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108篇 您的检索式:作者名="KARLAFTIS"
    题名 作者 年代 出处 被引量
1基于模型和决策支持系统的P+R收费优化政策研究(英文)显示文摘当私家车的使用可与公共交通结合时,人们会更倾向于乘坐公共交通出行.因此,P+R(停车换乘系统)在为公共交通吸引客流的同时也为公共交通的运营起到重要的作用.在建立和运营P+R系统时,制定合理的用户收费政策是诸多影响因素之一.事实上,收费政策作为调节手段之一,利用其鼓励或约束停车场的各类用户,将有助于交通部门管理和经营P+R设施.基于社会经济水平,本文为确定停车设施最优定价方案提供了一种新方法.结合遗传算法,本文利用财务分析模型确定了P+R设施最优定价方案参数.该模型应用于希腊雅典地铁网络的P+R设施.结果表明,该模型可在短时间内提供近似最优定价方案.另外,本文还在方便用户的计算机框架下结合该模型开发了相应决策支持系统.KEPAPTSOGLOU Konstantinos KARLAFTIS Matthew G LI Zong-zhi 2010交通运输系统工程与信息2010,10,5:3
2A multivariate state-space approach for urban traffic flow modeling and prediction 显示文摘Stathopoulos A Karlaftis M G 2003Transportation research Part C: Emerging technologies2003,11,2:1
3Effects of road geometry and traffic volumes on rural roadway accident rates显示文摘Karlaftis M G Golias I 2002Accident Analysis&Prevention2002,34,3:1
4Short-term forecasting: Overview of objectives and methods 显示文摘VLAHOGIANNI E I GOLIAS J C KARLAFTIS M G 2004Transport Reviews2004,24,5:1
5Statistical methods for detecting nonlinearity and non-stationarity in univariate short-term time-series of traffic volume 显示文摘Vlahogianni E I Karlaftis M G Golias J C 2006Transportation Research Part C: Emerging technologies2006,14,:1
6A DEA approach for evaluating the efficiency and effectiveness of urban transit systems 显示文摘KARLAFTIS M G 2004European Journal of Ope- rational Research2004,152,2:1
7Comparing traffic flow time series under fine and adverse weather conditions using recurrence-based complexity measures 显示文摘VLAHOGIANNI E I KARLAFTIS M G 2012Nonl Dyn2012,69,4:1
8Optimized and meta-optimized neural networks for short-term traffic flow prediction: a genetic approach 显示文摘Vlahogianni E I Karlaftis M G Golias J C 2005Transportation Re- search Part C :Emerging Technologies2005,13,:1
9Statistical methods versus neural networks in transportation research: Differences, similarities and some insights 显示文摘Karlaftis M G Vlahogianni E I 2011Transportation Research Part C: Emerging Tech- nologies2011,19,3:1
10A multivariate state space approach for urban traffic flow modeling and prediction 显示文摘Stathopoulos A Karlaftis M G 2003Transportation Research Part C2003,11,2:1
11Development of an object-oriented pedestrian traffic flow simulation environment for transport terminal planning显示文摘ANAGNOSTOPOUL OS D KARLAFTIS M NIKOLAIDOU M 2003Journal of Advanced Transportation2003,37,1:1
12Short- term traffic forecasting Where we are and where we're going 显示文摘Vlahogianni E I Karlaftis M G Golias J C 2014Transportation Research Part C: Emerging Technologies2014,43,1:1
13Containership routing with time deadlines and simultaneous deliveries and pick-ups显示文摘KARLAFTIS M G KEPAPTSOGLOU K SAMBRACOS E 2009Transportation Research Part E: Logistics and Transportation Review2009,45,1:1
14Statistical methods for detecting nonlinearity and non-stationarity in univariate short-term time-series of traffic volume 显示文摘Eleni I Vlahogianni Matthew G Karlaftis John C Golias 2006Transportation Research Part C2006,14,5:1
15Opti- mized and meta-optimized neural networks for short-term traffic flow prediction: A genetic ap- proach显示文摘Vlahogianni E I Karlaftis M G Golias J C 2005Transportation Research C2005,13,3:1
16Statis- tical Methods for Detecting Nonlinearity and Non- stationarity in Univariate Short-Term Time-Series of Traffic olume显示文摘Vlahogianni E I Karlaftis M G Golias J C 2006Transportation Research Part C2006,14,:1
17Statistical methods versus neural networks in transportation research:Differences, similarities and some insights显示文摘Karlaftis M G Vlahogianni E I 2011Transportation Research Part C2011,,38:1
18Modeling duration of urban traffic congestion 显示文摘Stathopoulos A Karlaftis M 2002Journal of Transportation Engineering2002,128,6:1
19Efficiency measurement in pubiie transport:are findings specification sensitive? 显示文摘KARLAFTIS M G TSAMBOULAS D 2012Transpor- tation Research Part A: Policy and Practice2012,46,2:1
20Develop- mental hemostasis: age-specific differences in the levels of hemostatic proteins 显示文摘Attard C van der Straaten T Karlaftis V 2013J Thromb Haemost2013,11,10:1
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