A systematic extreme learning machine approach to analyze visitors' thermal comfort at a public urban space
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- @Article{Kariminia:2016:RSER,
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author = "Shahab Kariminia and Shahaboddin Shamshirband and
Shervin Motamedi and Roslan Hashim and
Chandrabhushan Roy",
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title = "A systematic extreme learning machine approach to
analyze visitors' thermal comfort at a public urban
space",
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journal = "Renewable and Sustainable Energy Reviews",
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volume = "58",
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pages = "751--760",
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year = "2016",
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ISSN = "1364-0321",
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DOI = "doi:10.1016/j.rser.2015.12.321",
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URL = "http://www.sciencedirect.com/science/article/pii/S1364032115017049",
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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 micro-climatic 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.",
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keywords = "genetic algorithms, genetic programming, Outdoor
thermal comfort, Open urban area, Extreme learning
machine, Regression, Moderate climate, Dry climate",
- }
Genetic Programming entries for
Shahab Kariminia
Shahaboddin Shamshirband
Shervin Motamedi
Roslan Hashim
Chandrabhushan Roy
Citations