LSTM and TCN application for airport surface distress detection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F26%3A00564687" target="_blank" >RIV/60162694:G43__/26:00564687 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.rineng.2025.105708" target="_blank" >https://doi.org/10.1016/j.rineng.2025.105708</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.rineng.2025.105708" target="_blank" >10.1016/j.rineng.2025.105708</a>

Result language

angličtina

Original language name

LSTM and TCN application for airport surface distress detection

Original language description

This paper evaluates the feasibility of using smartphone accelerometers to identify and categorize airport pavement distresses. Using experimental measurements taken on a test road section, we tested the smartphone accelerometers to recognize and categorize selected distress patterns. In our work, we investigated the capacity of neural networks with a Long Short-Term Memory (LSTM) layer with normalized data weighted and not weighted, bidirectional LSTM, and Temporal Convolutional Networks (TCNs). The networks tested for sequence data classification displayed considerably high accuracy. However, many associations of sequence versus distress were needed to adequately complete the training process. In contrast, the TCNs we used for sequence-to-sequence classification showed lower accuracy. However, a much smaller dataset was sufficient to complete the training. As a consequence, we chose the TCN to implement the practical application. Both algorithms demonstrated high accuracy on training and validation data and performed well on other independent test samples.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

21100 - Other engineering and technologies

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

RESULTS IN ENGINEERING

ISSN

2590-1230

e-ISSN

2590-1230

Volume of the periodical

27

Issue of the periodical within the volume

27

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

11

Pages from-to

105708

UT code for WoS article

001513593900010

EID of the result in the Scopus database

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