Extension Neural Network Based on Immune Algorithm for Fault Diagnosis

Hybrid computing techniques for fault detection and isolation, a review

“…A neural networks based inference had been implemented on an oscillation-based analog diagnosis in Stošović et al [39]. In [40], Xiang et al developed a hybrid neural network with an immune algorithm for fault diagnosis problem. Nevertheless, most of the work on improvement of performance of standard backpropagation neural networks for fault diagnosis is based on the idea of explicit feature presentation of the neural networks as proposed in [41], Farell and Roat [42], Honggui et al [43], and Smail et al [44].…”