Szczegóły

Tytuł artykułu

Modelling Tyre-Road Noise with Data Mining Techniques

Tytuł czasopisma

Archives of Acoustics

Rocznik

2015

Wolumin

vol. 40

Numer

No 4

Autorzy publikacji

Wydział PAN

Nauki Techniczne

Wydawca

Committee on Acoustics PAS, PAS Institute of Fundamental Technological Research, Polish Acoustical Society

Data

2015[2015.01.01 AD - 2015.12.31 AD]

Identyfikator

ISSN 0137-5075 ; eISSN 2300-262X

Referencje

Kumar (2011), Road Traffic Noise Prediction with Neural Networks A Review An International Of Optimization And Control : Theories & Applications, Journal, 2, 1. ; Kaczmarek (2010), Annoyance of timevarying road - traffic noise of Acoustics, Archives, 35, 383. ; Mak (2014), Statistical tyre / road noise modeling in Hong Kong on friction course, Applied Acoustics, 76. ; Bueno (2011), Pavement temperature influence on close proximity tire / road noise, Applied Acoustics, 72. ; EWINS (2000), Modal Testing : Theory Practice and Application Studies Press Ltd, Research. ; Smola (2004), A tutorial on support vector regression and Computing, Statistics, 14, 199. ; Chou (2011), Optimizing the prediction accuracy of concrete compressive strength based on a comparison of datamining techniques of Computing in Civil Engineering, Journal, 25, 242. ; Raimundo (2010), Sound absorption coefficient of wet gap graded asphalt mixtures th International Congress and Exposition on Noise Control Engineering, INTERNOISE, 39. ; Cortez (2013), Using sensitivity analysis and visualization techniques to open black box data mining models, Information Sciences, 225. ; Sayers (1995), On the calculation of International Roughness Index from Longitudinal Road Profile Research Board, Transportation Research Record Transportation, 1. ; Miranda (2011), New Models for Strength and Deformability Parameter Calculation in Rock Masses Using Data - Mining Techniques of Geomechanics, International Journal, 11, 44. ; Zhou (2010), Integration of GIS and Data Mining Technology to Enhance the Pavement Management Decision Making of Transportation Engineering, Journal, 136. ; Freitas (2012), Traffic noise abatement : How different pavements vehicle speeds and traffic densities affect annoyance levels Research Part D : Transport and Environment, Transportation, 17, 321. ; Cherkassky (2004), Practical Selection of SVM Parameters and Noise Estimation for SVM Regression, Neural Networks, 17, 113, doi.org/10.1016/S0893-6080(03)00169-2 ; Fayyad (1996), From data mining to knowledge discovery in databases, AI magazine, 17, 37. ; Gołębiewski (2008), Changes in the acoustic properties of road porous surface with time of Acoustics, Archives, 33, 151. ; Cortez (2011), Opening black box data mining models using sensitivity analysis Symposium on Computational Intelligence and Data Mining IEEE Paris France, IEEE, 341. ; Tinoco (2014), A novel approach to predicting young s modulus of jet grouting laboratory formulations over time using data mining techniques, Engineering Geology, 169. ; Freitas (2010), In situ assessment of the normal incidence sound absorption coefficient of asphalt mixtures with a new impedance tube th International Congress and Exposition on Noise Control Engineering, INTERNOISE.

DOI

10.1515/aoa-2015-0054

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