Chemometrics and Intelligent Laboratory Systems

Chemometrics and Intelligent Laboratory Systems

ISSNs: 0169-7439

Elsevier

Scopus rating (2021): CiteScore 5.5

Journal

Journal Metrics

Research Output

  1. 2020
  2. Published

    Distribution-free hybrid schemes for process surveillance with application in monitoring chlorine content of water

    Sanusi, R. A., Chong, Z. L., Mukherjee, A. & Xie, M., 15 Nov 2020, In: Chemometrics and Intelligent Laboratory Systems. 206, 104099.

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 1
    Check@CityULib
  3. Published

    Sparse Bayesian learning approach for baseline correction

    Li, H., Dai, J., Pan, T., Chang, C. & So, H. C., 15 Sep 2020, In: Chemometrics and Intelligent Laboratory Systems. 204, 104088.

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 1
    Check@CityULib
  4. Published

    Improved linear profiling methods under classical and Bayesian setups: An application to chemical gas sensors

    Abbas, T., Mahmood, T., Riaz, M. & Abid, M., 15 Jan 2020, In: Chemometrics and Intelligent Laboratory Systems. 196, 14 p., 103908.

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 15
    Check@CityULib
  5. 2016
  6. Data-driven root cause diagnosis of faults in process industries

    Li, G., Qin, S. J. & Yuan, T., 15 Dec 2016, In: Chemometrics and Intelligent Laboratory Systems. 159, p. 1-11

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 54
    Check@CityULib