基于遗传模糊系统的交通数据空间插值

D. Ichiba, K. Hara, H. Kanoh
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引用次数: 7

摘要

提出了一种利用遗传模糊系统(gfs)插值道路交通数据的方法。在日本,汽车导航设备为驾驶员提供主要道路的实时交通信息。这些信息可以提供路线指导。在以往的研究中,由于人是经验地设计模糊c均值(FCM)的隶属度函数,该方法存在以下两个问题。一个事实是设计成本很高;另一个是最优地调优成员函数是困难的。我们使用遗传算法(GA)自动调整隶属函数。将隶属函数编码为遗传算法的一条染色体,并用实际交通数据计算的平均日误差的平均值作为适应度函数。使用实际交通数据和实际路线图进行的实验表明,该方法比传统方法更有效
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Interpolation of Traffic Data by Genetic Fuzzy System
We propose a method to interpolate traffic data of roads using genetic fuzzy systems (GFSs). In Japan, car navigation equipment provides drivers with real-time traffic information about principal roads. The information enables giving route guidance. In a previous study, the problem of the method lies in the following two facts because a human designs membership functions of fuzzy c-means (FCM) experientially. One fact is that the design cost is high; the other is that tuning membership functions optimally is difficult. We automatically tune membership functions using a genetic algorithm (GA). The membership functions are encoded as a chromosome of GA, and the average of mean daily errors calculated from actual traffic data is used as a fitness function. Experiments using actual traffic data and an actual road map indicate that our method is more effective than the conventional method
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