基于线性叠加的智能船舶经济性评估模型构建

经济性是智能船舶能否实现推广应用的关键,目前国内外有关智能船舶经济性分析的研究较少。本文通过对传统船舶经济性分析方法进行修正优化,提出智能船舶经济性分析计算模型,并根据理论推导结果,得出智能船舶经济性分析的线性叠加简化模型,并利用40万吨级VLOC实际运营数据进行科学性检验。本文提出的模型与方法适用于各类智能模块加装情况下的经济性核算,为相关单位开展智能船舶经济性快速分析提供了理论支持和解决方案。     

公共自行车使用时空特性挖掘及租还需求预测

基于宁波市公共自行车刷卡数据、POI(Point of Interest)数据、气象和空气质量等数据，从数据驱动视角，深入挖掘公共自行车使用的时空特征及站点租还车需求预测。在时间上，采用KMeans算法，将站点聚为5类，探讨各类站点的时变需求规律及影响因素；在空间上，提出基于POI 数据的站点用地类型识别方法，将站点分为居住类、交通设施类、办公类和商业休闲类。构建以 15，30，60 min 为间隔，以租还车需求为目标变量的随机森林预测模型，并与常用的 BP (Back Propagation)神经网络、K最近邻方法进行比较。结果表明，随机森林模型的精度更高，适用性更强。以30 min为间隔的站点租还车需求预测精度最高，考虑站点土地利用类型后能有效提高模型的预测精度。本文结果可作为未来站点平衡调度的依据并推广应用于共享单车系统，为改善服务水平提供技术和理论支撑。     

Widening the Panama Canal and U.S. ports: historical and economic impact analyses

ABSTRACT

The economic history of the U.S. illustrates how the role of many cities has been changed by being seaports or located on navigable rivers or lakes. Based on the widening of the Panama Canal in 2016, the West Coast ports that include the west coast seaports of California, Oregon, and Washington were expected to become less important, while the freight shares of the East Coast and Gulf ports would increase. By how much it has been not easy to measure or predict so far, but this study attempted to define some of the key parameters in the measurement. As well as several relevant background topics, both the demand- and supply-side versions of the National Interstate Economic Model, have been applied for the measurement of economic impacts. U.S. port authorities and policy makers at the local and national levels who respond and develop plans for coping with the new realities of the Panama Canal are able to understand the extent to which changes in shippers’ and land-mode transporters’ behaviors would undermine the logistics and the costs of their activities. Therefore, this study is important for a diverse spectrum of port development strategies in the U.S. to respond to the Canal expansion.     

Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

造船经济论证方法的探讨

船舶经济分析是船舶技术经济论证的主要环节之一,但传统的造船经济论证方法存在着一定的缺陷。为此,充分考虑各个因素的不确定性,考虑经营的风险性,对传统的造船经济论证方法加以综合改进,形成新的造船论证方法——计算机模拟方法。与传统方法相比,计算机模拟的方法在最终结果的处理上更有现实意义。     

从温州经济模式学到的经验

叙述了温州经济模式的发展 ,并总结了温州模式的思想精髓     

江淮气旋大风预报研究

江淮气旋大风预报研究的结果表明：气旋大风的预报实际上就是冷空气南下造成地面加压与气旋东移造成地面降压，这两个因素所造成气压梯度发展变化地以预报。还介绍用天气学原理建立的大风预报模式，以及用数理统计方法判别有无强风的预报，经过历史拟合和试报，在预报气旋大风中有一定的准确性。     

带孔沉箱结构类型与经济效益分析

通过大连华能电厂的循环水取水口工程实例,对不同的大型带孔沉箱结构进行了结构和经济效益的分析比较,以期推广受力性能较好、施工方便可行、经济效益较好的新型沉箱结构。     

对中国未来10年道路交通安全状况分析与初步预测

笔者从中国现代道路交通系统的发展现状与道路交通安全状况出发，以过去10多年中国汽车、摩托车保有量的发展轨迹为基础，对中国未来一定时期（2004～2015年）机动车保有量的发展变化及政府采取不同管理对策条件下的道路交通安全状况的发展水平进行了预测。结果表明：政府管理对策对道路交通安全状况变化具有决定性影响。     

GM(1,1)模型与指数模型在基桩沉降预测中的应用

以某大型基桩的沉降预测为例,利用灰色系统理论的GM(1,1)与Aeax曲线模型进行基桩在外荷载作用下沉降量的预测。结果表明:两种模型对于呈指数变化规律的系统能获得较好的预测结果;两种模型对基桩累计沉降的预测符合工程实际,对各级荷载作用下的本级沉降预测不够合理。对两种模型关系的研究表明,两者有内在联系,都属指数曲线预测模型,且指数曲线Aeax预测模型比GM(1,1)模型应用起来更简单,方便。