Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare
The aim of the paper was to build the models of sound pressure level as a function of traffic intensity in thoroughfare. The models were built by using artificial analytical models or regression trees. The former included Nordic Prediction Method. The latter were represented by Random Forest and Cub...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2019-01-01
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| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | https://doi.org/10.1051/matecconf/201925402038 |
| _version_ | 1818344042207903744 |
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| author | Kekez Michał |
| author_facet | Kekez Michał |
| author_sort | Kekez Michał |
| collection | DOAJ |
| description | The aim of the paper was to build the models of sound pressure level as a function of traffic intensity in thoroughfare. The models were built by using artificial analytical models or regression trees. The former included Nordic Prediction Method. The latter were represented by Random Forest and Cubist. The analysis of accuracy of all obtained models was conducted. The best models can be used in the process of reconstruction of equivalent sound level data. |
| first_indexed | 2024-12-13T16:40:11Z |
| format | Article |
| id | doaj.art-e3cd39c8154e4b24a6d20315313cbc4d |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-13T16:40:11Z |
| publishDate | 2019-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-e3cd39c8154e4b24a6d20315313cbc4d2022-12-21T23:38:18ZengEDP SciencesMATEC Web of Conferences2261-236X2019-01-012540203810.1051/matecconf/201925402038matecconf_mms18_02038Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfareKekez Michał0Kielce University of Technology, Faculty of Mechatronics and Mechanical EngineeringThe aim of the paper was to build the models of sound pressure level as a function of traffic intensity in thoroughfare. The models were built by using artificial analytical models or regression trees. The former included Nordic Prediction Method. The latter were represented by Random Forest and Cubist. The analysis of accuracy of all obtained models was conducted. The best models can be used in the process of reconstruction of equivalent sound level data.https://doi.org/10.1051/matecconf/201925402038traffic noisenordic prediction methodrandom forest |
| spellingShingle | Kekez Michał Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare MATEC Web of Conferences traffic noise nordic prediction method random forest |
| title | Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare |
| title_full | Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare |
| title_fullStr | Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare |
| title_full_unstemmed | Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare |
| title_short | Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare |
| title_sort | application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare |
| topic | traffic noise nordic prediction method random forest |
| url | https://doi.org/10.1051/matecconf/201925402038 |
| work_keys_str_mv | AT kekezmichał applicationofselectedcomputationalintelligencemethodstosoundlevelmodellingbasedontrafficintensityinthoroughfare |