基于小波支持向量机的多式联运风险分析

发布时间：2018-03-15 23:20

本文选题：多式联运　切入点：风险分析　出处：《大连海事大学》2015年硕士论文　论文类型：学位论文

【摘要】：随着现代科学技术的发展、经济区域的扩张,社会竞争日益激烈,市场的需求已不再局限于传统的单一运输方式。未来货物运输的发展方向将是高效、综合的货运系统,使得各种运输方式有效衔接,实现一体化,而能够满足这种现代物流运输需求的运输体系就是多式联运。作为一种先进的运输组织形式,多式联运能够充分发挥各种不同运输方式的内在优势,实现货物运输的完整性和高效率。但是,多式联运作为一个运输系统,难免会受到各种因素的影响,导致货运风险不断增加。因此,有效降低和规避风险显得格外重要。本文按照风险识别、风险评价、风险处理的步骤,对多式联运的风险进行了分析。首先,总结了国内外多式联运的研究现状,并系统阐述了多式联运风险及风险分析的理论体系。其次,综合分析多式联运过程中存在的不确定影响因素,识别出影响多式联运系统的内外因素,初步建立了一套全面反映多式联运风险水平的指标体系。并根据粗糙集理论对指标进行约简,筛选出20个关键性指标。再次,本文构建了小波函数作为支持向量机的核函数,建立了小波支持向量机模型,对多式联运进行风险评价。最后,将该模型和算法应用到实例中,在MATLAB环境下采用LibSVM软件实现。将结果与其他方法进行了比较分析,验证了该方法的有效性,为多式联运风险分析提供了科学依据。在此基础上,针对不同的风险因素,简要提出了相应的风险处理措施。
[Abstract]:With the development of modern science and technology, the expansion of economic regions and the increasingly fierce social competition, the market demand is no longer confined to the traditional single mode of transportation. In the future, the development direction of freight transportation will be efficient and integrated freight transportation system. The transportation system that can meet the demand of modern logistics transportation is multimodal transport. As an advanced form of transportation organization, Multimodal transport can give full play to the inherent advantages of different modes of transport and achieve the integrity and high efficiency of the transport of goods. However, as a transport system, multimodal transport is inevitably affected by various factors. This paper analyzes the risk of multimodal transport according to the risk identification, risk evaluation and risk handling steps. First of all, the risk of multimodal transport is analyzed. The research status of multimodal transport at home and abroad is summarized, and the theoretical system of risk and risk analysis of multimodal transport is systematically expounded. Secondly, the uncertain influencing factors in multimodal transport process are comprehensively analyzed. The internal and external factors affecting multimodal transport system are identified, and a set of index system is established to reflect the risk level of multimodal transport. According to rough set theory, the index is reduced and 20 key indexes are screened out. In this paper, the wavelet function is constructed as the kernel function of support vector machine, and the wavelet support vector machine model is established to evaluate the risk of multimodal transport. Finally, the model and algorithm are applied to an example. The results are compared with other methods, and the validity of the method is verified, which provides a scientific basis for the risk analysis of multimodal transport. On this basis, different risk factors are analyzed. The corresponding risk treatment measures are put forward briefly.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F512.4

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