Adaptive Network Based Fuzzy Inference System with Meta-Heuristic Optimizations for International Roughness Index Prediction

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ID: 121233
2019
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Abstract
The International Roughness Index (IRI) is the one of the most important roughness indexes to quantify road surface roughness. In this paper, we propose a new hybrid approach between adaptive network based fuzzy inference system (ANFIS) and various meta-heuristic optimizations such as the genetic algorithm (GA), particle swarm optimization (PSO), and the firefly algorithm (FA) to develop several hybrid models namely GA based ANGIS (GANFIS), PSO based ANFIS (PSOANFIS), FA based ANFIS (FAANFIS), respectively, for the prediction of the IRI. A benchmark model named artificial neural networks (ANN) was also used to compare with those hybrid models. To do this, a total of 2811 samples in the case study of the north of Vietnam (Northwest region, Northeast region, and the Red River Delta Area) within the scope of management of the DRM-I Department were used to validate the models in terms of various criteria like coefficient of determination (R) and the root mean square error (RMSE). Experimental results affirmed the potentiality and effectiveness of the proposed prediction models whereas the PSOANFIS (RMSE = 0.145 and R = 0.888) is better than the other models named GANFIS (RMSE = 0.155 and R = 0.872), FAANFIS (RMSE = 0.170 and R = 0.849), and ANN (RMSE = 0.186 and R = 0.804). The results of this study are helpful for accurate prediction of the IRI for evaluation of quality of road surface roughness.
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bui2019appliedadaptive Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hoang-Long Nguyen,Binh Thai Pham,Le Hoang Son,Nguyen Trung Thang,Hai-Bang Ly,Tien-Thinh Le,Lanh Si Ho,Thanh-Hai Le,Dieu Tien Bui;Hoang-Long Nguyen;Binh Thai Pham;Le Hoang Son;Nguyen Trung Thang;Hai-Bang Ly;Tien-Thinh Le;Lanh Si Ho;Thanh-Hai Le;Dieu Tien Bui;
Journal applied sciences
Year 2019
DOI
10.3390/app9214715
URL
https://sciprofiles.com/publication/view/98cf325e448b063a90cd2810c8cae957
Keywords
Machine learning ann particle swarm optimization anfis international roughness index

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