Scipediacontent: Scipediacontent moved page Draft Content 379664561 to 238,295lm

2021-03-22T23:37:13Z

Scipediacontent moved page Draft Content 379664561 to 238,295lm

Scipediacontent: Created page with " == Abstract == This paper presents a method of optimizing the elements of a hierarchy of fuzzy-rule-based systems (FRBSs). It is a hybridization of a genetic algorithm (GA)..."

2021-03-22T23:35:54Z

Created page with " == Abstract == This paper presents a method of optimizing the elements of a hierarchy of fuzzy-rule-based systems (FRBSs). It is a hybridization of a genetic algorithm (GA)..."

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== Abstract ==

This paper presents a method of optimizing the elements of a hierarchy of fuzzy-rule-based systems (FRBSs). It is a hybridization of a genetic algorithm (GA) and the cross-entropy (CE) method, which is here called GACE. It is used to predict congestion in a 9-km-long stretch of the I5 freeway in California, with time horizons of 5, 15, and 30 min. A comparative study of different levels of hybridization in GACE is made. These range from a pure GA to a pure CE, passing through different weights for each of the combined techniques. The results prove that GACE is more accurate than GA or CE alone for predicting short-term traffic congestion.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_379664561-beopen1324-2867-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1109/tits.2015.2491365 http://dx.doi.org/10.1109/tits.2015.2491365] under the license https://creativecommons.org/licenses/by-nc-nd

* [https://zenodo.org/record/164838 https://zenodo.org/record/164838]

* [https://zenodo.org/record/164838/files/Lopez_GACE.pdf https://zenodo.org/record/164838/files/Lopez_GACE.pdf] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

* [http://xplorestaging.ieee.org/ielx7/6979/7394960/07331637.pdf?arnumber=7331637 http://xplorestaging.ieee.org/ielx7/6979/7394960/07331637.pdf?arnumber=7331637],
: [http://dx.doi.org/10.1109/tits.2015.2491365 http://dx.doi.org/10.1109/tits.2015.2491365] under the license cc-by-nc-nd

* [https://dblp.uni-trier.de/db/journals/tits/tits17.html#Lopez-GarciaOOM16 https://dblp.uni-trier.de/db/journals/tits/tits17.html#Lopez-GarciaOOM16],
: [https://ieeexplore.ieee.org/document/7331637 https://ieeexplore.ieee.org/document/7331637],
: [http://ieeexplore.ieee.org/document/7331637 http://ieeexplore.ieee.org/document/7331637],
: [https://doi.org/10.1109/TITS.2015.2491365 https://doi.org/10.1109/TITS.2015.2491365],
: [https://trid.trb.org/view.aspx?id=1397289 https://trid.trb.org/view.aspx?id=1397289],
: [https://academic.microsoft.com/#/detail/2274750026 https://academic.microsoft.com/#/detail/2274750026]

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Scipediacontent: Scipediacontent moved page Draft Content 379664561 to 238,295lm

Scipediacontent: Created page with " == Abstract == This paper presents a method of optimizing the elements of a hierarchy of fuzzy-rule-based systems (FRBSs). It is a hybridization of a genetic algorithm (GA)..."