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Creators/Authors contains: "Zhou, Yuxun"

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  1. ; ; ; ; ; (, IEEE Control Systems Letters)
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  2. ; ; ; ; (, IEEE Transactions on Industrial Electronics)
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  3. ; ; ; ; (, 2018 IEEE Conference on Decision and Control (CDC))
    A novel multivariate deep causal network model (MDCN) is proposed in this paper, which combines the theory of conditional variance and deep neural networks to identify the cause-effect relationship between different interdependent time-series. The MCDN validation is conducted by a double step approach. The self validation is performed by information theory - based metrics, and the cross validation is achieved by a foresting application that combines the actual interdependent electricity, transportation, and weather datasets in the City of Tallahassee, Florida, USA. 
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  4. ; ; (, IEEE Transactions on Smart Grid)
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  5. ; ; ; ; ; (, 2017 IEEE Manchester PowerTech)
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