Modelling tyre-road noise with data mining techniques
| Autor: | Paulo A. A. Pereira, Francisco Emanuel Cunha Soares, Elisabete F. Freitas, Jocilene Otilia da Costa, Paulo Cortez, Joaquim Agostinho Barbosa Tinoco |
|---|---|
| Přispěvatelé: | Universidade do Minho |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Truck
Tyre-road noise Science & Technology Acoustics and Ultrasonics Computer science Work (physics) Aggregate (data warehouse) Function (mathematics) computer.software_genre Damping Data modeling Set (abstract data type) Noise Engenharia e Tecnologia::Engenharia Civil 11. Sustainability Engenharia Civil [Engenharia e Tecnologia] Surface characteristics Data mining Sensitivity (control systems) Texture computer Model |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| Popis: | The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors. This research was financed by FEDER Funds through “Programa Operacional Factores de Competitividade – COMPETE” and by Portuguese Funds through FCT – “Fundação para a Ciência e a Tecnologia”, within the Project PEst-OE/ECI/UI4047/2014. |
| Databáze: | OpenAIRE |
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