Detection and Classification of Selected Noise Sources in Long-Term Acoustic Climate Monitoring

• Authors: M. Kłaczyński , T. Wszołek
• Languages of publication: EN

Abstracts

EN

Continuous acoustical climate monitoring of the environment raises several problems related to large quantities of the recorded data, which often represents information unrelated to the studied noise source. Manual verification of such data is time-consuming and costly. Therefore, developing effective methods for automatic identification of transport noise sources becomes an important task for the proper determination of noise levels. This paper presents a concept of such method of automatic detection and classification of the noise sources from the air and railway transportation in the acoustic environmental monitoring.

Keywords

EN

43.60.Lq; 84.35.+i; 43.55.Ka

Discipline

• 84.35.+i: Neural networks(for optical neural networks, see 42.79.Ta; see also 07.05.Mh Neural networks, fuzzy logic, artificial intelligence in computers in experimental physics; 87.18.Sn in biological complexity)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2012
• Volume: 121
• Issue: 1A
• Pages: A-179-A-182

Dates

published

2012-01

Contributors

author

M. Kłaczyński

• AGH University of Science and Technology, Faculty of Mechanical Engineering and Robotics Department of Mechanics and Vibroacoustics, al. A. Mickiewicza 30, 30-059 Krakow, Poland

author

T. Wszołek

• AGH University of Science and Technology, Faculty of Mechanical Engineering and Robotics Department of Mechanics and Vibroacoustics, al. A. Mickiewicza 30, 30-059 Krakow, Poland

References

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Identifiers

DOI

10.12693/APhysPolA.121.A-179