FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2234902021> ?p ?o ?g. }

• W2234902021 endingPage "760" @default.
• W2234902021 startingPage "751" @default.
• W2234902021 abstract "Abstract Thermal quality of open public spaces in every city influences its residents’ outdoor life. Higher level of thermal comfort attracts more visitors to such places; hence, brings benefits to the community. Previous research works have used the body energy balance or adaptation model for predicting the thermal comfort in outdoor spaces. However, limited research works have applied computational methods in this field. For the first of its’ type, this study applied a systematic approach using a class of soft-computing methodology known as the extreme learning machine (ELM) to forecast the thermal comfort of the subject visitors at an open area in Iran. For data collection, this study used common thermal indices for assessing the thermal perceptions of the subjects. The fieldworks comprised of measuring the microclimatic conditions and interviewing the visitors. This study compared the results of ELM with other conventional soft-computing methods (i.e., artificial neural network (ANN) and genetic programming (GP)). The findings indicate that the ELM results match with the field data. This implies that a model constructed by ELM can accurately predict visitors’ thermal sensations. We conclude that the proposed model’s predictability performance is reliable and superior compared to other approaches (i.e., GP and ANN). Besides, the ELM methodology significantly reduces training time for a Neural Network as compared to the conventional methods." @default.
• W2234902021 created "2016-06-24" @default.
• W2234902021 creator A5061289164 @default.
• W2234902021 creator A5061782653 @default.
• W2234902021 creator A5065328445 @default.
• W2234902021 creator A5071435927 @default.
• W2234902021 creator A5086550972 @default.
• W2234902021 date "2016-05-01" @default.
• W2234902021 modified "2023-09-26" @default.
• W2234902021 title "A systematic extreme learning machine approach to analyze visitors׳ thermal comfort at a public urban space" @default.
• W2234902021 cites W1660761602 @default.
• W2234902021 cites W1965753391 @default.
• W2234902021 cites W1966931108 @default.
• W2234902021 cites W1967725657 @default.
• W2234902021 cites W1968924397 @default.
• W2234902021 cites W1975324114 @default.
• W2234902021 cites W1988115241 @default.
• W2234902021 cites W1991806028 @default.
• W2234902021 cites W1996374044 @default.
• W2234902021 cites W1999582615 @default.
• W2234902021 cites W2003523195 @default.
• W2234902021 cites W2011568797 @default.
• W2234902021 cites W2011780923 @default.
• W2234902021 cites W2012509317 @default.
• W2234902021 cites W2013497870 @default.
• W2234902021 cites W2017417471 @default.
• W2234902021 cites W2022275615 @default.
• W2234902021 cites W2026976681 @default.
• W2234902021 cites W2031234589 @default.
• W2234902021 cites W2043283914 @default.
• W2234902021 cites W2044486831 @default.
• W2234902021 cites W2050893611 @default.
• W2234902021 cites W2052965397 @default.
• W2234902021 cites W2053009031 @default.
• W2234902021 cites W2063371001 @default.
• W2234902021 cites W2070387180 @default.
• W2234902021 cites W2076092573 @default.
• W2234902021 cites W2076678586 @default.
• W2234902021 cites W2076882291 @default.
• W2234902021 cites W2086485442 @default.
• W2234902021 cites W2089357710 @default.
• W2234902021 cites W2104714048 @default.
• W2234902021 cites W2110158084 @default.
• W2234902021 cites W2110633383 @default.
• W2234902021 cites W2111072639 @default.
• W2234902021 cites W2152365410 @default.
• W2234902021 cites W2158054309 @default.
• W2234902021 cites W2167982865 @default.
• W2234902021 cites W2169976759 @default.
• W2234902021 cites W2170359055 @default.
• W2234902021 cites W2172172920 @default.
• W2234902021 cites W2316025663 @default.
• W2234902021 cites W2532056307 @default.
• W2234902021 cites W3125537303 @default.
• W2234902021 cites W322083849 @default.
• W2234902021 cites W4294117813 @default.
• W2234902021 doi "https://doi.org/10.1016/j.rser.2015.12.321" @default.
• W2234902021 hasPublicationYear "2016" @default.
• W2234902021 type Work @default.
• W2234902021 sameAs 2234902021 @default.
• W2234902021 citedByCount "23" @default.
• W2234902021 countsByYear W22349020212016 @default.
• W2234902021 countsByYear W22349020212017 @default.
• W2234902021 countsByYear W22349020212018 @default.
• W2234902021 countsByYear W22349020212019 @default.
• W2234902021 countsByYear W22349020212020 @default.
• W2234902021 countsByYear W22349020212021 @default.
• W2234902021 countsByYear W22349020212022 @default.
• W2234902021 countsByYear W22349020212023 @default.
• W2234902021 crossrefType "journal-article" @default.
• W2234902021 hasAuthorship W2234902021A5061289164 @default.
• W2234902021 hasAuthorship W2234902021A5061782653 @default.
• W2234902021 hasAuthorship W2234902021A5065328445 @default.
• W2234902021 hasAuthorship W2234902021A5071435927 @default.
• W2234902021 hasAuthorship W2234902021A5086550972 @default.
• W2234902021 hasConcept C111919701 @default.
• W2234902021 hasConcept C119857082 @default.
• W2234902021 hasConcept C127413603 @default.
• W2234902021 hasConcept C133913538 @default.
• W2234902021 hasConcept C153294291 @default.
• W2234902021 hasConcept C154945302 @default.
• W2234902021 hasConcept C170154142 @default.
• W2234902021 hasConcept C205649164 @default.
• W2234902021 hasConcept C2778572836 @default.
• W2234902021 hasConcept C2780150128 @default.
• W2234902021 hasConcept C2984866010 @default.
• W2234902021 hasConcept C41008148 @default.
• W2234902021 hasConcept C50644808 @default.
• W2234902021 hasConceptScore W2234902021C111919701 @default.
• W2234902021 hasConceptScore W2234902021C119857082 @default.
• W2234902021 hasConceptScore W2234902021C127413603 @default.
• W2234902021 hasConceptScore W2234902021C133913538 @default.
• W2234902021 hasConceptScore W2234902021C153294291 @default.
• W2234902021 hasConceptScore W2234902021C154945302 @default.
• W2234902021 hasConceptScore W2234902021C170154142 @default.
• W2234902021 hasConceptScore W2234902021C205649164 @default.
• W2234902021 hasConceptScore W2234902021C2778572836 @default.
• W2234902021 hasConceptScore W2234902021C2780150128 @default.

• next