Investigation of Iterative and Direct Strategies with Recurrent Neural Networks for Short-Term Traffic Flow Forecasting

Fandango, Armando; Kapoor, Amita

doi:10.1007/978-981-13-1813-9_43

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…For example, in case of earthquake or natural disaster, damage determination can be made via the images received from the site [18]. Into the metropolises, estimation of traffic densities and determination of the car speed in related to this, decreases the accident risk in the roads [19]. In a similar way, car assistant systems provide the focusing to the road by the identification of the traffic warning signs at the roadside [20].…”

Section: Introductionmentioning

confidence: 99%

İnşaat Mühendisliğinde Derin Öğrenme Algoritmalarının Değerlendirilmesi ve Uygulanması

Çakiroğlu¹,

Süzen²

2020

El-Cezeri Fen Ve Mühendislik Dergisi

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In this study, the applicability of deep learning algorithms in the field of civil engineering has been investigated. Firstly, the information that is about deep learning algorithms has been given. Additionally, deep learning applications, which are made, in subjects such as classification, estimation, and interpretation in the field of civil engineering, have been examined. The applications are elaborated according to civil engineering's sub-branches that transportation, geotechnical and construction. The contributions of the realized applications' in view of success rates to civil engineering that were analyzed. As a result of the study, it is foreseen that in the studies where the number of data is high, high performance will be achieved in the use of deep algorithms.

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Section: Introductionmentioning

confidence: 99%