Scipediacontent: Scipediacontent moved page Draft Content 556503687 to Ban et al 2017a

2021-02-12T12:26:35Z

Scipediacontent moved page Draft Content 556503687 to Ban et al 2017a

Scipediacontent: Created page with " == Abstract == There is always an asymmetric phenomenon between traffic data quantity and unit information content. Labeled data is more effective but scarce, while unlabele..."

2021-02-12T12:26:32Z

Created page with " == Abstract == There is always an asymmetric phenomenon between traffic data quantity and unit information content. Labeled data is more effective but scarce, while unlabele..."

New page

== Abstract ==

There is always an asymmetric phenomenon between traffic data quantity and unit information content. Labeled data is more effective but scarce, while unlabeled data is large but weaker in sample information. In an urban transportation assessment system, semi-supervised extreme learning machine (SSELM) can unite manual observed data and extensively collected data cooperatively to build connection between congestion condition and road information. In our method, semi-supervised learning can integrate both small-scale labeled data and large-scale unlabeled data, so that they can play their respective advantages, while the ELM can process large scale data at high speed. Optimized by kernel function, Kernel-SSELM can achieve higher classification accuracy and robustness than original SSELM. Both the experiment and the real-time application show that the evaluation system can precisely reflect the traffic condition.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_556503687-beopen160-3222-document.pdf</pdf>

== Original document ==

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

* [https://www.mdpi.com/2073-8994/9/5/70/pdf https://www.mdpi.com/2073-8994/9/5/70/pdf] under the license https://creativecommons.org/licenses/by

* [http://www.mdpi.com/2073-8994/9/5/70/pdf http://www.mdpi.com/2073-8994/9/5/70/pdf],
: [http://dx.doi.org/10.3390/sym9050070 http://dx.doi.org/10.3390/sym9050070] under the license cc-by

* [https://www.mdpi.com/2073-8994/9/5/70/htm https://www.mdpi.com/2073-8994/9/5/70/htm],
: [https://www.mdpi.com/2073-8994/9/5/70/pdf https://www.mdpi.com/2073-8994/9/5/70/pdf],
: [https://dblp.uni-trier.de/db/journals/symmetry/symmetry9.html#ShenBG17 https://dblp.uni-trier.de/db/journals/symmetry/symmetry9.html#ShenBG17],
: [https://doi.org/10.3390/sym9050070 https://doi.org/10.3390/sym9050070],
: [https://academic.microsoft.com/#/detail/2612902285 https://academic.microsoft.com/#/detail/2612902285] under the license https://creativecommons.org/licenses/by/4.0/

← Older revision	Revision as of 12:26, 12 February 2021
(No difference)

Ban et al 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 556503687 to Ban et al 2017a

Scipediacontent: Created page with " == Abstract == There is always an asymmetric phenomenon between traffic data quantity and unit information content. Labeled data is more effective but scarce, while unlabele..."