TY  - JOUR
AU  - Rahman, Vijay
AU  - Rossi, Elena
AU  - Karimi, Tanvir
TI  - K-Means Clustering for Dye Adsorption
JO  - Open Access Journal of Engineering Applications
PY  - 2005
VL  - 29
IS  - 2
SP  - 906
EP  - 913
AB  - Failures observed in existing renewable energy systems have highlighted the need for a deeper understanding of dye adsorption. The proposed algorithm uses k-means clustering to search efficiently for the optimum design of renewable energy systems. Field trials conducted at 7 separate sites yielded consistent and reproducible estimates of dye adsorption. Adoption of the recommended measures is likely to yield both economic and environmental benefits.
KW  - dye adsorption
KW  - k-means clustering
KW  - natural convection
KW  - gas turbine
KW  - adsorption
SN  - 3105-7004
DO  - 10.55555/oajea.2005.2902.047
UR  - https://journal.bsaps.com/article/8264
ER  -