The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets

The station-free sharing bike is a new sharing traffic mode that has been deployed in a large scale in China in the early 2017. Without docking stations, this system allows the sharing bike to be parked in any proper places. This study aimed to develop a dynamic demand forecasting model for station-free bike sharing using the deep learning approach. The spatial and temporal analyses were first conducted to investigate the mobility pattern of the station-free bike sharing. The result indicates the imbalanced spatial and temporal demand of bike sharing trips. The long short-term memory neural networks (LSTM NNs) were then developed to predict the bike sharing trip production and attraction at TAZ for different time intervals, including the 10-min, 15-min, 20-min and 30-min intervals. The validation results suggested that the developed LSTM NNs have reasonable good prediction accuracy in trip productions and attractions for different time intervals. The statistical models and recently developed machine learning methods were also developed to benchmark the LSTM NN. The comparison results suggested that the LSTM NNs provide better prediction accuracy than both conventional statistical models and advanced machine learning methods for different time intervals. The developed LSTM NNs can be used to predict the gap between the inflow and outflow of the sharing bike trips at a TAZ, which provide useful information for rebalancing the sharing bike in the system.     

实际交通流的运动微分方程

提出了交通流的相对粘性假设,在理想交通流的欧拉方程中引入相对粘性阻力项,得到了实际交通流的运动微分方程,并以速度一密度定流量模型和Green Shields速度一密度线性关系模型验证了假设和方程。     

强非线性问题的改进的L-P法及其应用

用改进的L-P法求解了强非线性Duffing方程和一类非振动型强非线性微分方程的初值问题 ,计算过程简单 ,精度也比张佑启等[2 ] 的改进的L-P法的更好     

Boussinesq方程波浪数学模型计算马来西亚科美纳河河口的波浪场

Ｂｏｕｓｓｉｎｅｓｑ方程波浪数学模型计算马来西亚科美纳河河口单堤整治方案的波浪场,为分析整治建筑物对河口地区水动力条件的影响提供依据。     

矿产资源资产估价的动态收益现值法研究

应用随机时间序列理论和资产评估理论对矿产资源资产估价的收益现值法进行了研究,建立了待估矿产资源资产未来净收益的动态预测模型,提出了折现率历史数据的测算方法,据此,建立了与净收益预测模型相类似的未来折现率的动态预测模型。这些模型和方法为把现行的偏重于静态的收益现值法扩展为科学实用的动态收益现值法奠定了基础。     

港口交通资源承载力预测预警模型

根据航道交通容量计算方法,建立了航道资源静态承载力模型,基于锚地规模计算方法和基准判定参数,建立了锚地资源承载力分级模型。应用排队理论,将港口码头泊位的服务强度与航道资源、锚地资源的承载力模型相融合,构建了港口交通资源承载力综合预测预警模型,并以中国南方某港口进行实例验证。计算结果表明:应用预测预警模型,2008年与2010年的航道资源承载力指数分别为0.405与0.608,锚地资源承载力综合指数分别为1.489与0.600,2008年的港口码头服务强度为0.565,计算结果与事实相符;按照货物吞吐量的增长速度,预计到2015年,最小、最大航道资源承载力指数分别为0.593与0.796,预计到2020年,最小、最大航道资源承载力指数分别为0.685与0.944;基于现有锚地资源,预计到2015年,水深小于5m的最大锚地资源承载力指数为0.177,水深在5～10m的最大锚地资源承载力指数为1.037,水深大于10m的最大锚地资源承载力指数为1.294,预计到2020年,水深小于5m的最大锚地资源承载力指数为0.210,水深在5～10m的最大锚地资源承载力指数为1.231,水深大于10m的最大锚地资源承载力指数为1.535;预计到2015年,港口码头的最小泊位服务强度为0.858,预计到2020年,港口码头的最小泊位服务强度为0.994。     

城市轨道交通网络新线接入后的客流预测

城市轨道交通网络新线接入后,网络拓扑结构和客流时空规律都将发生较大变化。提出通过可达性指标将进出站量预测、OD分布量预测、基于路径选择模型的随机客流分配等阶段关联,构建客流预测模型。进出站量预测时,构建土地利用替代指标,避免对新车站周边土地利用、社会经济属性等进行调查;同时由目的地选择效用计算得到车站可达性指标,描述车站位置对进出站量的影响。OD分布量预测时,构建目的地选择模型,可适应拓扑变化后的场景,模型中OD可达性指标由路径选择效用计算得到。构建的路径选择模型,综合考虑了影响乘客路径选择的各因素。最后,对广州市地铁6号线接入后的客流进行建模预测,各模型参数均符合统计检验要求且客流预测精度较高。     

F(z)上线性有源网络状态方程的分析

如果线性有源网络的每一条支路上的物理量都视为独立变量，那么网络成了这些参量的有理函数域F（z）上的网络．文中讨论了F（z）上线性有源网络状态方程存在的条件，推导出状态方程表达式．并用VC与MATLAB语言设计了专门的电网络分析软件，可将所需要分析的电网络通过图形输入及编辑、电路拓扑结构分析和矩阵代数运算，即可得到要求的状态方程。     

枝状天然气管网流动方程

过去使用的关联矩阵方法在描述枝状天然气管网流动方程时,没有考虑压气站的自耗气,这在一些需要准确描述这部分气量的模型中会产生不可避免的偏差.文中通过增加自耗气源向量的方法对此进行了改进,使得该方法可以完整地描述这部分天然气,能更加准确地对管网的结构和流动方程进行描述.     

Structural equation modeling of user satisfaction of bus transit service quality based on stated preferences and latent variables

Few studies have been conducted on the service quality (SQ) of bus transit in developing countries. This paper presents a structural equation modeling (SEM) approach to identifying the relationships among major attributes that affect the SQ of bus transit in the city of Dhaka in Bangladesh. Specifically, 22 bus transit SQ attributes, drawn from 655 questionnaires, are used to develop different SEM models for the city. Along with stated preferences, the effect of three latent variables on SQ is analyzed. Among the developed models, the best model is selected by using different statistical approaches. With the best model, selected attributes are rated according to their relative importance on SQ. Acknowledging limited resources of a developing nation, this study gives a clear way ahead to planners, operating companies and transport managers to design appropriate transport policies which will ensure more effective services to current bus users as well as attracting new passengers.