动态导航系统中的语义融合模型研究与实现

发布时间：2018-05-26 16:41

本文选题：动态导航系统 + 语义融合　；参考：《南京邮电大学》2014年硕士论文

【摘要】：智能交通系统在世界范围内得到迅猛发展，交通信息作为其基础与保障也是各国争相研究的热点，目前，各种交通信息采集技术层出不穷，但是，它们对不同交通信息的检测性能是各不相同的，特别是实时动态交通信息。为了满足智能交通系统对交通信息的需求，从多源交通信息中挖掘出更全面、更准确、更深入的信息，并根据智能交通系统使用者对交通信息的不同需求，提供个性化的交通信息服务，，因此需要一种行之有效的智能化交通信息融合技术。本文从智能交通系统的典型应用场景出发，分析其对交通信息智能化融合的需求，并在现有融合模型的基础上提出了一个层次分明、原理清晰、易于实现的交通信息语义融合模型。在此基础上，本文进一步构建了动态导航系统中的语义融合机制，其中包括：在语义编码层提出了一种以路网为主体的交通信息语义编码方法；在语义处理层提出了一种基于可信度的语义逻辑代数方法，能够根据交通信息采集设备的可信度等级对交通信息进行语义融合，该方法提高了交通信息融合的准确度，同时对其设置反馈机制，进一步提高了交通信息质量；在应用服务层，提出了一种基于模糊神经网络的语义融合机制，根据动态导航系统用户对交通信息的偏好权重建立模糊神经网络，并通过权值学习为用户提供个性化的服务。文章最后通过仿真分析与动态导航系统实现表明，本文提出的融合方法提高了交通信息质量，为导航系统提供了智能化服务，从而证明了本文所提出方法的有效性和正确性。
[Abstract]:The intelligent transportation system is developing rapidly in the world, and the traffic information is the base and guarantee of all countries. At present, all kinds of traffic information acquisition technology emerge in endlessly. However, the detection performance of different traffic information is different, especially the real time dynamic traffic information. It needs an effective and intelligent traffic information fusion technology to provide more comprehensive, more accurate and more in-depth information from the multisource traffic information, and to provide personalized traffic information services according to the different needs of the traffic information.
Based on the typical application scene of intelligent transportation system, this paper analyzes its demand for intelligent fusion of traffic information, and puts forward a semantic fusion model with distinct layers, clear principles and easy realization on the basis of the existing fusion model. On this basis, this paper further constructs the semantics of the dynamic navigation system. In the semantic coding layer, a semantic coding method for traffic information is proposed in the semantic coding layer, and a semantic logic algebra based on reliability is proposed in the semantic processing layer, which can be semantically fused according to the reliability level of the traffic information acquisition equipment, and the method is improved. In the application service layer, a semantic fusion mechanism based on fuzzy neural network is proposed to establish a fuzzy neural network based on the preference weight of the traffic information, and the user is proposed by the weight learning for the user. In the end, the simulation analysis and the implementation of the dynamic navigation system show that the fusion method proposed in this paper improves the traffic information quality and provides the intelligent service for the navigation system, which proves the validity and correctness of the proposed method.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP391.1;U495

【相似文献】