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针对目前交通模式识别以人工设计特征为主,特征设计主观性强、区分度不高的问题,本文依据深度学习理论,建立了基于卷积神经网络的特征自动学习模型。该模型利用卷积神经网络自动学习深度特征,然后与人工特征共同用于交通模式识别。模型基于微软Geo Life数据,针对不同特征组合与分类方法设计实验,实验结果表明模型能学习到高区分度深度特征、有效提高交通模式识别准确率。 相似文献
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Microblogs currently play an important role in social communication. Hot topics currently being tweeted can quickly become popular within a very short time as a result of re-tweeting. Gaining an understanding of the retweeting behavior is desirable for a number of tasks such as topic detection, personalized message recommendation, and fake information monitoring and prevention. Inter-estingly, the propagation of tweets bears some similarity to the spread of infectious diseases. We present a method to model the tweets’ spread behavior in microblogs based on the classic Susceptible-Infectious-Susceptible (SIS) epidemic model that was developed in the medical field for the spread of infectious dis-eases. On the basis of this model, future re-tweeting trends can be predicted. Our experi-ments on data obtained from the Chinese micro-blog?ging website Sina Weibo show that the proposed model has lower predictive error compared to the four commonly used predic-tion methods. 相似文献
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信息描述字典是参数信息的描述表集,通过提炼参数的共性和特征使参数处理统一化,使得程序处理与数据格式相对独立,减少程序对数据的依赖。 相似文献
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