基于最优组合马尔柯夫链的业务量预测模型

提出了一种基于最优组合马尔柯夫链的业务量预测模型，通过分析影响业务量变化的各种因素，建立了最优组合模型来预测业务量，其最优加权系数依据最小二乘法原理确定，该模型的主要特点是综合考虑了移动台数量与业务量的动态分布，避免了单一预测模型仅利用部分信息而带来的不足，仿真结果证实了该模型较单一预测方法降低了预测误差，提高了预测精度，为研究系统性能、提高服务质量提供了有效措施。

Traffic Load Forecast Model by Optimally Combined Markov Chain

A traffic load forecast model by optimally combined Markov chain is presented. The optimally combined model is set up to derive the forecast results by analyzing the factors that affect the variations of traffic load, and the weighting coefficients are derived according to least square principle. The main characteristic of using composite model instead of only one method is that it can make the most of the available factors of the dynamic distribution of mobile station and traffic load so as to avoid the drawback that only partial information is used. Simulation results show that the model can reduce the prediction error and yield higher forecast precision compared to using only one method, and it therefore provides a valuable means for evaluating the system performance and yield better service performance.