Modelling Tyre-Road Noise with Data Mining Techniques
Bueno M., Luong J., Vi˜nuela U., Ter´an F., Paje S.E. (2011), Pavement temperature influence on close proximity tire/road noise, Applied Acoustics, 72, 11, 829–835.
Cherkassky V., Ma Y. (2004), Practical Selection of SVM Parameters and Noise Estimation for SVM Regression, Neural Networks, 17, 1, 113–126.
Chopra A.K. (1995), Dynamics of structures, Prentice Hall Inc.
Chou J., Chiu C., Farfoura M., Al-Taharwa I. (2011), Optimizing the prediction accuracy of concrete compressive strength based on a comparison of data-mining techniques, Journal of Computing in Civil Engineering, 25, 3, 242–253.
Cortes C., Vapnik V. (1995), Support-vector networks, Machine learning, 20, 3, 273–297.
Cortez P., Embrechts M. (2011), Opening black box data mining models using sensitivity analysis, IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2011, IEEE, Paris, France, 341–348.
Cortez P., Embrechts M. (2013), Using sensitivity analysis and visualization techniques to open black box data mining models, Information Sciences, 225, 1–17.
Cortez P. (2010), Data mining with neural networks and support vector machines using the R/rminer tool, Perner P. 10th Industrial conference on data mining, advances in data mining: applications and theoretical aspects, Berlin, Germany: LNAI 617: Springer, 572–583.
DEUFRAKO (2009), Prediction and Propagation of Rolling Noise, Final Report.
Domingos P. (2012), A few useful things to know about machine learning, Communications of the ACM, 55, 10, 78–87.
EN ISO 13473-1 (2004), Characterization of pavement texture by use of surface profiles – Part 1: Determination of Mean Profile Depth.
Ertel W. (2009), Introduction to Artificial Intelligence, Springer.
EWINS (2000), Modal Testing: Theory, Practice and Application, Research Studies Press Ltd., UK.
Fayyad U., Piatetsky-Shapiro G., Smyth P. (1996a), From data mining to knowledge discovery in databases, AI magazine, 17, 3, 37–54.
Fayyad U., Piatetsky-Shapiro G., Smyth P. (1996b), The KDD process for extracting useful knowledge from volumes of data, Communications of the ACM, 39, 11, 27–34.
Freitas E., Raimundo I., In´acio O., Pereira P. (2010), In situ assessment of the normal incidence sound absorption coefficient of asphalt mixtures with a new impedance tube, 39th International Congress and Exposition on Noise Control Engineering – INTER-NOISE 2010, Lisbon.
Freitas E., Mendonc¸a C., Santos J.A., Murteira C., Ferreira J.P. (2012), Traffic noise abatement: How different pavements, vehicle speeds and traffic densities affect annoyance levels, Transportation Research Part D: Transport and Environment, 17, 4, 321–326.
Gołębiewski R. (2008), Changes in the acoustic properties of road porous surface with time, Archives of Acoustics, 33, 2, 151–164.
Gomes Correia A., Cortez P., Tinoco J., Marques R. (2013), Artificial Intelligence Applications in Transportation Geotechnics, Geotechnical and Geological Engineering, 31, 3, 861–879.
Hamel L. (2009), Knowledge Discovery with Support Sector Machines, Wiley-Interscience.
Hastie T., Tibshirani R., Friedman J. (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition, Springer-Verlag.
ISO 11819-1 (1997), Acoustics – Method for measuring the influence of road surfaces on traffic noise – Part 1: statistical pass-by method.
ISO CD 11819-2 (2000), Acoustics – Method for Measuring the Influence of Road Surfaces on Traffic Noise – Part 1: The Close Proximity Method.
ISO 13473-5 (2009), Characterization of pavement texture by use of surface profiles – Part 5: Determination of megatexture.
Kaczmarek T., Preis A. (2010), Annoyance of time-varying road-traffic noise, Archives of Acoustics, 35, 3, 383–393.
Kenig S., Ben-David A., Orner M., Sadeh A. (2001), Control of properties in injection molding by neural networks, Engineering Applications of Artificial Intelligence, 14, 819–823.
Kumar K., Parida M., Katiyar V. (2011), Road Traffic Noise Prediction with Neural Networks – A Review, An International Journal Of Optimization And Control: Theories & Applications (IJOCTA), 2, 1, 29–37.
Larsson K. (2002), Modelling of dynamic contact – exemplified on the tyre-road interaction, PhD Thesis, Department of Applied Acoustics, Calmers University of Technology, Gothenburg, Sweden.
Mak K.-L., Hung W.-T. (2014), Statistical tyre/road noise modeling in Hong Kong on friction course, Applied Acoustics, 76, 0, 24–27.
Mendonc¸a C., Freitas E., Ferreira J.P., Raimundo I., Santos J.A. (2013), Noise abatement and traffic safety: The trade-off of quieter engines and pavements on vehicle detection, Accident Analysis & Prevention, 51, 0, 11–17.
Miranda T., Comes Correia A., Santos M., Sousa L., Cortez P. (2011), New Models for Strength and Deformability Parameter Calculation in Rock Masses Using Data-Mining Techniques, International Journal of Geomechanics, 11, 44–58.
Morgan P., Sandberg U., Blokland G. (2009), The selection of new reference test tyres for use with the CPX method, to be specified in ISO/TS 11819-3, 38th International Congress and Exposition on Noise Control Engineering – INTER-NOISE, Ottawa.
R DEVELOPMENT CORE TEAM (2009), R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, Web site: http://www.r-project.org/.
Raimundo I., Freitas E., In´acio O., Pereira P. (2010), Sound absorption coefficient of wet gap graded asphalt mixtures, 39th International Congress and Exposition on Noise Control Engineering – INTER-NOISE 2010, Lisbon.
Sandberg U., Ejsmont J. (2002), Tyre/Road Noise Reference Book, Informex SE – 59040, Kisa, Sweden.
Sayers M.W. (1995), On the calculation of International Roughness Index from Longitudinal Road Profile, Transportation Research Record 1501, Transportation Research Board, Washington D.C., 1–12.
Schölkopf B., Smola A.J. (2002), Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, The MIT Press.
Smola A.J., Schölkopf B. (2004), A tutorial on support vector regression, Statistics and Computing, 14, 3, 199–222.
Steinwart I., Christmann A. (2008), Support Vector Machines, Springer.
Taylor P., Anand S., Griffiths N., Adamu-Fika F., Dunoyer A., Popham T. (2012), Automotive UI'12, Proceedings of the 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 233–240.
Tinoco J., Gomes Correia A., Cortez P. (2011), Application of data mining techniques in the estimation of the uniaxial compressive strength of jet grouting columns over time, Construction and Building Materials, 25, 1257–1262.
Tinoco J., Gomes Correia A., Cortez P. (2014), A novel approach to predicting young’s modulus of jet grouting laboratory formulations over time using data mining techniques, Engineering Geology, 169, 50–60.
Zhou G., Wang L., Wang D., Reichle S. (2010), Integration of GIS and Data Mining Technology to Enhance the Pavement Management Decision Making, Journal of Transportation Engineering, 136, 4, 332–341.
Copyright © Polish Academy of Sciences & Institute of Fundamental Technological Research (IPPT PAN)