基于Sub_FCM聚类算法的交通流量段自动划分方法
Method of Automatic Programming Traffic Flow Based on Sub_FCM Clustering Algorithm
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摘要: 基于FCM算法提出一种结合减法聚类与聚类有效性评判的模糊c均值聚类算法Sub_FCM,该算法能自动确定合理划分类数并初始化聚类原型,建立一种基于交替优化策略的无监督机器学习自动分类模型,并详细阐述了该模型在怀柔交叉路口流量段自动划分中的具体应用.实例分析表明,该算法能很好地反映路口交通流数据的内在结构,自动划分出合理流量段,为进一步实施合理的控制算法奠定基础.Abstract: A new algorithm based on FCM,Sub_FCM is presented.This algorithm is combined with subtractive clustering and cluster validity evaluation.It can be used to determine the optimal cluster number and initialize clustering prototype automatically.An automatic classification model based on Alternative Optimization strategy and an unsupervised machine learning method are proposed.Experiments show that the internal structure of the traffic flow data is revealed correctly and the proper traffic flow range is determined automatically.The results lay the foundation for applying a proper control algorithm.