TY  - JOUR
KW  - Mineral oils; Naphthalene; Principal component analysis; Rough set theory; Water treatment plants
KW  -  Clusterings; Environmental data; Low molecular weight; Malaysia; Principal-component analysis; Sampling stations; Sungai perak
KW  -  Polycyclic aromatic hydrocarbons
JF  - Chemical Physics Letters
A1  - Mustafa, S.F.Z.
A1  - Mat Deris, M.
A1  - Abd Manan, T.S.B.
A1  - Beddu, S.
A1  - Mohd Kamal, N.L.
A1  - Mohamad, D.
A1  - Yavari, S.
A1  - Qazi, S.
A1  - Hanafiah, Z.
A1  - Omar Abu Nassar, S.
A1  - Yeoh, K.L.
A1  - Sheriff, I.
A1  - Wan Mohtar, W.H.M.
A1  - Isa, M.H.
A1  - Yusoff, M.S.
A1  - Abdul Aziz, H.
AV  - none
N1  - cited By 1
Y1  - 2023///
TI  - Modelling of similarity characteristics of polycyclic aromatic hydrocarbons (PAHs) in Sungai Perak, Malaysia via rough set theory and principal component analysis (PCA)
N2  - 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�0.8. The Simdegx,y�0.7 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). © 2023 Elsevier B.V.
ID  - scholars18181
VL  - 828
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166185833&doi=10.1016%2fj.cplett.2023.140721&partnerID=40&md5=ed43f2b694312a0b88f3cd3ce15d19e4
ER  -