Quality variables are measured much less frequently and usually with a significant time delay by comparison with the measurement of process variables. Monitoring process variables and their associated quality variables is essential undertaking as it can lead to potential hazards that may cause system shutdowns and thus possibly huge economic losses. Maximum correlation was extracted between quality variables and process variables by partial least squares analysis (PLS) (Kruger et al. 2001; Song et al. 2004; Li et al. 2010; Hu et al. 2013; Zhang et al. 2015).


    Access

    Download


    Export, share and cite



    Title :

    Locally Linear Embedding Orthogonal Projection to Latent Structure


    Additional title:

    Intelligent Control & Learning Systems


    Contributors:
    Wang, Jing (author) / Zhou, Jinglin (author) / Chen, Xiaolu (author)


    Publication date :

    2022-01-03


    Size :

    21 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





    Orthogonal locally discriminant spline embedding for plant leaf recognition

    Lei, Y. K. / Zou, J. W. / Dong, T. et al. | British Library Online Contents | 2014


    Modal Identification Method Following Locally Linear Embedding

    Bai, J. / Yan, G. / Wang, C. | British Library Online Contents | 2013


    Fractional Supervised Orthogonal Local Linear Projection

    Zhi, Ruicong / Ruan, Qiuqi | IEEE | 2008


    Conditionally-Linear Filtering Using Conditionally-Orthogonal Projection

    Choukroun, D. / Speyer, J. | British Library Conference Proceedings | 2007


    Linear discriminant projection embedding based on patches alignment

    Wang, J. / Zhang, B. / Qi, M. et al. | British Library Online Contents | 2010