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International Journal for Traffic and Transport Engineering最新文献

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A DESIGN OF SUSTAINABLE LAST-MILE DELIVERY OF POSTAL ITEMS IN CITIES USING MULTI-CRITERIA DECISION-MAKING TECHNIQUES 利用多标准决策技术设计城市中可持续的最后一英里邮政投递
Pub Date : 2022-04-01 DOI: 10.7708/ijtte2022.12(2).08
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引用次数: 0
PARKING ON STREET PARKING LOTS IN TOURIST DESTINATIONS – CASE STUDY CITY OF ŠIBENIK 旅游目的地街道停车场停车——以Šibenik城市为例
Pub Date : 2022-04-01 DOI: 10.7708/ijtte2022.12(2).05
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引用次数: 0
INFLUENCE OF ROAD SAFETY CULTURE ON DRIVERS BEHAVIOR BETWEEN GREECE AND PALESTINE 希腊与巴勒斯坦道路安全文化对驾驶员行为的影响
Pub Date : 2022-04-01 DOI: 10.7708/ijtte2022.12(2).04
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引用次数: 0
THE RELATIONSHIP BETWEEN PAVED ROADS INVESTMENT AND THE WIDER ECONOMIC BENEFITS IN UGANDA 在乌干达,铺路投资与更广泛的经济利益之间的关系
Pub Date : 2022-04-01 DOI: 10.7708/ijtte2022.12(2).06
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引用次数: 0
U.S./EUROPE COMPARISON OF ATC-RELATED ACCIDENTS AND INCIDENTS 美国/欧洲空中交通管制相关事故和事件的比较
Pub Date : 2022-04-01 DOI: 10.7708/ijtte2022.12(2).01
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引用次数: 0
ESTIMATING A REGIONAL AIRPORT AIR PASSENGER DEMAND USING AN ARTIFICIAL NEURAL NETWORK APPROACH: THE CASE OF HUAHIN AIRPORT, THAILAND 基于人工神经网络的区域机场航空旅客需求估算:以泰国华欣机场为例
Pub Date : 2022-04-01 DOI: 10.7708/ijtte2022.12(2).07
P. Srisaeng, Glenn Baxter, Parleda Sampaothong
: Artificial neural networks (ANNs) are a promising modelling approach for predicting an airport’s air passenger demand. The study proposed and empirically tested an artificial neural network model to predict the annual passenger demand for Huahin Airport, a regional and tourist focused airport located in Thailand. The ANN input variables included Thailand’s population size, Thailand’s real GDP, world jet fuel prices, Thailand total passengers carried, Thailand’s tourist numbers and Thailand’s unemployment rates. The data were trained using the Levenberg-Marquandt back-propagation algorithm. The ANN comprises eight neurons in the hidden layer and one neuron in the output layer. 80 per cent of the data was used in the training phase with the remaining data divided into validation (10 per cent) and testing (10 per cent) phases. The proposed ANN provided very accurate prediction values. The coefficient of determination R value of model was around 0.995, and the mean absolute percentage error (MAPE) of the final ANN model was 13.27%. The study found that the four key determinants of Huahin Airport annual air passenger demand were Thailand population size, the commencement of AirAsia services at Huahin Airport, Thailand’s tourist numbers, and Thailand’s real GDP.
人工神经网络(ANNs)是预测机场航空旅客需求的一种很有前途的建模方法。本研究提出并实证检验了人工神经网络模型,以预测泰国华欣机场的年旅客需求。人工神经网络的输入变量包括泰国的人口规模、泰国的实际GDP、世界航空燃料价格、泰国的总乘客人数、泰国的游客人数和泰国的失业率。使用Levenberg-Marquandt反向传播算法对数据进行训练。该神经网络由隐藏层的8个神经元和输出层的1个神经元组成。80%的数据用于训练阶段,其余的数据分为验证阶段(10%)和测试阶段(10%)。所提出的人工神经网络提供了非常准确的预测值。模型的决定系数R值约为0.995,最终ANN模型的平均绝对百分比误差(MAPE)为13.27%。研究发现,华欣机场年航空旅客需求的四个关键决定因素是泰国人口规模、亚航在华欣机场服务的开始、泰国的游客数量和泰国的实际GDP。
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引用次数: 0
CROWD LOGISTICS: HOUSEHOLD AS A LOGISTICS SERVICE PROVIDER 人群物流:以家庭为物流服务商
Pub Date : 2021-12-01 DOI: 10.7708/ijtte2022.12(1).08
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引用次数: 4
QUEUE DISCHARGE HEADWAY: CHARACTERISTICS, DISTRIBUTIONS AND EFFECTS ON SATURATION FLOW RATES AT SELECTED SIGNALIZED INTERSECTIONS IN LAGOS 队列放电车头:特征,分布和影响饱和流量率在拉各斯选定的信号交叉口
Pub Date : 2021-12-01 DOI: 10.7708/ijtte2022.12(1).09
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引用次数: 0
MEASURING THE EFFICIENCY OF THE TRANSPORT PROCESS IN DISTRIBUTION CENTRES OF A TRADING COMPANY 衡量一个贸易公司的配送中心的运输过程的效率
Pub Date : 2021-12-01 DOI: 10.7708/ijtte2022.12(1).07
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引用次数: 2
THE CONNECTION BETWEEN SPATIAL AUTOCORRELATION AND BORDER CROSSING TRAFFIC 空间自相关与过境交通的关系
Pub Date : 2021-12-01 DOI: 10.7708/ijtte2022.12(1).10
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引用次数: 0
期刊
International Journal for Traffic and Transport Engineering
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