Matches in SemOpenAlex for { <https://semopenalex.org/work/W2953669836> ?p ?o ?g. }
- W2953669836 endingPage "e0218855" @default.
- W2953669836 startingPage "e0218855" @default.
- W2953669836 abstract "Sustainable development goals are used as a guidance for strategies development on local, regional and national levels. The importance of including young people in this complex process is recognized in all relevant documents (i.e. Agenda 21), however it is not an easy task to elicit opinions and preferences from the youth. Furthermore, the assessment of the sustainable development goals itself presents a challenge for the noisy data and nonlinear relationships in data. Popular approach is fuzzy set models where expert knowledge is presented with comprehensible rules; however expert knowledge elicitation takes a long time too. Several studies proposed an adaptive neuro-fuzzy inference system approach that combines the fuzzy set theory to model expert knowledge with neural networks for inferring rules and membership functions from data to assess the sustainable development performance. We base our assumptions that ANFIS can be used to predict the importance of sustainable development pillars from the demographic data of young people. For this purpose, we have conducted an online survey on sustainable development goals opinions and importance of young people in Serbia. The sample of 386 respondents has been split into a training sample of 300 instances (to generate membership functions and fuzzy rules) and a testing sample of 86 instances to predict the importance of the three pillars. We have conducted a trace-driven simulation test to validate the results of the proposed ANFIS model. Results of the study provided insights into how the young people in Serbia assess the importance of sustainable development goals. Secondly, the results suggest that ANFIS can be applied to predict values of importance of the three sustainable development pillars with the relative error of Rel Err < 5%. It must be noted that the considered model could be further improved by using training samples with more data." @default.
- W2953669836 created "2019-07-12" @default.
- W2953669836 creator A5000335976 @default.
- W2953669836 creator A5011401748 @default.
- W2953669836 creator A5011653490 @default.
- W2953669836 creator A5038079956 @default.
- W2953669836 creator A5038333519 @default.
- W2953669836 creator A5053291844 @default.
- W2953669836 creator A5071019443 @default.
- W2953669836 date "2019-06-25" @default.
- W2953669836 modified "2023-10-01" @default.
- W2953669836 title "Youth and forecasting of sustainable development pillars: An adaptive neuro-fuzzy inference system approach" @default.
- W2953669836 cites W1969062436 @default.
- W2953669836 cites W1970778577 @default.
- W2953669836 cites W2012988178 @default.
- W2953669836 cites W2019207321 @default.
- W2953669836 cites W2029828041 @default.
- W2953669836 cites W2042837939 @default.
- W2953669836 cites W2048012762 @default.
- W2953669836 cites W2048262921 @default.
- W2953669836 cites W2066898401 @default.
- W2953669836 cites W2073524950 @default.
- W2953669836 cites W2135863705 @default.
- W2953669836 cites W2150807667 @default.
- W2953669836 cites W2160985323 @default.
- W2953669836 cites W2169619085 @default.
- W2953669836 cites W2172621144 @default.
- W2953669836 cites W2341531390 @default.
- W2953669836 cites W2608204247 @default.
- W2953669836 cites W2614093519 @default.
- W2953669836 cites W2624764517 @default.
- W2953669836 cites W2747168925 @default.
- W2953669836 cites W2784064024 @default.
- W2953669836 cites W2806028442 @default.
- W2953669836 cites W2886027304 @default.
- W2953669836 cites W3124148362 @default.
- W2953669836 doi "https://doi.org/10.1371/journal.pone.0218855" @default.
- W2953669836 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6592548" @default.
- W2953669836 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31237924" @default.
- W2953669836 hasPublicationYear "2019" @default.
- W2953669836 type Work @default.
- W2953669836 sameAs 2953669836 @default.
- W2953669836 citedByCount "3" @default.
- W2953669836 countsByYear W29536698362020 @default.
- W2953669836 countsByYear W29536698362022 @default.
- W2953669836 countsByYear W29536698362023 @default.
- W2953669836 crossrefType "journal-article" @default.
- W2953669836 hasAuthorship W2953669836A5000335976 @default.
- W2953669836 hasAuthorship W2953669836A5011401748 @default.
- W2953669836 hasAuthorship W2953669836A5011653490 @default.
- W2953669836 hasAuthorship W2953669836A5038079956 @default.
- W2953669836 hasAuthorship W2953669836A5038333519 @default.
- W2953669836 hasAuthorship W2953669836A5053291844 @default.
- W2953669836 hasAuthorship W2953669836A5071019443 @default.
- W2953669836 hasBestOaLocation W29536698361 @default.
- W2953669836 hasConcept C111919701 @default.
- W2953669836 hasConcept C119857082 @default.
- W2953669836 hasConcept C124101348 @default.
- W2953669836 hasConcept C127413603 @default.
- W2953669836 hasConcept C154945302 @default.
- W2953669836 hasConcept C177264268 @default.
- W2953669836 hasConcept C17744445 @default.
- W2953669836 hasConcept C185592680 @default.
- W2953669836 hasConcept C186108316 @default.
- W2953669836 hasConcept C195975749 @default.
- W2953669836 hasConcept C198531522 @default.
- W2953669836 hasConcept C199360897 @default.
- W2953669836 hasConcept C199539241 @default.
- W2953669836 hasConcept C201995342 @default.
- W2953669836 hasConcept C2522767166 @default.
- W2953669836 hasConcept C2776214188 @default.
- W2953669836 hasConcept C2780451532 @default.
- W2953669836 hasConcept C41008148 @default.
- W2953669836 hasConcept C42011625 @default.
- W2953669836 hasConcept C43617362 @default.
- W2953669836 hasConcept C4554734 @default.
- W2953669836 hasConcept C50644808 @default.
- W2953669836 hasConcept C552854447 @default.
- W2953669836 hasConcept C58166 @default.
- W2953669836 hasConcept C58328972 @default.
- W2953669836 hasConcept C98045186 @default.
- W2953669836 hasConceptScore W2953669836C111919701 @default.
- W2953669836 hasConceptScore W2953669836C119857082 @default.
- W2953669836 hasConceptScore W2953669836C124101348 @default.
- W2953669836 hasConceptScore W2953669836C127413603 @default.
- W2953669836 hasConceptScore W2953669836C154945302 @default.
- W2953669836 hasConceptScore W2953669836C177264268 @default.
- W2953669836 hasConceptScore W2953669836C17744445 @default.
- W2953669836 hasConceptScore W2953669836C185592680 @default.
- W2953669836 hasConceptScore W2953669836C186108316 @default.
- W2953669836 hasConceptScore W2953669836C195975749 @default.
- W2953669836 hasConceptScore W2953669836C198531522 @default.
- W2953669836 hasConceptScore W2953669836C199360897 @default.
- W2953669836 hasConceptScore W2953669836C199539241 @default.
- W2953669836 hasConceptScore W2953669836C201995342 @default.
- W2953669836 hasConceptScore W2953669836C2522767166 @default.
- W2953669836 hasConceptScore W2953669836C2776214188 @default.
- W2953669836 hasConceptScore W2953669836C2780451532 @default.