FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3088296465> ?p ?o ?g. }

• W3088296465 endingPage "124206" @default.
• W3088296465 startingPage "124206" @default.
• W3088296465 abstract "The precise estimation of spatial variation of groundwater quality variables is necessary for making appropriate decisions regarding aquifer resources management and environmental systems. The aim of this research is to evaluate five different data-intelligent methods so as to get the best one in spatial estimation of electrical conductivity (EC) and total hardness (TH) of groundwater resources. The study uses water quality data including Na, Cl, Mg, Ca, SO4, HCO3, TH, and EC, observed at 367 wells, in the Chhattisgarh state, central India. Four different scenarios are decided by implementing Gamma and linear regression methods. Data-intelligent methods applied to selected scenarios to estimate EC and TH are dynamic evolving neural-fuzzy inference system (DENFIS), group method of data handling (GMDH), multivariate adaptive regression spline (MARS), M5 Tree model (M5 Tree), and gene expression programming (GEP). Evaluation of the methods with respect to correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE), Nash-Sutcliffe efficiency (NSE), Legates and McCabe index (LMI), and Willmott index of agreement (WI) indicates that the GEP for the input combination including TH, Na, Cl, HCO3 variables and the DENFIS by employing Ca, Mg, EC variables provide the best accuracy in estimating EC and TH, respectively. The statistical metrics of the GEP (DENFIS) for the best scenario are R = 0.970 (0.958), NSE = 0.941 (0.917), RMSE = 105.317 μs/cm (34.692 mg/L), MAE = 57.075 μs/cm (12.603 mg/L), WI = 0.984 (0.979) and LMI = 0.824 (0.868). The spatial distribution maps indicate that the EC and TH values of groundwater resources in the studied area are in their permissible limits for drinking consumption and the interpolated maps of the data-intelligent techniques have suitable precision in comparison with the observed maps." @default.
• W3088296465 created "2020-10-01" @default.
• W3088296465 creator A5016315589 @default.
• W3088296465 creator A5020118515 @default.
• W3088296465 creator A5039175272 @default.
• W3088296465 creator A5070423702 @default.
• W3088296465 creator A5079408919 @default.
• W3088296465 creator A5088432880 @default.
• W3088296465 date "2020-12-01" @default.
• W3088296465 modified "2023-09-23" @default.
• W3088296465 title "Exploring the application of soft computing techniques for spatial evaluation of groundwater quality variables" @default.
• W3088296465 cites W1977064421 @default.
• W3088296465 cites W2007495462 @default.
• W3088296465 cites W2034159055 @default.
• W3088296465 cites W2038458563 @default.
• W3088296465 cites W2045464761 @default.
• W3088296465 cites W2058998332 @default.
• W3088296465 cites W2066003898 @default.
• W3088296465 cites W2066636447 @default.
• W3088296465 cites W2066660768 @default.
• W3088296465 cites W2076063813 @default.
• W3088296465 cites W2162635690 @default.
• W3088296465 cites W2285539412 @default.
• W3088296465 cites W2512849376 @default.
• W3088296465 cites W2529179410 @default.
• W3088296465 cites W2897565907 @default.
• W3088296465 cites W2904258885 @default.
• W3088296465 cites W2907283755 @default.
• W3088296465 cites W2920998881 @default.
• W3088296465 cites W2921197958 @default.
• W3088296465 cites W2921869001 @default.
• W3088296465 cites W2947574711 @default.
• W3088296465 doi "https://doi.org/10.1016/j.jclepro.2020.124206" @default.
• W3088296465 hasPublicationYear "2020" @default.
• W3088296465 type Work @default.
• W3088296465 sameAs 3088296465 @default.
• W3088296465 citedByCount "15" @default.
• W3088296465 countsByYear W30882964652021 @default.
• W3088296465 countsByYear W30882964652022 @default.
• W3088296465 countsByYear W30882964652023 @default.
• W3088296465 crossrefType "journal-article" @default.
• W3088296465 hasAuthorship W3088296465A5016315589 @default.
• W3088296465 hasAuthorship W3088296465A5020118515 @default.
• W3088296465 hasAuthorship W3088296465A5039175272 @default.
• W3088296465 hasAuthorship W3088296465A5070423702 @default.
• W3088296465 hasAuthorship W3088296465A5079408919 @default.
• W3088296465 hasAuthorship W3088296465A5088432880 @default.
• W3088296465 hasConcept C105795698 @default.
• W3088296465 hasConcept C119857082 @default.
• W3088296465 hasConcept C124101348 @default.
• W3088296465 hasConcept C127413603 @default.
• W3088296465 hasConcept C128990827 @default.
• W3088296465 hasConcept C129360787 @default.
• W3088296465 hasConcept C139945424 @default.
• W3088296465 hasConcept C140073362 @default.
• W3088296465 hasConcept C154945302 @default.
• W3088296465 hasConcept C161584116 @default.
• W3088296465 hasConcept C187320778 @default.
• W3088296465 hasConcept C18903297 @default.
• W3088296465 hasConcept C2780797713 @default.
• W3088296465 hasConcept C33923547 @default.
• W3088296465 hasConcept C39432304 @default.
• W3088296465 hasConcept C41008148 @default.
• W3088296465 hasConcept C44882253 @default.
• W3088296465 hasConcept C48921125 @default.
• W3088296465 hasConcept C58166 @default.
• W3088296465 hasConcept C64946054 @default.
• W3088296465 hasConcept C6980683 @default.
• W3088296465 hasConcept C75622301 @default.
• W3088296465 hasConcept C76177295 @default.
• W3088296465 hasConcept C86803240 @default.
• W3088296465 hasConcept C87717796 @default.
• W3088296465 hasConceptScore W3088296465C105795698 @default.
• W3088296465 hasConceptScore W3088296465C119857082 @default.
• W3088296465 hasConceptScore W3088296465C124101348 @default.
• W3088296465 hasConceptScore W3088296465C127413603 @default.
• W3088296465 hasConceptScore W3088296465C128990827 @default.
• W3088296465 hasConceptScore W3088296465C129360787 @default.
• W3088296465 hasConceptScore W3088296465C139945424 @default.
• W3088296465 hasConceptScore W3088296465C140073362 @default.
• W3088296465 hasConceptScore W3088296465C154945302 @default.
• W3088296465 hasConceptScore W3088296465C161584116 @default.
• W3088296465 hasConceptScore W3088296465C187320778 @default.
• W3088296465 hasConceptScore W3088296465C18903297 @default.
• W3088296465 hasConceptScore W3088296465C2780797713 @default.
• W3088296465 hasConceptScore W3088296465C33923547 @default.
• W3088296465 hasConceptScore W3088296465C39432304 @default.
• W3088296465 hasConceptScore W3088296465C41008148 @default.
• W3088296465 hasConceptScore W3088296465C44882253 @default.
• W3088296465 hasConceptScore W3088296465C48921125 @default.
• W3088296465 hasConceptScore W3088296465C58166 @default.
• W3088296465 hasConceptScore W3088296465C64946054 @default.
• W3088296465 hasConceptScore W3088296465C6980683 @default.
• W3088296465 hasConceptScore W3088296465C75622301 @default.
• W3088296465 hasConceptScore W3088296465C76177295 @default.
• W3088296465 hasConceptScore W3088296465C86803240 @default.
• W3088296465 hasConceptScore W3088296465C87717796 @default.
• W3088296465 hasLocation W30882964651 @default.

• next