Comparing prediction methods for maritime accidents

ABSTRACT

The purpose of maritime accident prediction is to reasonably forecast an accident occurring in the future. In determining the level of maritime traffic management safety, it is important to analyze development trends of existing traffic conditions. Common prediction methods for maritime accidents include regression analysis, grey system models (GM) and exponential smoothing. In this study, a brief introduction is provided that discusses the aforementioned prediction models, including the associated methods and characteristics of each analysis, which form the basis for an attempt to apply a residual error correction model designed to optimize the grey system model. Based on the results, in which the model is verified using two different types of maritime accident data (linear smooth type and random-fluctuation type, respectively), the prediction accuracy and the applicability were validated. A discussion is then presented on how to apply the Markov model as a way to optimize the grey system model. This method, which proved to be correct in terms of prediction accuracy and applicability, is explored through empirical analysis. Although the accuracy of the residual error correction model is usually higher than the accuracy of the original GM (1,1), the effect of the Markov correction model is not always superior to the original GM (1,1). In addition, the accuracy of the former model depends on the characteristics of the original data, the status partition and the determination method for the status transition matrix.     

Measuring the influence of bus service quality on the perception of users

Encouraging the use of public transport is a key policy goal in many countries. Therefore, public transport should offer the level of quality that accommodates the demands of current users, and importantly, the desires of potential users. This study investigates the influence of the perceived quality of bus service on the perception of both current and potential users. The study draws upon data from 512 questionnaires distributed across Belfast City in the UK. The study utilises a binary logistic regression model to quantify the relationships between the perceived quality of 29 bus indicators (independent) and the perceptions of users towards the overall bus service (dependent). Eleven significant indicators are reported to have significant influence on the perception of users. These indicators are utilised to propose scenarios for optimising the quality of bus service with the perceptions of current and potential users.     

The relationship between urban street networks and private motorized trips at the city level

There are factors that impact car usage in urban areas, such as density, diversity and design, but there have been few studies that examine the relationship between street network factors and car usage at the city level (macro level). This paper focuses on this relationship by introducing urban street network variables, such as blocks per area, nodes per block and length of roads and motorways, as independent variables and the percentage of daily trips by private motorized modes as the dependent variable. The street network in this study includes interconnecting lines and points that present streets, roads, motorways, intersections and blocks. The strength of the relationship in this study is found using multiple linear regression. The findings of this research indicate that an increase in car usage is correlated with an increasing number of blocks per area, number of nodes per block and length of motorways. In addition, because the urban street network is the result of macro-scale planning decisions, considering this relationship can lead to better planning decisions.     

斜拉桥不确定性参数随机分析研究

为了研究复杂结构体系中不确定性结构参数对其静动力特性的影响,采用多元步进响应面的Monte Carlo法,即将数理统计中的多元步进回归技术引入响应面拟合中,选择出若干个对因变量影响较大的随机变量参与响应面拟合,从而建立一个较为理想和稳定的回归方程,提高响应面的精度,并基于拟合响应面采用拉丁超立方抽样法生成MonteCarlo样本,实现复杂结构体系响应参数的随机分析。采用该方法对润扬大桥北汊斜拉桥静动力特性进行了敏感性因素分析。计算分析表明,斜拉桥主梁质量密度的随机性对其静动力特性最为敏感,同时斜拉索和主梁结构参数的随机性对斜拉桥低阶模态的敏感性较强。所做工作能为斜拉桥结构受力分析提供参考,同时为复杂结构体系不确定性参数的随机分析提供相应的思路。     

客运企业能源消耗统计模型的研究

为了适应当前汽车运输企业的经营现状,通过建立燃油消耗统计模型,对燃油消耗量进行统计。以燃油消耗量为因变量,以影响燃油消耗的因素：周转量、客运量、车龄、驾驶员驾龄、平均车速、实栽率、行驶里程作为自变量,建立多元线性回归模型。通过拟合优度检验、F检验,判断其线性相关性,再运用逐步回归法优化统计模型,从而实现在知道有限数据信息的情况下,预测出该企业当月的车辆燃油消耗总量。将企业调研的实际统计数据代入统计模型计算的燃油消耗量,与实际统计燃油消耗量比较接近,而且统计过程得到简化。结合统计模型的研究方法开发了相应的统计软件。     

人民币对美元汇率影响因素浅析

运用简单线性回归、多自变量回归的经济计量学方法考察了人民币对美元汇率的运行结构,确立了人民币对美元汇率的多因素模型,并通过扩大样本模型检验的方法对1994年我国外汇体制改革前后的人民币对美元汇率模型进行对比分析,提出了对人民币汇率变动趋势的见解。     

基于影响因素分析的船舶交通流量预测多元线性回归模型

随着经济的发展,通过长江水域的船舶数量日益增多,通过对长江镇江段的船舶流量进行调研以及对影响船舶交通流量的因素进行分析,能够更为精确地建立船舶流量预测模型,为预测提供科学依据。     

双断级滑行艇的阻力回归公式

本文以5艘双断级滑行艇模型的试验数据为基础,采用多元线性回归的方法对试验数据进行回归分析,从而导出在不同断级参数情况下双断级滑行艇的阻力回归公式。通过相对误差分析法验证了回归公式的精确性,并根据回归的结果绘制成图以供设计参考。     

货运企业客户价值聚类分析实例

为合理配置营销资源,改善货运企业经营状况,在整合某货运企业15家样本客户相关数据的基础上,计算客户的直接价值和潜在价值,利用SPSS软件对客户价值进行聚类分析,并针对不同价值的客户制定差异化营销策略。     

偏载作用下圆截面墩柱裂缝宽度的简化计算方法

笔者讨论了新《公桥规》中偏载作用下圆截面墩柱裂缝宽度的计算方法,以及传统的用名义拉应力法间接控制裂缝的方法,提出了用名义拉应力直接计算其裂缝宽度的简化计算方法,并对工程中常用的数组数据进行比较验算证明,该计算方法极大地简化了计算程序,并与按新《公桥规》计算的结果吻合较好.