船舶防污染作业等级评定量化研究

文章应用模糊数学评估方法,建立船舶防污染作业等级评定模型,为量化研究船舶防污染作业单位安全状况提供了具体的方法和依据。最后结合辖区实际进行了验证。     

Identifying multiclass vehicles using global positioning system data

It has been previously evidenced that global positioning system (GPS) data can be used to distinguish passenger cars from delivery trucks. In this paper, a machine learning approach is proposed to use GPS data to identify multiclass vehicles, including passenger cars, single unit trucks, and multi-trailer trucks. The method is acceleration and deceleration-based since it considers the variations of acceleration and deceleration as the most effective features to classify vehicles. The overall classification result for the three vehicle classes is about 75%. The major challenge is to distinguish single unit trucks from multitrailer trucks due to their somewhat similar mobility patterns. The paper also explores the impacts of GPS sampling frequency on vehicle classification. It is found that the proposed multiclass vehicle classification can be reasonably conducted if the data are collected frequently enough (i.e., every five seconds or more frequently) to capture the major acceleration and deceleration processes. The proposed method can be considered as a low-cost and non-intrusive approach to collect vehicle class information and to potentially supplement the existing classification schemes in urban areas.     

Development and evaluation of bus lanes with intermittent and dynamic priority in connected vehicle environment

Exclusive bus lanes provide a very high level of priority for transit operations, especially for Bus Rapid Transit and Express service, but these lanes could be underutilized and be a source of extra capacity if they could be shared in an intelligent way. This article explores the benefits of providing intermittent priority, called bus lane with intermittent and dynamic priority, of these exclusive bus lanes. Intermittent and dynamic priority can be implemented by allowing vehicles to use the lane when Bus Rapid Transit or Express bus is not present. Drivers can be alerted when a bus is in the lane using either infrastructure-based signs, or in the future using infrastructure-to-vehicle, or connected vehicle communications. Some critical operating parameters for implementing bus lane with intermittent and dynamic priority system including clear distance, degree of saturation (volume-to-capacity ratio), connected vehicle penetration, and bus departure/headway frequency have been investigated in this paper.     

水下平台进水下潜过程的稳定性控制

介绍了某型水下平台的压载水系统组成,分析了其进水下潜过程的工作特点,结合静力学原理对平台进行分析和建模。针对进水控制系统为MIMO型且存在多变量耦合,采用模糊解耦的方法进行解耦分析,提出了一种基于模糊控制算法的平台进水下潜过程稳定性控制方法。经Matlab仿真表明,这种控制方法能够满足平台自动进水下潜过程的稳定性以及快速性要求。最后,通过实际系统水下试验进一步验证其可靠性。     

基于神经网络的海面噪声预测算法

海面噪声是整个海洋噪声研究领域的重要组成部分,准确预测海面噪声对于船舶探测系统及水声系统性能至关重要。本文对影响海面噪声的信号源特性进行分析,通过统计学方法对噪声源的分布情况及噪声传播条件进行研究,分析传播中的射线原理对噪声的影响。最后利用神经网络算法对简正波模型进行改进,研究小角度范围内噪声场的密度函数,并发散至大广角范围,得到海面噪声以及噪声信道的统计特性函数,并进行了实验。     

基于模糊综合法构建物流企业客户信用评价指标体系（英文）

针对物流企业客户信用评价进行了研究,基于模糊综合法构建了以企业信誉及违约记录、速动比率及资产负债率、人力资源水平及盈利能力、产权清晰程度及担保状况、区域信用状况及区域法制环境等10个因素为指标的物流企业客户信用评价指标体系;通过层次分析法(AHP)确定了指标权重,并采用专家咨询法(Delphi method)确定了指标评价标准;通过实证案例进行了验算,验算结果与事实相符,该指标体系能有效评价客户信用状况.     

基于满意度最大化的列车开行方案研究

地铁公司在编制列车开行方案时,很难同时兼顾到公司自身利益与社会利益。因此,建立基于地铁公司效益和乘客满意度最大化的地铁列车调度方案优化模型非常必要。使用层次分析法计算不同影响因素的权重,利用模糊数学的方法对计算数据进行拟合,并通过实例验证该模型的可行性。     

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基于北京地铁6个换乘站客流高峰期乘客对上行方向步行楼梯和自动扶梯的选择行为调查数据,采用灰色关联法计算乘客选择行为影响因素的重要度并排序。利用模糊数学理论建立乘客的选择行为模型,并分析乘客选择行为与相关影响因素的变化规律。研究表明,楼梯高度、扶梯前排队人数、乘客携带行李情况为影响乘客选择行为的重要因素。本文建立的模型可较好地刻画乘客的选择行为,模型计算结果与实际数据较吻合。此外,扶梯前排队人数少于25人时,乘客选择楼梯的概率较小,受其他因素影响小;超过25人后,乘客选择楼梯概率随排队人数的增加显著增加,且乘客负重、楼梯高度越小,影响越明显。不同负重乘客选择楼梯的概率随楼梯高度的变化规律一致,并随楼梯高度的增加近似呈线性下降。     

高等级公路绿色施工评价模型研究

阐述了高等级公路绿色施工的内涵,从资源能源的节约利用、减少环境负荷、综合管理等方面构建了高等级公路绿色施工评价指标体系,并对各指标评价标准进行了较全面、系统的量化。针对指标的模糊不相容性建立了高等级公路绿色施工模糊物元评价模型,采用层次分析法和熵权法确定该指标的权重。以工程实例分析了该评价模型的可行性。     

高速公路路基边坡生态防护效果评价

为评价高速公路路基边坡生态防护效果,从护坡效果、生态效益、景观效果3个方面,通过专家咨询,建立层次分析法与模糊综合评价相结合的路基边坡生态防护效果评价体系,并将其应用于贵州省某高速公路路堑边坡的评价。评价结果表明:护坡功能是影响边坡生态防护效果评价的最重要因素,其次是生态效益,景观效果所占比重最小;该高速公路路堑边坡生态防护效果良好。