聚类分析和支持向量机回归的交通流预测  

Traffic Forecasting Based on Cluster Analysis and Support Vector Machine Regression

作　　者：邓晶[1] 张倩[1] DENG Jing;ZHANG Qian(School of Computer Engineering, Nanjing Institute of Engineering, Nanjing 211167, China)

机构地区：[1]南京工程学院计算机学院

出　　处：《电脑知识与技术》2019年第5X期13-16,共4页Computer Knowledge and Technology

摘　　要：本文以交通流数据为研究对象,主要对数据挖掘技术在交通流预测方面的应用进行了研究和探讨。并基于研究内容,提出了基于聚类分析和支持向量机回归的交通流预测模型。并针对支持向量机参数选择,提出了人工鱼群算法使其快速寻找到最优参数组合。最后,通过实验数据论证本文所提出的算法和模型。This paper takes traffic flow data as the research object, mainly studies and discusses the application of data mining technology in traffic flow prediction. Based on the research content, a traffic forecasting model based on clustering analysis and support vector machine regression is proposed. Aiming at the parameter selection of support vector machine, an artificial fish swarm algorithm is proposed to quickly find the optimal parameter combination. Finally, the algorithm and model proposed in this paper are demonstrated by experimental data.

关 键 词：数据挖掘 交通流预测 聚类分析 支持向量机 人工鱼群算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]