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  1. No Access

    Chapter and Conference Paper

    Parallel Feedforward Process Neural Network with Time-Varying Input and Output Functions

    In reality, the inputs and outputs of many complicated systems are time-varied functions. However, conventional artificial neural networks are not suitable to solving such problems. In order to overcome this l...

    Shisheng Zhong, Gang Ding, Daizhong Su in Advances in Neural Networks – ISNN 2005 (2005)

  2. No Access

    Chapter and Conference Paper

    Approximation Capability Analysis of Parallel Process Neural Network with Application to Aircraft Engine Health Condition Monitoring

    Parallel process neural network (PPNN) is a novel spatio-temporal artificial neural network. The approximation capability analysis is very important for the PPNN to enhance its adaptability to time series pred...

    Gang Ding, Shisheng Zhong in Advances in Neural Networks – ISNN 2007 (2007)

  3. No Access

    Chapter and Conference Paper

    Aeroengine Turbine Exhaust Gas Temperature Prediction Using Support Vector Machines

    The turbine exhaust gas temperature (EGT) is an important parameter of the aeroengine and it represents the thermal health condition of the aeroengine. By predicting the EGT, the performance deterioration of t...

    Xuyun Fu, Gang Ding, Shisheng Zhong in Advances in Neural Networks – ISNN 2009 (2009)

  4. No Access

    Article

    CSiamese: a novel semi-supervised anomaly detection framework for gas turbines via reconstruction similarity

    The main problem in data-driven anomaly detection of gas turbines is that the monitoring data consists of only a very small number of abnormal samples with the overwhelming majority of normal samples. To addre...

    Dan Liu, Shisheng Zhong, Lin Lin, Minghang Zhao… in Neural Computing and Applications (2023)