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Research on multimedia image classification technology based on chaos optimization machine learning algorithm
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DOI：10.1007/s11042-019-7636-y.png)
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摘要
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With the advent of the era of information explosion, multimedia big data with images as the main carrier has increased dramatically and has penetrated into various fields of people's lives. As the basis of image recognition, classification has become an important tool for analyzing and understanding image information. Therefore, how to quickly and efficiently image classification has become a challenging research hotspot. In order to solve the limitation of traditional machine learning algorithm in classification performance, an image classification method based on chaotic optimization machine learning algorithm is proposed. This method combines the support vector machine in the machine learning algorithm with the chaotic time series to construct the classification prediction model. The particle swarm optimization algorithm is used to realize the optimal parameter search of the support vector machine to improve the performance of the prediction model. The test results show that compared with other multi-machine learning algorithm predictions, the proposed method effectively reduces the dependence of classification results on sample types and features, and has a higher and robust classification effect.
Keyword:
Image classification
Machine learning
Chaotic time series
Support vector machine
Particle swarm optimization
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期刊
IF:
3
论文数:
1.9W
被引数:
3.2W
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