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                <identifier>oai:data.mendeley.com/25v3pdk9jj.1</identifier>
                <datestamp>2025-06-09T07:56:37Z</datestamp>
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    <dc:creator id="https://orcid.org/0000-0002-6434-3307">Colpo, Leonardo</dc:creator>
    <dc:title>Dataset for Machine Learning Training of Road Class Recognition</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This data contain the files for training ML algorithms in order to recognize a road ISO class.

- Ground_Profile contains the .mat vector of ground, containing shuffles parts of road classes A,B and C.
- Vehicle_Data contains the vehicle data used in simulations.
- Training_Data is the dataset used for ML training. Each column has its name on the .mat table file. In road class, Class A =1, Class B=2 and Class C =3.
- Machine Learning Classification Results contain the results for the trained algorithms for different classes and velocity, besides the F1-score calculation.
- Vibration Reduction Results is the RMS and ISO acceleration values of the proposed approach, comparing to traditional benchmarks.</dc:description>
    <dc:subject>Machine Learning</dc:subject>
    <dc:subject>Fuzzy Control</dc:subject>
    <dc:contributor id="https://orcid.org/0000-0001-5635-1852">Martins Gomes, Herbert</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/25v3pdk9jj.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/25v3pdk9jj.1</dc:identifier>
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    <dc:date>2025-06-09T07:56:37Z</dc:date>
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