摘要
为了有效提高无线传感器网络流量预测精度,结合α-稳定分布和小波变换,提出了一种新的预测算法(state prediction algorithm based onα-stable distribution,SP-α)。该算法定义了α-稳定分布特征,并给出服从该分布的判断依据。同时,通过融合α-稳定分布和小波变换的预测结果,减少实际流量的预测误差。以OPNET和MATLAB进行联合仿真,深入研究了影响该算法的关键因素,并对比FARIMA模型性能,结果发现SP-α算法具有较好的适应性。
In order to improve the prediction accuracy of wireless sensor network,this paper proposed a novel prediction algorithm( state prediction algorithm based on α-stable distribution,SP-α) by α-stable distribution and wavelet transform. This algorithm defined the characteristic of α-stable distribution,and gave the judgment of obeying distribution. Then,it decreased the prediction error of actual traffic by fusion the results of α-stable distribution and wavelet transform. Finally it conducted a simulation to study the key influence factor of algorithm with OPNET and MATLAB. The results show that,compared to FARIMA model,SP-α has better suitability.
出处
《计算机应用研究》
CSCD
北大核心
2014年第8期2457-2460,共4页
Application Research of Computers
基金
重庆市教委科学技术研究项目(KJ133103)
江苏省自然科学基金资助项目(BK2011152)
中国科学院计算机科学国家重点实验室开放项目(CSYSKF0908)
关键词
无线传感器网络
预测
α-稳定分布
小波
误差
wireless sensor network
prediction
α-stable distribution
wavelet
error