Calculation of Effective Structural Number Using Simple Neural Network for Some Road Links in Indonesia

Jurnal Tiarsie

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Title Calculation of Effective Structural Number Using Simple Neural Network for Some Road Links in Indonesia
Calculation of Effective Structural Number Using Simple Neural Network for Some Road Links in Indonesia
 
Creator Syafier, Siegfried
 
Description In the pavement maintenance system, the parameter of effective structural number (SNeff) would be a considered factor in deciding whether a road link would be repaired or not. To calculate this parameter, it is required the testing of Falling Weight Deflectometer (FWD) and information of layer composition and thicknesses. The combination of these information and using the method of AASHTO’93, it can be calculated the SNeff. These two information generally would be gained through the testings of core drill and test pit which would take time and cost. To overcome these problems, the neural network method or precisely the artificial neural network is developed for analysis of pavement structure. From the analysis, it can be said that the neural network of single perceptron can be used for predicting the SNeff with an acceptable error. In general the value of SNeff obtained from neural network calculation is lower than that of AASHTO’93. In this paper it is also recommended to develop the neural network using multi layer perceptron for the use on pavement system analysis that might be decreasing the error.
In the pavement maintenance system, the parameter of effective structural number (SNeff) would be a considered factor in deciding whether a road link would be repaired or not. To calculate this parameter, it is required the testing of Falling Weight Deflectometer (FWD) and information of layer composition and thicknesses. The combination of these information and using the method of AASHTO’93, it can be calculated the SNeff. These two information generally would be gained through the testings of core drill and test pit which would take time and cost. To overcome these problems, the neural network method or precisely the artificial neural network is developed for analysis of pavement structure. From the analysis, it can be said that the neural network of single perceptron can be used for predicting the SNeff with an acceptable error. In general the value of SNeff obtained from neural network calculation is lower than that of AASHTO’93. In this paper it is also recommended to develop the neural network using multi layer perceptron for the use on pavement system analysis that might be decreasing the error.
 
Publisher Fakultas Teknik Universitas Langlangbuana
 
Date 2018-02-06
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://jurnalunla.web.id/tiarsie/index.php/tiarsie/article/view/Calculation%20of%20Effective%20Structural%20Number%20Using%20Simple%20Neural%20Network%20for%20Some%20Road%20Links%20in%20Indonesia
10.32816/tiarsie.v14i1.15
 
Source Jurnal TIARSIE; Vol 14 No 2 (2017): Jurnal TIARSIE 14.2; 45-50
Jurnal TIARSIE; Vol 14 No 2 (2017): Jurnal TIARSIE 14.2; 45-50
2623-2391
1411-2248
10.32816/tiarsie.v14i2
 
Language eng
 
Relation http://jurnalunla.web.id/tiarsie/index.php/tiarsie/article/view/Calculation%20of%20Effective%20Structural%20Number%20Using%20Simple%20Neural%20Network%20for%20Some%20Road%20Links%20in%20Indonesia/4
 
Rights Copyright (c) 2017 JURNAL TIARSIE
http://creativecommons.org/licenses/by-nc-sa/4.0
 

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