Application of M5 model tree optimized with Excel Solver Platform for water quality parameter estimation.
Catchment monitoring
Excel Solver Platform (ESP)
M5 mode tree
Water quality
Journal
Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769
Informations de publication
Date de publication:
Feb 2021
Feb 2021
Historique:
received:
12
06
2020
accepted:
28
09
2020
pubmed:
10
10
2020
medline:
30
1
2021
entrez:
9
10
2020
Statut:
ppublish
Résumé
The high cost and time for determining water quality parameters justify the importance of application of mathematical models in discovering connection among them. This paper presents a data mining technique and its improved version in estimating water quality parameters. For this purpose, the surface and ground water quality data from Hamedan (Iran) between 2006 and 2015 were analyzed using M5 model tree and its modified version optimized with Excel Solver Platform (ESP). The values of electrical conductivity (EC), total dissolved solids (TDS), sodium adsorption ratio (SAR), and total hardness (TH) were considered as target variables, whereas pH, concentrations of sodium (Na), chlorine (Cl), bicarbonate (HCO
Identifiants
pubmed: 33033926
doi: 10.1007/s11356-020-11047-w
pii: 10.1007/s11356-020-11047-w
doi:
Substances chimiques
Water Pollutants, Chemical
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7347-7364Références
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