计算机工程与应用2016，Vol.52Issue(12)：90-94,5.DOI:10.3778/j.issn.1002-8331.1501-0160
呼叫中心分块回归话务量预测
Block regression traffic prediction model for call center
摘要
Abstract
In order to obtain the prospective traffic data, solve the seats arrangement problem of call center, realize the rational allocation of human resources, block regression traffic prediction model, based on support vector machine and K-nearest neighbor algorithm is proposed(SKBR), after analyzing the characteristics of historical traffic data. According to the date type, traffic can be divided into weekday traffic, weekend traffic and holiday traffic, and different model is used to predict the corresponding traffic. Taking the traffic of a province electric power call center for example, experiments are carried on the MATLAB platform. Results show that compared with the SVM model and improved SVM model for its method of searching parameters, SKBR model has improved the prediction accuracy.关键词
话务量/预测/支持向量机/近邻算法/预测准确性Key words
traffic/prediction/support vector machine/nearest neighbor algorithm/prediction accuracy分类
信息技术与安全科学引用本文复制引用
张沪寅,胡瑞芸,何政..呼叫中心分块回归话务量预测[J].计算机工程与应用,2016,52(12):90-94,5.基金项目
高等学校博士学科点专项科研基金（No.20130141110022）；武汉市科学技术局（No.201302038）。 （）
