SRPM–CNN: a combined model based on slide relative position matrix and CNN for time series classification

Research on the time series classification is gaining an increased attention in the machine learning and data mining areas due to the existence of the time series data almost everywhere, especially in our daily work and life. Recent studies have shown that the convolutional neural networks (CNN) can...

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Veröffentlicht in:Complex & Intelligent Systems 2021-06, Vol.7 (3), p.1619-1631
Hauptverfasser: Li, Taoying, Zhang, Yuqi, Wang, Ting
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description Research on the time series classification is gaining an increased attention in the machine learning and data mining areas due to the existence of the time series data almost everywhere, especially in our daily work and life. Recent studies have shown that the convolutional neural networks (CNN) can extract good features from the images and texts, but it often encounters the problem of low accuracy, when it is directly employed to solve the problem of time series classification. In this pursuit, the present study envisaged a novel combined model based on the slide relative position matrix and CNN for time series. The proposed model first adopted the slide relative position for converting the time series data into 2D images during preprocessing, and then employed CNN to classify these images. This made the best of the temporal sequence characteristic of time series data, thereby utilizing the advantages of CNN in image recognition. Finally, 14 UCR time series datasets were chosen to evaluate the performance of the proposed model, whose results indicate that the accuracy of the proposed model was higher than others.
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subjects Analysis
Artificial neural networks
Complexity
Computational Intelligence
Computational linguistics
Data mining
Data Structures and Information Theory
Engineering
Feature extraction
Image classification
Language processing
Machine learning
Model accuracy
Natural language interfaces
Neural networks
Object recognition
Original Article
Time series
title SRPM–CNN: a combined model based on slide relative position matrix and CNN for time series classification
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