,以便工程实现。将所提方法应用于某型接收机,结果表明,在训练时间可控的前提下,与4种常见的一类分类(one-class classification, OCC)算法相比,所提方法可均衡地提高召回率、查准率和特异度,以LMK-OC-ELM-sig为代表,其在F1、曲线下方面积(area under curve, AUC)、G-mean和准确率4个指标上,比最近提出的局部多核异常检测(localized multiple kernel anomaly detection, LMKAD)方法分别提高了1.60%、1.57%、1.53%和2.23%。