铁路客票系统数据一致性的实现技术

本文分析了分布式数据库系统数据一致性的实现方法，介绍了客票系统中采用的两种实现数据一致性的技术：复制服务器技术和数据库通信技术，以及这两种技术的实现机制。     

关于加强打车软件综合管理的建议

中国打车软件从2012年开始上线,“嘀嘀打车”和“快的打车”通过“双向补贴”方式竞争客户,一度导致全国范围主要城市出租汽车运营秩序混乱,引起社会广泛争议。对打车软件涉及的金融系统安全、出租汽车运营秩序、群体性事件等问题展开分析。总结国内外打车软件的主要区别,指出中国打车软件的管理更为复杂、更容易引起社会矛盾。最后,建议在国家层面提出指导性意见,着重研究网络金融进入公共服务业的规则、现代信息技术服务于出租汽车营运的管理规则,以及出租汽车行业管理中政府和企业的权责界限。     

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提高航线需求预测精度是航空客运收益管理系统的重要研究课题。提出一种首先运用EM算法对航线历史订座数据中由于受资源限制而没有被满足的需求进行修复，取得更为准确的需求数据，然后，针对航班销售具有提前预订的特点，将航线历史订座数据整合成一个提前日矩阵，使预测时能够利用更多的已知信息并减少了计算数据量，最后再运用Winters模型进行预测的航线需求预测方法。以成都到广州航线历史数据为例仿真计算，预测结果的平均误差为4.9％ ，而直接采用winters法进行预测的平均误差为21.7％ ，验证了算法的可行性和有效性。     

铁路客票预订需求预测模式

对当前铁路运输客票预订系统进行了分析。研究了建立动态多席订票需求预测模式。针对不同等级订票需求,引用泊松分布来描述不同时段,不同等级的订票到达率。当实际资料难以获取时,以ｍｏｎｔｅ ｃａｒｌｏ模拟产生资料进行参数估计,最后动态规划的方法的方法建立了获取最大利益的模型,以实际数据代入运算,结果与实际情况相吻合。     

Itinerary choice and advance ticket booking for high-speed-railway network services

This paper formulates and examines the passenger flow assignment (itinerary choice) problem in high-speed railway (HSR) systems with multiple-class users and multiple-class seats, given the train schedules and time-varying travel demand. In particular, we take into account advance booking cost of travelers in the itinerary choice problem. Rather than a direct approach to model advance booking cost with an explicit cost function, we consider advance booking cost endogenously, which is determined as a part of the passenger choice equilibrium. We show that this equilibrium problem can be formulated as a linear programming (LP) model based on a three-dimension network representation of time, space, and seat class. At the equilibrium solution, a set of Lagrange multipliers for the LP model are obtained, which are associated with the rigid in-train passenger capacity constraints (limited numbers of seats). We found that the sum of the Lagrange multipliers along a path in the three-dimension network reflects the advance booking cost of tickets (due to advance/early booking to guarantee availability) perceived by the passengers. Numerical examples are presented to demonstrate and illustrate the proposed model for the passenger assignment problem.     

A self-learning advanced booking model for railway arrival forecasting

Accurate short-term arrival forecasting is essential information for railway operators to conduct daily operations such as demand management strategies. Conventional time series methods apply historical arrival data which is the accumulation of reservations to project future arrivals. This study aims to utilize reservation data directly and proposes a novel advanced booking model by using the framework of case-based reasoning. The proposed model contains four modules with distinctive functions for similarity evaluation, instance selection, arrival projection, and parameter search. We have the constructed model tested on fourteen daily arrival series and compared its out-of-sample accuracy with that of four traditional benchmarks. The empirical results show that in average the proposed self-learning model may reduce at least 11% of mean square errors (MSE). Moreover, the learning scheme in the model may achieve significant reduction of MSE comparing with performance of other naïve versions.     

高校学生火车票网上预订管理信息系统的研究开发

随着全国大学生数量的不断增加，每年寒暑假大量的学生要乘火车回家，给车站正常的售票工作带来了极大的压力。目前针对这个特殊群体的订票方法实施效果并不理想。而利用目前流行的C#、ASP．NET、SQL数据库等技术开发的“高校火车票预订管理信息系统”，可以很好的解决此问题。此系统采用B／S系统体系结构，实现学生网上订票，并利用网上订票信息容量大、可提供多个选择方案的优势，利用计算机对数据进行优化，最终达到订票成功率最大的目标。而且可以与校园一卡通一起实现转账等功能。     

北京市出租汽车智能召车分析及评价方法研究

利用打车APP软件通过智能手机进行出租汽车预约是近来北京市使用较为广泛的出租汽车用车方式.为了解这一新兴用车方式时间和空间分布的特点,本文通过构建订单数据处理模型,对智能召车软件订单数据进行分析,揭示出智能召车的时空分布特性,包括夜间用车高峰明显、周六为每周订单数量低谷、用车即时性强,以及中心城区订单数量随环路变化呈线性增长趋势,核密度空间分布不均匀等特点.并根据智能召车与出租汽车行业运营管理基础指标的对比分析,提出了一种智能召车软件评价方法,并以两个周期为例对智能召车软件应用效果进行了评价.