NETWORK TRAFFIC PREDICTION MODEL BASED ON VECTOR QUANTIZATION IFTS
Aimed at the limitation of traditional network traffic prediction model,a new network traffic prediction model based on vector quantization intuitionistic fuzzy time series is proposed.The fuzzy intuitionistic reasoning was used to effectively express the high degree of fuzziness and uncertainty in the network traffic data.The vector distance of intuitionistic fuzzy time series was used as the evaluation standard,and through coordinate translation and centroid matching,the classification ability of different time series was improved,thus effectively establishing network traffic prediction model.According to the experimental analysis,the proposed prediction model can improve the prediction accuracy and reduce the computational complexity.In addition,the algorithm has the ability to predict multiple outputs in a long term.
Intuitionistic fuzzy time seriesVector quantizationNetwork trafficLong-term prediction
国家科技期刊平台
NSTL
万方数据
维普
