摘要
移动通信话务数据具有强非线性,传统的预测技术很难准确预测其变化规律.文中根据移动通信话务量的特点,对移动通信话务数据进行分块建模———采用最近邻模糊聚类算法对周期分量模块进行建模,采用线性回归方法对趋势分量模块进行建模,并据此设计了一种智能型的自适应最优模糊逻辑话务预测系统,进而对广东某地区的话务数据进行了预测.现场调试结果表明,该预测系统能有效预测移动通信的话务量.
It is difficult to correctly forecast mobile telephone traffic data by the traditional method because of the strong nonlinearity of the data. In order to overcome the difficulty, this paper proposes a new approach to forecast mobile telephone traffic data. According to the characteristics of mobile telephone traffic, the mobile telephone traffic data is divided into two parts： the periodic traffic modeled by the first closest clustering method and the trend traffic modeled by the liner regression method. Hereby, an adaptive optimized fuzzy logical forecasting system is designed, which is then tested by all data in a mobile telephone system of Guangdong Province. The testing results show that the proposed system is effective in the forecasting of mobile telephone traffic.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第12期66-69,共4页
Journal of South China University of Technology(Natural Science Edition)
关键词
话务预测
最近邻模糊聚类
话务建模
traffic forecasting
first closest fuzzy clustering
traffic modeling
