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A Proposal to Facilitate Mandatory Bridge Load Tests with Artificial Neural Network Analyses Using a Digital Data Aggregation Platform

Piotr OWERKO

Piotr OWERKO

Assistant Prof.; PhD, Faculty of Materials, Civil and Environmental Engineering, University of Bielsko-BialaBielsko-Biala, Poland
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OWERKO, Piotr
, 
Jerzy KAŁUŻA

Jerzy KAŁUŻA

MSc; Aspekt Laboratorium Sp. z o.o.Jaworzno, Poland
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KAŁUŻA, Jerzy
 und 
Marek WAZOWSKI

Marek WAZOWSKI

PhD; Aspekt Laboratorium Sp. z o.o.Jaworzno, Poland
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WAZOWSKI, Marek
  
08. Okt. 2021
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Online veröffentlicht: 08. Okt. 2021
Seitenbereich: 69 - 78
Eingereicht: 21. Mai 2021
Akzeptiert: 03. Juli 2021
DOI: https://doi.org/10.21307/acee-2021-023
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© 2021 Piotr Owerko et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Simplfied sketch of proposed digital platform for bridge load tests information management
Simplfied sketch of proposed digital platform for bridge load tests information management

Figure 2.

Simplfied sketch of proposed modifications in the bridge approval criterion [32]
Simplfied sketch of proposed modifications in the bridge approval criterion [32]

Figure 3.

Exemplary typical bridge under test loading
Exemplary typical bridge under test loading

Figure 4.

Regression perceptron of 4-7-1 architecture
Regression perceptron of 4-7-1 architecture

Figure 5.

Cost function values in each training epoch; in regard to: a) the example “A”; b) the example “B”
Cost function values in each training epoch; in regard to: a) the example “A”; b) the example “B”

Figure 6.

Comparison of the predictive effectiveness of perceptrons in regard to: a) the example “A”; b) the example “B”
Comparison of the predictive effectiveness of perceptrons in regard to: a) the example “A”; b) the example “B”
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