ISBN 555555555/$10.00  2002 IEEE Abstract – The normal and the abnormal behaviors in networked computers are hard to predict, as the boundaries cannot be well defined. This prediction process usually generates false alarms in many anomaly based intrusion detection systems. However, with fuzzy logic, the false alarm rate in determining intrusive activities can be reduced, where a set of fuzzy r...

Abstract With the proposal of smart grid, demand both source and load for fine monitoring control power is becoming increasingly prominent. Non-intrusive a technical means to better meet this demand. However, research at home abroad focuses on existing data sets labeled improve accuracy identification, while training method model under massive unlabeled in actual scene still relatively blank st...

At present, the non-intrusive load decomposition method for low-frequency sampling data is as yet insufficient within context of generalization performance, failing to meet accuracy requirements when applied novel scenarios. To address this issue, a based on instance-batch normalization network proposed. This uses an encoder-decoder structure with attention mechanism, in which skip connections ...

With the ever-growing number of elevators coupled with aging workforce, diminishing new installations and limited use maintenance technology, it is increasingly challenging for owners responsible parties to maintain safe reliable operation lift systems. To address this issue, a non-intrusive artificial intelligence (AI) based diagnosis system, aiming at providing fault detection potential predi...