Similarity Search in Time Series Database Based on SOFM Neural Network

摘要：

A novel algorithm for the similarity search in time series database is proposed. Considering the neural networks poor capability when handling with time change process sequence, the original data is mapped into the feature pattern space by means of Discrete Cosine Transform (DCT) for dimension reduction. By analyzing the advantages when the artificial neural network is used as similarity measurement model, the All-pairs query algorithm is presented based on SOFM neural network. For this experiment we examined the real flight data, the simulation result shows the proposed method is correct, and it has multi-scale feature and can reflect different similarity of time series under the various resolution.

关键词： Discrete Cosine Transform Artificial Neural Network Time series Similarity Search Multi-scale

作者: Zhang Peng Du Jun Zhang Jianye Li Xueren

作者单位: Air force Engineering University Engineering College,Xian 050003 China Department of Automatic Control,Northwestern Polytechnical University,Xian 710072 China

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）