计算机科学 ›› 2011, Vol. 38 ›› Issue (3): 266-268.
• 人工智能 • 上一篇 下一篇
熊勰,刘光远,温万惠
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XIONG Xie,LIU Guang-yuan,WEN Wan-hui
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摘要: 针对基于生理信号的情感识别问题,采用具有模拟退火机制的遗传算法、最大最小蚁群算法和粒子群算法来进行特征选择,用Fisher分类器对高兴、惊奇、厌恶、悲伤、愤怒和恐惧6种情感进行分类,获得了较高的识别率,并找出了对情感识别系统模型的构建具有较好性能的特征组合,建立了对6类情感具有预测能力的识别系统。
关键词: 情感识别,特征选择,智能算法
Abstract: For the problem of emotion recognition, genetic algorithm based on simulated-annealing method, max-min ant colony algorithm and particle swarm algorithm were used for feature selection, and combined with Fisher linear classifier to recognize six emotions: joy, surprise, disgust, grief, anger and fear, it has obtained higher recognition rate. Effective feature subset which can identify the emotion recognition system model with better perfomfance was found, and the recognition system was established with forecasting ability of six emotions.
Key words: Emotion recognition, Feature selection, Intelligent algorithm
熊勰,刘光远,温万惠. 基于智能算法的生理信号情感识别[J]. 计算机科学, 2011, 38(3): 266-268. https://doi.org/
XIONG Xie,LIU Guang-yuan,WEN Wan-hui. Emotion Recognition of Physiological Signals Based on Intelligent Algorithm[J]. Computer Science, 2011, 38(3): 266-268. https://doi.org/
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