FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283781259> ?p ?o ?g. }

• W4283781259 endingPage "118805" @default.
• W4283781259 startingPage "118805" @default.
• W4283781259 abstract "Water quality monitoring programs are essential planning and management tools, but they face many challenges in the developing world. The scarcity of financial and human resources and the unavailability of infrastructure often make it impossible to meet the legal requirements of water monitoring. Many approaches to optimizing water quality monitoring programs have already been proposed. However, few investigations have developed and tested data mining for this purpose. This article has developed data-based models to reduce the number of water quality parameters of monitoring programs using data mining. The objective was to extract patterns from the database, expressed by association rules, which together with field parameters, measured with automatic probes, can estimate laboratory variables. This approach was applied in 35 monitoring stations along 27 river basins throughout Brazil. The data are from fifty years of monitoring (1971-2021), constituting 6328 observations of 60 water quality parameters investigated in different environmental contexts, water quality, and the structuring of monitoring programs. With the applied approach it was possible to estimate 56% of the laboratory parameters in the monitoring stations investigated. The influence of environmental characteristics on the optimization capacity of monitoring programs was evident. The methodology used was not influenced by different water quality levels and anthropogenic impacts. However, the number of parameters was the most influential element in optimization. Monitoring programs with 20 or more water quality variables have the highest potential (≥44%) of optimization by this methodology. Results demonstrate that this approach is a promising alternative that can reduce the frequency of analyses measured in the laboratory and increase the spatial and temporal coverage of water quality monitoring networks." @default.
• W4283781259 created "2022-07-03" @default.
• W4283781259 creator A5019936294 @default.
• W4283781259 creator A5046929330 @default.
• W4283781259 date "2022-08-01" @default.
• W4283781259 modified "2023-10-16" @default.
• W4283781259 title "Optimization of water quality monitoring programs by data mining" @default.
• W4283781259 cites W1799131156 @default.
• W4283781259 cites W1967046557 @default.
• W4283781259 cites W1978339192 @default.
• W4283781259 cites W1983715260 @default.
• W4283781259 cites W1984363611 @default.
• W4283781259 cites W1996567022 @default.
• W4283781259 cites W2015053255 @default.
• W4283781259 cites W2024495965 @default.
• W4283781259 cites W2033014209 @default.
• W4283781259 cites W2037743064 @default.
• W4283781259 cites W2044317047 @default.
• W4283781259 cites W2052576555 @default.
• W4283781259 cites W2055366723 @default.
• W4283781259 cites W2073036074 @default.
• W4283781259 cites W2123407739 @default.
• W4283781259 cites W2136808971 @default.
• W4283781259 cites W2148061495 @default.
• W4283781259 cites W2153894051 @default.
• W4283781259 cites W2167040687 @default.
• W4283781259 cites W2273992620 @default.
• W4283781259 cites W2287647527 @default.
• W4283781259 cites W2331659570 @default.
• W4283781259 cites W2339820545 @default.
• W4283781259 cites W2346945911 @default.
• W4283781259 cites W2473801385 @default.
• W4283781259 cites W2479755133 @default.
• W4283781259 cites W2512919575 @default.
• W4283781259 cites W2595559279 @default.
• W4283781259 cites W2737195924 @default.
• W4283781259 cites W2742423835 @default.
• W4283781259 cites W2769929350 @default.
• W4283781259 cites W2771288795 @default.
• W4283781259 cites W2792277382 @default.
• W4283781259 cites W2799364093 @default.
• W4283781259 cites W2893905736 @default.
• W4283781259 cites W2912494733 @default.
• W4283781259 cites W3023852953 @default.
• W4283781259 cites W3030537919 @default.
• W4283781259 cites W3037198439 @default.
• W4283781259 cites W3052587105 @default.
• W4283781259 cites W3086048481 @default.
• W4283781259 cites W3091212547 @default.
• W4283781259 cites W3093867326 @default.
• W4283781259 cites W3097943792 @default.
• W4283781259 cites W3132318968 @default.
• W4283781259 cites W3173271464 @default.
• W4283781259 cites W3208150240 @default.
• W4283781259 cites W4200295299 @default.
• W4283781259 cites W613488006 @default.
• W4283781259 doi "https://doi.org/10.1016/j.watres.2022.118805" @default.
• W4283781259 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35949073" @default.
• W4283781259 hasPublicationYear "2022" @default.
• W4283781259 type Work @default.
• W4283781259 citedByCount "11" @default.
• W4283781259 countsByYear W42837812592022 @default.
• W4283781259 countsByYear W42837812592023 @default.
• W4283781259 crossrefType "journal-article" @default.
• W4283781259 hasAuthorship W4283781259A5019936294 @default.
• W4283781259 hasAuthorship W4283781259A5046929330 @default.
• W4283781259 hasConcept C109747225 @default.
• W4283781259 hasConcept C111472728 @default.
• W4283781259 hasConcept C112930515 @default.
• W4283781259 hasConcept C124101348 @default.
• W4283781259 hasConcept C127413603 @default.
• W4283781259 hasConcept C138885662 @default.
• W4283781259 hasConcept C144133560 @default.
• W4283781259 hasConcept C153823671 @default.
• W4283781259 hasConcept C162324750 @default.
• W4283781259 hasConcept C175444787 @default.
• W4283781259 hasConcept C176217482 @default.
• W4283781259 hasConcept C18903297 @default.
• W4283781259 hasConcept C200601418 @default.
• W4283781259 hasConcept C21547014 @default.
• W4283781259 hasConcept C24756922 @default.
• W4283781259 hasConcept C2779530757 @default.
• W4283781259 hasConcept C2780505938 @default.
• W4283781259 hasConcept C2780797713 @default.
• W4283781259 hasConcept C39432304 @default.
• W4283781259 hasConcept C41008148 @default.
• W4283781259 hasConcept C539469273 @default.
• W4283781259 hasConcept C86803240 @default.
• W4283781259 hasConcept C87717796 @default.
• W4283781259 hasConceptScore W4283781259C109747225 @default.
• W4283781259 hasConceptScore W4283781259C111472728 @default.
• W4283781259 hasConceptScore W4283781259C112930515 @default.
• W4283781259 hasConceptScore W4283781259C124101348 @default.
• W4283781259 hasConceptScore W4283781259C127413603 @default.
• W4283781259 hasConceptScore W4283781259C138885662 @default.
• W4283781259 hasConceptScore W4283781259C144133560 @default.
• W4283781259 hasConceptScore W4283781259C153823671 @default.
• W4283781259 hasConceptScore W4283781259C162324750 @default.

• next