Android消息推送机制在城市通中的应用研究

智能手机App应用五花八门,涉及了日常生活吃、穿、住、行、娱乐等各个方面,方便和丰富了我们的生活,加快了信息化生活的脚步,人们利用智能手机可以轻松地查收邮件、移动办公、查看新闻、下载应用等。本文提到的城市通也是智能手机APP应用,能够为人们的日常生活带来很大方便,其中一个重要功能是提供生活中煤气费、水费、电费欠费提醒功能,为了及时地传递此类信息,需要为此类信息实现消息推送功能,在Android手机操作系统中消息推送的方式有几种可以供选择,本文通过对这几种推送消息的方式的特点比较,选择最适合手机城市通的推送方式。

地下城市通廊的防火设计

地下城市通廊具有形态复杂、周围衔接的空间多、内部功能和人员组成多样的特点,在现行的规范中没有直接的解决方案。对城市通廊的形态和特点进行了论述,对一种跨越多层、与地铁融合的多层城市通廊的形式提出了防火分隔和人员疏散的解决方案,并与常规设计进行分析对比。分析表明,城市通廊虽然放弃了传统的防火分区的概念,但是围绕商业进行防火分隔的方案不仅可以满足平面布局的要求,还可以更好地控制火灾蔓延的风险。人员疏散系统的设计要求很好地对现有不同规范之间进行了衔接,既保持了消防安全水平,也兼顾了项目的经济效益。

城市通沟污泥无害化处理及其制备路基材料的研究

从城市通沟污泥的资源化利用出发,根据通沟污泥本身的物理化学特性,用其更为有价值的固相部分替代三渣混合料中的细集料。试验表明,制成的复合三渣混合材料路用性能和耐久性能满足路基材料的技术要求,同时将重金属有效地加以固化,符合国家标准的排放要求,不会给环境带来二次污染。

内蒙古锡赤通城市群重点城市功能定位优化研究

城市群能够发挥各城市优势,加强城市之间的合作,是促进区域发展及经济增长的重要形式,有利于区域经济一体化发展格局的形成。内蒙古中西部已经形成以呼包鄂城市群为中心的区域经济一体化发展,为缩小东西部差距,应助力蒙东经济增长轴的形成,“锡赤通”地区有条件作为重点经济增长轴,促进区域经济的发展。本文以内蒙古锡赤通城市群重点城市功能定位优化为题,结合相关数据、资料,运用数据统计分析、文献收集整理等方法,分析锡赤通城市群各个重点城市具备的区位、经济、资源、政策等优势,总结锡赤通城市群的综合竞争力,明确城市发展的重点方向,并给予整个城市群明确的功能定位。致力于为锡赤通城市群的协同发展提供理论依据。

开辟地下通廊 疏解地上交通——新加坡地下“城市通廊商场Citylink Mall”

现代化大城市的交通发展已进入多层次的立体化时代，无论是快速交通的需要，还是人车分流的需要，都在探索各种方式，体现以人为本（人的安全、方便）的基本理念。事实证明人行步道网络系统与地面车行系统的立交处理，是加快机动车行进速度、确保人行安全卓有成效的措施。

高速公路通城市路段声环境影响防治对策研究

基于对高速公路通城市路段交通噪声现状、车辆源强的调查,针对通城市路段高速公路声环境敏感目标空间分布特点,开展噪声综合控制对策的研究,从土地、城市和交通规划相结合的视角规划控制,采取低噪声路面、声屏障、临街建筑噪声防护等技术控制,结合限速、禁鸣等多种管理手段,提出通城市路段的高架复合道路交通噪声综合治理对策,对提升交通运输噪声污染控制效果、提高沿线居民满意度具有指导意义。

城市暖通空调的节能减排对策浅析

在当前的城市生活中,暖通空调已经成为了极为重要的一个组成部分.这些暖通空调的使用确实在较大程度上提升了人们的生活质量,但是其使用的能耗也越来越大.因此,针对这些暖通空调采取恰当的措施进行节能减排也就显得极为必要.本文就对城市暖通空调的节能减排对策进行了简要的分析和探讨.

探讨城市道路交通导识系统的交互设计

文章从城市交通导识系统的功能及导识系统交互设计的基本原则出发,较为详尽地论述了图像识别、大数据计算等新技术在改善城市交通导识系统中交互设计中的应用方式,进而提出了针对交通信息发布、图像提示和语音交互等方面进行改进的策略。

数字经济下公共交通虚拟化服务研究

近年来,随着新型智慧城市建设、“互联网+”战略的全面推进,涌现了一大批无现金、虚拟化的便捷应用场景,并在各类场所提供虚拟化在线服务,深得市民喜爱。在此背景下,通过对出行服务虚拟化、广州出行服务实践进行分析,提出其在交通行业应用的前景的优势,并探讨未来发展方向,解决传统交通“投入-产出”模式的创新问题,挖掘虚拟化服务的创新空间和市场潜力,实现集约化转型发展。

Design and verification of an improved experimental platform for stray current in urban rail transit

With the rapid development of urban rail transit,there have been an urgent problem of excessive stray current.Because the stray current distribution is random and difficult to verify in the field,we designed an improved stray current experimental platform by replacing the simulated aqueous solution with a real soil environment and by calculating the transition resistance by measuring the soil resistivity,which makes up for the defects in the previous references.Firstly,the mathematical models of rail-drainage net and rail-drainage netground were established,and the analytical expressions of current and voltage of rail,drainage net and other structures were derived.In addition,the simulation model was built,and the mathematical analysis results were compared with the simulation results.Secondly,the accuracy of the improved stray current experimental platform was verified by comparing the measured and simulation results.Finally,based on the experimental results,the influence factors of stray current were analyzed.The relevant conclusions provide experimental data and theoretical reference for the study of stray current in urban rail transit.

