Development of fuzzy models for asphalt pavement performance
The objective of this paper was to develop fuzzy models for asphalt pavement performance. The fuzzy logic can convert linguistic or qualitative variables into quantitative values. This feature makes it possible to gather experts’ experience about the knowledge they have on factors that affect the pa...
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Universidade Estadual de Maringá
2019-05-01
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Series: | Acta Scientiarum: Technology |
Online Access: | http://periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/35626 |
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doaj-1148347a93c94c04a90ed237fda074832020-11-24T21:55:22ZengUniversidade Estadual de MaringáActa Scientiarum: Technology1807-86642019-05-01411e35626e3562610.4025/actascitechnol.v41i1.3562619002Development of fuzzy models for asphalt pavement performanceSérgio Pacífico SoncimIgor Castro Sá de OliveiraFelipe Brandão SantosThe objective of this paper was to develop fuzzy models for asphalt pavement performance. The fuzzy logic can convert linguistic or qualitative variables into quantitative values. This feature makes it possible to gather experts’ experience about the knowledge they have on factors that affect the pavement performance and its state condition. Forms developed in an organized way were applied for acquiring the knowledge from experts on pavement construction and maintenance. The variables pavement age, traffic, International Roughness Index (IRI) and Flexible Pavement Condition Index (FPCI) were associated with numerical scales and linguistic concepts such as new, old, light, heavy, good, fair, and poor. From the information obtained through the application of forms, variables were modeled with the aid of software InFuzzy and fuzzy models were developed for IRI and FPCI. For validating the model, a straight line adjustment was used to relate the predicted to the observed data. Also, the corresponding correlation coefficient (r) was calculated and residuals were analyzed. The developed models fitted to observed data and correlation coefficient r = 0.71 and 0.70, respectively.http://periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/35626 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sérgio Pacífico Soncim Igor Castro Sá de Oliveira Felipe Brandão Santos |
spellingShingle |
Sérgio Pacífico Soncim Igor Castro Sá de Oliveira Felipe Brandão Santos Development of fuzzy models for asphalt pavement performance Acta Scientiarum: Technology |
author_facet |
Sérgio Pacífico Soncim Igor Castro Sá de Oliveira Felipe Brandão Santos |
author_sort |
Sérgio Pacífico Soncim |
title |
Development of fuzzy models for asphalt pavement performance |
title_short |
Development of fuzzy models for asphalt pavement performance |
title_full |
Development of fuzzy models for asphalt pavement performance |
title_fullStr |
Development of fuzzy models for asphalt pavement performance |
title_full_unstemmed |
Development of fuzzy models for asphalt pavement performance |
title_sort |
development of fuzzy models for asphalt pavement performance |
publisher |
Universidade Estadual de Maringá |
series |
Acta Scientiarum: Technology |
issn |
1807-8664 |
publishDate |
2019-05-01 |
description |
The objective of this paper was to develop fuzzy models for asphalt pavement performance. The fuzzy logic can convert linguistic or qualitative variables into quantitative values. This feature makes it possible to gather experts’ experience about the knowledge they have on factors that affect the pavement performance and its state condition. Forms developed in an organized way were applied for acquiring the knowledge from experts on pavement construction and maintenance. The variables pavement age, traffic, International Roughness Index (IRI) and Flexible Pavement Condition Index (FPCI) were associated with numerical scales and linguistic concepts such as new, old, light, heavy, good, fair, and poor. From the information obtained through the application of forms, variables were modeled with the aid of software InFuzzy and fuzzy models were developed for IRI and FPCI. For validating the model, a straight line adjustment was used to relate the predicted to the observed data. Also, the corresponding correlation coefficient (r) was calculated and residuals were analyzed. The developed models fitted to observed data and correlation coefficient r = 0.71 and 0.70, respectively. |
url |
http://periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/35626 |
work_keys_str_mv |
AT sergiopacificosoncim developmentoffuzzymodelsforasphaltpavementperformance AT igorcastrosadeoliveira developmentoffuzzymodelsforasphaltpavementperformance AT felipebrandaosantos developmentoffuzzymodelsforasphaltpavementperformance |
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