Artificial Intelligence and Learning Systems Methods in Supporting Long-Term Acoustic Climate Monitoring

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

Abstracts

EN

Developing effective methods for automatic identification of noise sources is currently one of the most important tasks in long-term acoustical climate monitoring of the environment. Manual verification of recorded data, when it comes to proper determination of noise levels, is time-consuming and costly. A possible solution is to use pattern recognition techniques for acoustic signal recorded by a monitoring station. This paper presents usefulness of special directed measurement techniques, acoustic signal processing, and classification methods using artificial intelligence (the Sammon mapping) and learning systems methods (Support Vector Machines) in the recognition of corona audible noise from ultra-high voltage AC transmission lines.

Keywords

EN

43.60.Lq; 07.05.Mh

Discipline

• 07.05.Mh: Neural networks, fuzzy logic, artificial intelligence

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2013
• Volume: 123
• Issue: 6
• Pages: 1024-1028

Dates

published

2013-06

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

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Identifiers

DOI

10.12693/APhysPolA.123.1024