@article{scholars1197,
            year = {2010},
          volume = {68},
            note = {cited By 3},
           pages = {264--271},
           title = {A black-box approach in modeling valve stiction},
         journal = {World Academy of Science, Engineering and Technology},
          author = {Zabiri, H. and Mazuki, N.},
            issn = {2010376X},
        abstract = {Several valve stiction models have been proposed in the literature to help understand and study the behavior of sticky valves. In this paper, an alternative black-box modeling approach based on Neural Network (NN) is presented. It is shown that with proper network type and optimum model structures, the performance of the developed NN stiction model is comparable to other established method. The resulting NN model is also tested for its robustness against the uncertainty in the stiction parameter values. Predictive mode operation also shows excellent performance of the proposed model for multi-steps ahead prediction.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751638301&partnerID=40&md5=a54f4a6cc2a57fe68c9b8be310854fb0},
        keywords = {Black box approach; Black-box modeling; Control valve stiction; Excellent performance; Mode operation; Modeling; Network types; Parameter values; Stiction models, Behavioral research; Model structures; Safety valves; Stiction; Structural optimization, Neural networks}
}