基于机器学习的船舶能耗智能预测方法验证分析

船舶能耗智能预测是实现船舶能效智能评估与优化决策的基础和前提。大数据、人工智能、机器学习等新兴技术促进了船舶能耗预测方法的不断发展,为分析不同基于机器学习的船舶能耗预测算法的预测精度与效果,进行了不同预测算法的实例验证分析。结合船舶油耗及其影响因素实船采集数据,通过采用不同机器学习算法对船舶能耗进行预测分析,验证了各算法的特点和优势,从而为选择合适的船舶能耗预测算法提供参考。     

从效率角度谈城市轨道交通的规划、建设和运营

面对国内各大中城市正在掀起的轨道交通建设高潮,从规划、建设、运营和管理等角度,阐述了对目前城市轨道交通建设过程中有关效率问题的看法,以及如何提高城市轨道交通效率的一些体会.并指出合理的线网规划是发挥效率的根本,合适的建设标准是发挥效率的保证,科学的运营管理是发挥效率的关键.     

基于价值工程的南京地铁全效修实施效果评估

南京地铁车辆系统全效修是一种全新的地铁维修模式,其实施效果除了主观的判断外,应用科学具体的理论方法进行客观的评价,从而为选择改善措施提供依据。简要介绍价值工程理论,利用AHP(层次分析法)从人、机、物、法、环五个功能层面分析全效修实施影响因素并构建基于价值工程的评估体系,建立评估模型;通过数据信息收集确定相应的功能系数及成本系数,完成对全效修的价值评估。评估结果表明,全效修实施过程中功能与成本之间匹配程度良好,同时也揭示出推行过程中的薄弱环节,并提出了改进建议。     

公路施工企业降低生产成本提高经济效益的对策

文章分析公路施工企业生产成本高利润率低的现状及成因,针对当前的市场环境,提出公路施工企业降低生产成本,提高经济效益的六大对策,论证提高企业管理能力和核心竞争力是改变现状的根本办法。     

Analysis of the operational energy efficiency for inland river ships

This paper looks at the energy consumption and green house gas emissions of inland river shipping, and compares them with the performance of seagoing ships. The analysis is based on a case study of container shipping on the Yangtze River, China. Data were collected under both calm water and real navigation conditions, and energy efficiency operation indices under these conditions are calculated and analyzed. We find that the navigation environment can influence significantly the operational energy efficiency of inland river ships.     

Rebound effects caused by the improvement of vehicle energy efficiency: An analysis based on a SP-off-RP survey

This study provide a straightforward way of examining the rebound effects of switching to more fuel efficient technologies, as well as determining the distribution of the effects in the household sector, including both the residential and transport sectors. A SP-off-RP survey conducted in Japan in 2012 asked people to state their preference for the reallocation behaviors after informing them of their annual operating cost saving resulting from the vehicle efficiency improvement. Coupled who save money from relocation are more likely to spend this either on housing features or transport; supporting the idea of rebound effects, although not only limited to within the transport sector. Regarding the distribution of rebound effects, domestic appliances are more likely to be affected than vehicles.     

未来空域窗体制下小口径舰炮反导效能分析

针对高射速小口径舰炮如何进行防空反导的问题,文章论述了未来空域窗的构造和设计,并通过仿真比较不同射击误差协方差矩阵和空域窗半径下的毁伤效能,得出不同射击协方差矩阵和空域窗半径影响了未来空域窗毁伤区域的大小。因此,在保证一定命中概率的前提下,通过调整射击误差协方差矩阵和未来空域窗半径可以有效提高空域窗毁伤区域的大小,从而在目标大范围机动的情况下,保证了舰炮的反导效能。     

A framework for user- and system-oriented optimisation of fuel efficiency and traffic flow in Adaptive Cruise Control

Fully automated vehicles could have a significant share of the road network traffic in the near future. Several commercial vehicles with full-range Adaptive Cruise Control (ACC) systems or semi-autonomous functionalities are already available on the market. Many research studies aim at leveraging the potential of automated driving in order to improve the fuel efficiency of vehicles. However, in the vast majority of those, fuel efficiency is isolated to the driving dynamics between a single follower-leader pair, hence overlooking the complex nature of traffic. Consequently fuel efficiency and the efficient use of the roadway capacity are framed as conflicting objectives, leading to fuel-economy control models that adopt highly conservative driving styles.This formulation of the problem could be seen as a user-optimal approach, where in spite of delivering savings for individual vehicles, there is the side-effect of the deterioration of traffic flow. An important point that is overlooked is that the inefficient use of roadway capacity gives rise to congested traffic and traffic breakdowns, which in return increases energy costs within the system. The optimisation methods used in these studies entail high computational costs and, therefore, impose a strict constraint on the scope of problem.In this study, the use of car-following models and the limitation of the search space of optimal strategies to the parameter space of these is proposed. The proposed framework enables performing much more comprehensive optimisations and conducting more extensive tests on the collective impacts of fuel-economy driving strategies. The results show that, as conjectured, a “short-sighted” user-optimal approach is unable to deliver overall fuel efficiency. Conversely, a system-optimal formulation for fuel efficient driving is presented, and it is shown that the objectives of fuel efficiency and traffic flow are in fact not only non-conflicting, but also that they could be viewed as one when the global benefits to the network are considered.     

Optimum routing of battery electric vehicles: Insights using empirical data and microsimulation

This study investigates the energy consumption impact of route selection on battery electric vehicles (BEVs) using empirical second-by-second Global Positioning System (GPS) commute data and traffic micro-simulation data. Drivers typically choose routes that reduce travel time and therefore travel cost. However, BEVs’ limited driving range makes energy efficient route selection of particular concern to BEV drivers. In addition, BEVs’ regenerative braking systems allow for the recovery of energy while braking, which is affected by route choices. State-of-the-art BEV energy consumption models consider a simplified constant regenerative braking energy efficiency or average speed dependent regenerative braking factors. To overcome these limitations, this study adopted a microscopic BEV energy consumption model, which captures the effect of transient behavior on BEV energy consumption and recovery while braking in a congested network. The study found that BEVs and conventional internal combustion engine vehicles (ICEVs) had different fuel/energy-optimized traffic assignments, suggesting that different routings be recommended for electric vehicles. For the specific case study, simulation results indicate that a faster route could actually increase BEV energy consumption, and that significant energy savings were observed when BEVs utilized a longer travel time route because energy is regenerated. Finally, the study found that regenerated energy was greatly affected by facility types and congestion levels and also BEVs’ energy efficiency could be significantly influenced by regenerated energy.     

Social and spatial effects of transforming the private vehicle fleet in Brisbane,Australia

Transformation of the motor vehicle fleet has been an important feature of the world’s peak car phenomenon. Very few urban transport studies have explored such important changes in large urban cities. Using an innovative green vehicle datasets constructed for 2009 and 2014, this paper investigates the ongoing change in urban private vehicle fleet efficiency (VFE) in Brisbane. The spatial patterns of VFE change were examined with social-spatial characteristics of the urban area. The results showed that the social and spatial effect of VFE changes remain uneven over urban space. The inner urban areas have experienced higher level of VFE change, whilst people in the outer and oil vulnerable areas showed a low tendency in shifting to more efficient vehicles. The implication of VFE change for future household vehicle adoption was also evaluated based on a cost-benefit analysis of new vehicle technology costs and expected fuel savings for households that choose a fuel efficient vehicle. The results show that imposing a stronger national fuel economy target in the long term would accelerate evolution of vehicle fleets and oil vulnerability reduction in Brisbane.