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Adaptive Neuro-Fuzzy Inference System For Forecasting Traffic Volume(Case Study Of National Road Km 41 Kamal)

Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan

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Title Adaptive Neuro-Fuzzy Inference System For Forecasting Traffic Volume(Case Study Of National Road Km 41 Kamal)
 
Creator Angkoso, Agustinus
Cahyono, Muhammad Shofwan Donny
 
Subject —
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Description The effect of the development of an infrastructure such as shopping centers, settlements, and so on is one study that is generally considered in the governance of a region. Typically, this construction has a major traffic impact. Combined with the effects of population growth, which is constantly growing every year, the flow of traffic is increasingly congested. This is because many of these people choose to own personal vehicles. Tremendous congestion would result from a road capacity that is not proportional to vehicle growth. A traffic analysis was conducted using road traffic volume data to prevent this. This research will attempt to survey a road on National road KM 41 Kamal and use the neuro fuzzy method to forecast traffic volume. The amount of traffic that will be studied is only motorcycles. The results show that with an error percentage of 16.0793%, neuro fuzzy can predict motorcycle traffic volume. It can be inferred from this that Neuro Fuzzy can forecast traffic volume on a road quite well.
 
Publisher Litbang Pemas - Universitas Islam Lamongan
 
Contributor —
 
Date 2021-10-16
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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Format application/pdf
 
Identifier https://jurnalteknik.unisla.ac.id/index.php/CVL/article/view/540
10.30736/cvl.v6i2.540
 
Source Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan; Vol 6, No 2 (2021): September; 155-166
Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan; Vol 6, No 2 (2021): September; 155-166
2620-7222
2503-2399
 
Language eng
 
Relation https://jurnalteknik.unisla.ac.id/index.php/CVL/article/view/540/pdf
 
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https://creativecommons.org/licenses/by-sa/4.0