@article{MAKHILLIJSSCEA201811128764,
    title = {Modeling of Temporal Stability to Critical States for
Predicting Operational Safety of Turbogenerators},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {11},
    number = {1},
    pages = {13-19},
    year = {2018},
    issn = {1997-5422},
    doi = {ijssceapp.2018.13.19},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2018.13.19},
    author = {Dmitry Aleksandrovich,Aleksandr Sergeyevich,Andrey Vladimirovich,Sergey Aleksandrovich and},
    keywords = {Forecasting,adaptive reaction,safety of industrial objects,critical condition,reaction modeling,temporal stability},
    abstract = {The study is devoted to the creation of a method for predicting the temporal stability under
conditions of dynamic and static effects during process of operation of a turbogenerator. The method is based
on the restoration modeling the operating mode of the turbogenerator under critical conditions; the model
assumes an adaptive response at the initial stage of the critical state recognition. The deep neural network
teaching technique whilst the classification of spectrogram anomalies is provided.}
    }