城市公交线网差异化计程票价多目标优化

为获取更加接近实际城市公交线网的票价策略，将出行者的社会互动行为与后悔心理引入广义费用，提出线路客流OD矩阵均衡算法；分别以交通管理部门利润最大化及出行者效用最大化为目标，以公交计程票价、发车频率、私家车停车费为变量，建立固定需求下公交线网差异化计程票价多目标优化模型.引入集群智能多目标优化算法求解，并应用于Mandl 标准公交线网.研究发现：以线路里程为标准，差异化计程票制可以有效降低出行成本；依据帕累托最优解调节票价，可以促进出行者选择行为向优势均衡转移.     

Toward using social media to support ridesharing services: challenges and opportunities

Ridesharing has been attracting increasing attention from both academia and industry. One of the challenges posed by the study of ridesharing is to identify the most valuable information for improving the ridesharing decisions taken by participants. Another challenge is to use harvesting techniques to extract specific types of travel-related information. Many methods have been developed by the community in order to solve these issues. However, due to a lack of information sharing between different transit authorities and the difficulty of identifying subjective perceptions of the experience of ridesharing, understanding and evaluating how social media data might support or obstruct goals for mobility, safety and environmental sustainability in ridesharing is a difficult task. In this survey, we first analyze the literature on ridesharing with a focus on the properties and model of service, and introduce a framework to describe the major components required for a ridesharing service. Then, we illustrate the potential value of information extracted from social media and present the rationale for harvesting travel-related data. Finally, we detail some possible directions and different approaches for using social media data, and highlight their assets and drawbacks.     

论宪法作为非确断性的社会评价系统在"新启蒙运动"中的意义

在当前的意识形态领域里，学术界对“新蒙昧主义思潮”的泛起和蔓延给予了很大的关注。相应地国际国内一大批社会人文主义科学家倡导要在全世界范围内开展一场大规模的“新启蒙运动”。“新蒙昧主义思潮”中的“宗教政治蒙昧主义”对宪法政教分离的原则与宪政已经和正在造成重大冲击并产生了消极性影响。对此，宪法学术界应当予以严肃的对待。本文从宪法作为非确断性的社会评价系统的职能角度，作了初步的探讨。     

中国音乐网站现况分析

21世纪网络的发展给社会生活带来了许多新现象和新问题,也为音乐传播带来了新的生机和活力。本文从音乐网站在社会传播中的现状出发,指出网络在音乐传播中存在的问题,并进一步从受众、传播媒介、把关人和法律建设等角度分析问题背后的原因。     

沪杭磁浮线的社会经济效益分析

沪杭磁浮线对长江三角洲的经济将会带来巨大影响,同时其投入资金巨大.从可量化效益(节约乘客出行时间、提高安全性、提高乘客的劳动生产率、节约城市土地、降低污染、带动沿线不动产的增值、节约能源)和不可量化效益(改善交通促进城市发展、改善居民生活质量)这两大方面对沪杭磁浮线的社会经济效益进行分析.     

紧扣民需民意 推进三社联动 探索基层治理新模式

党的十九大对国家治理体系和治理能力现代化提出了新任务、新要求,突出社会化、法治化、智能化、专业化。以湖南省株洲市荷塘区为例,通过深入实施三社联动,不断创新基层治理,推进社会治理体系和治理能力现代化。     

新媒体环境下全地形车营销策略分析

互联网+和大数据技术的不断发展和进步让信息经济时代真正地到来了。伴随着电子商务从起步到发展,很多的电商运营平台也逐渐凸显出自己的价值和地位。与此同时,电子商务的营销模式也从传统的B2B、B2C模式向着O2O、C2B的方向发展。全地形车,是一种十分独特的车型,适用的范围和人群也具有特定性。为此,在新媒体的环境之下,如何进行全地形车的营销,如何能够为全地形车吸引到更多的受众群体,这正是本文所要探究的关键所在。为此,文章在对全地形车的基本内涵、主要分类进行阐述和分析以后,针对全地形车这一个特殊车型的营销模式的创新和进步,提出了一些见解和主张。     

实现城市防洪经济、社会、环境效益三统一

本文从分析防洪经济效益、社会效益、环境效益三者关系入手 ,明确了在生态失衡、灾害频繁、环境问题已经成为危及人类生存与发展的今天 ,实现三者统一协调、整体推进的重要性 ,并提出了工作思路与对策     

Potentials of using social media to infer the longitudinal travel behavior: A sequential model-based clustering method

This study explores the possibility of employing social media data to infer the longitudinal travel behavior. The geo-tagged social media data show some unique features including location-aggregated features, distance-separated features, and Gaussian distributed features. Compared to conventional household travel survey, social media data is less expensive, easier to obtain and the most importantly can monitor the individual’s longitudinal travel behavior features over a much longer observation period. This paper proposes a sequential model-based clustering method to group the high-resolution Twitter locations and extract the Twitter displacements. Further, this study details the unique features of displacements extracted from Twitter including the demographics of Twitter user, as well as the advantages and limitations. The results are even compared with those from traditional household travel survey, showing promises in using displacement distribution, length, duration and start time to infer individual’s travel behavior. On this basis, one can also see the potential of employing social media to infer longitudinal travel behavior, as well as a large quantity of short-distance Twitter displacements. The results will supplement the traditional travel survey and support travel behavior modeling in a metropolitan area.     

Identifying tourists and analyzing spatial patterns of their destinations from location-based social media data

Reliable travel behavior data is a prerequisite for transportation planning process. In large tourism dependent cities, tourists are the most dynamic population group whose size and travel choices remain unknown to planners. Traditional travel surveys generally observe resident travel behavior and rarely target tourists. Ubiquitous uses of social media platforms in smartphones have created a tremendous opportunity to gather digital traces of tourists at a large scale. In this paper, we present a framework on how to use location-based data from social media to gather and analyze travel behavior of tourists. We have collected data of about 67,000 users from Twitter using its search interface for Florida. We first propose several filtering steps to create a reliable sample from the collected Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The accuracy of the proposed classifier has been compared against the state-of-the-art classification methods. Finally, different clustering methods have been used to find the spatial patterns of destination choices of tourists. Promising results have been found from the output clusters as they reveal most popular tourist spots as well as some of the emerging tourist attractions in Florida. Performance of the proposed clustering techniques has been assessed using internal clustering validation indices. We have analyzed temporal patterns of tourist and resident activities to validate the classification of the users in two separate groups of tourists and residents. Proposed filtering, identification, and clustering techniques will be significantly useful for building individual-level tourist travel demand models from social media data.