@article{scholars18181,
         journal = {Chemical Physics Letters},
           title = {Modelling of similarity characteristics of polycyclic aromatic hydrocarbons (PAHs) in Sungai Perak, Malaysia via rough set theory and principal component analysis (PCA)},
            year = {2023},
             doi = {10.1016/j.cplett.2023.140721},
            note = {cited By 1},
          volume = {828},
          author = {Mustafa, S. F. Z. and Mat Deris, M. and Abd Manan, T. S. B. and Beddu, S. and Mohd Kamal, N. L. and Mohamad, D. and Yavari, S. and Qazi, S. and Hanafiah, Z. and Omar Abu Nassar, S. and Yeoh, K. L. and Sheriff, I. and Wan Mohtar, W. H. M. and Isa, M. H. and Yusoff, M. S. and Abdul Aziz, H.},
        abstract = {This paper presents application of rough set theory and PCA for modelling of similarity characteristics of PAHs from Perak River: Tanjung Belanja Bridge (TBB, l1), Water Treatment Plant Parit (WTPP, l2), Parit Town Discharge (PTD, l3), Water Treatment Plant Senin (WTPS, l4), and Water Treatment Plant Kepayang (WTPK, l5). The clustering involved PAHs as attributes and sampling stations as objects. The l1 and l3 were clustered in Simdegx,y{\^a}?Y0.8. The Simdegx,y{\^a}?Y0.7 was observed in all attributes (except l5) forming two sets of clusters. PCA showed that low molecular weight (LMW) PAHs were prominent with variances of 68.47 (naphthalene, Nap) and 27.63 (carbazole). {\^A}{\copyright} 2023 Elsevier B.V.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166185833&doi=10.1016\%2fj.cplett.2023.140721&partnerID=40&md5=ed43f2b694312a0b88f3cd3ce15d19e4},
        keywords = {Mineral oils; Naphthalene; Principal component analysis; Rough set theory; Water treatment plants, Clusterings; Environmental data; Low molecular weight; Malaysia; Principal-component analysis; Sampling stations; Sungai perak, Polycyclic aromatic hydrocarbons}
}