从“粗放发展”走向“深耕服务”——广电融媒体与政企融合创意探究

移动互联网是每个智慧城市的重要“神经单元”,是智慧城市最重要最基础的支撑与组成,广电融媒体融合技术作为一种新兴的产业形态,具有高速移动化、高效能服务化、融合创新化、受众便捷化、实时获得性等特征,是智慧城市建设的最佳实践载体。通过打造媒体融合创新服务平台,能够更好地满足现代广大群众多样化、个性化的精神、文化及生活各方面需求,让受众感受到广电新媒体数字经济带来的便利与优质服务。

The comprehensive measure model for urban traffic congestion based on value function

According to the distribution characteristics of traffic congestion in time and space, a measure index system of urban traffic congestion is set up based on the spatial and temporal distribution. Based on the analysis of the main characteristics of traffic congestion and the generation process of traffic congestion, the measure model for urban traffic congestion is constructed by the value function. Moreover, based on the measure values of traffic congestion in urban road networks with defined different levels, a method to prevent and control traffic congestion is designed. The application results confirm that the proposed method is feasible in comprehensive measures for urban traffic congestion and they are consistent with the results of other methods. The measuring results can therefore reflect the actual situation. The comprehensive measure model is scientific and the process is simple, and it has wide application prospects and practical value.

Passenger flow dynamic assignment model of urban mass transit and its application during interval interrupted operation

In order to find a method which can describe the passenger flow dynamical distribution of urban mass transit during interval interrupted operation,an urban railway network topology model was built based on the travel path dual graph by considering interchange,crowd and congestion.The breadth first valid travel path search algorithm is proposed,and the multipath passenger flow distribution logit model is improved.According to the characteristics of passengers under the interruption condition,the distribution rules of different types of passenger flow are proposed.The method of calculating the aggregation number of station is proposed for the case of insufficient transport capacity.Finally,the passenger flow of Beijing urban mass transit is simulated for the case study.The results show that the relative error of most of transfer passenger flow is below 10%.The proposed model and algorithm can accurately assign the daily passenger flow,which provides a theoretical basis for urban mass transit emergency management and decision.

电子地图e彩纷呈

电子地图在信息浪潮的冲击下应运而生,正在为人类架构美妙的“精神乐园”。随着电脑和网络的普及，文化的传播交流变得如电光火石般迅捷，文化资源的获取共享在瞬间即可实现。电子地图正如春风细雨般向我国国民经济的方方面面渗透，日益发挥出其在科学管理和社会生活等方面所特有的强劲的辅助功能。电子地图的冲击波正酝酿着一场划时代的地图的“革命”。

Spatial-temporal Characteristics and Factors Influencing Commuting Activities of Middle-class Residents in Guangzhou City, China

The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.

Particle swarm optimization for train schedule of Y-type train routing in urban rail transit

The train schedule usually includes train stop schedule,routing scheme and formation scheme.It is the basis of subway transportation.Combining the practical experience of transport organizations and the principle of the best match between transport capacity and passenger flow demand,taking the minimum value of passenger travel costs and corporation operating costs as the goal,considering the constraints of the maximum rail capacity,the minimum departure frequency and the maximum available electric multiple unit,an optimization model for city subway Y-type operation mode is constructed to determine the operation section of mainline as well as branch line and the train frequency of the Y-type operation mode.The particle swarm optimization(PSO)algorithm based on classification learning is used to solve the model,and the effectiveness of the model and algorithm is verified by a practical case.The results show that the length of branch line in Y-type operation affects the cost of waiting time of passengers significantly.

Probabilistic interval prediction of metro-to-bus transfer passenger flow in the trip chain

To accurately analyze the fluctuation range of time-varying differences in metro-to-bus transfer passenger flows,the application of a probabilistic interval prediction model is proposed to predict transfer passenger flows.First,bus and metro data are processed and matched by association to construct the basis for public transport trip chain extraction.Second,a reasonable matching threshold method to discriminate the transfer relationship is used to extract the public transport trip chain,and the basic characteristics of the trip based on the trip chain are analyzed to obtain the metro-to-bus transfer passenger flow.Third,to address the problem of low accuracy of point prediction,the DeepAR model is proposed to conduct interval prediction,where the input is the interchange passenger flow,the output is the predicted median and interval of passenger flow,and the prediction scenarios are weekday,non-workday,and weekday morning and evening peaks.Fourth,to reduce the prediction error,a combined particle swarm optimization(PSO)-DeepAR model is constructed using the PSO to optimize the DeepAR model.Finally,data from the Beijing Xizhimen subway station are used for validation,and results show that the PSO-DeepAR model has high prediction accuracy,with a 90%confidence interval coverage of up to 93.6%.

A BP neural network based information fusion method for urban traffic speed estimation

Obtaining comprehensive and accurate information is very important in intelligent tragic system （ITS）. In ITS, the GPS floating car system is an important approach for traffic data acquisition. However, in this system, the GPS blind areas caused by tall buildings or tunnels could affect the acquisition of tragic information and depress the system performance. Aiming at this problem, a novel method employing a back propagation （BP） neural network is developed to estimate the traffic speed in the GPS blind areas. When the speed of one road section is lost, the speed of its related road sections can be used to estimate its speed. The complete historical data of these road sections are used to train the neural network, using Levenberg-Marquardt learning algorithm. Then, the current speed of the related roads is used by the trained neural network to get the speed of the road section without GPS signal. We compare the speed of the road section estimated by our method with the real speed of this road section, and the experimental results show that the proposed method of traffic speed estimation is very effective.