Fuzzy logic algorithms in the analysis of electrotelluric data with reference to monitoring of volcanic activity
The expert processing of monitoring data of large networks on hazardous natural phenomena becomes increasingly more complicated due to an increase in the initial data flow. An approach alternative to the visual recognition of signals is proposed. A number of recognition algorithms and results of the...
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| Vydáno v: | Izvestiya. Physics of the solid earth Ročník 43; číslo 7; s. 597 |
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| Hlavní autoři: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Dordrecht
Springer Nature B.V
01.07.2007
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| ISSN: | 1069-3513, 1555-6506 |
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| Abstract | The expert processing of monitoring data of large networks on hazardous natural phenomena becomes increasingly more complicated due to an increase in the initial data flow. An approach alternative to the visual recognition of signals is proposed. A number of recognition algorithms and results of their application to the analysis of geoelectric potential monitoring data are discussed. Data of monitoring La Fournaise Volcano (Réunion Island) obtained in the vicinity of the intense volcanic eruption of 1988 are used. The obtained results show that these algorithms are capable of recognizing anomalous segments of records and discriminating between several types of anomalies presumably associated with the effects of various physical factors (heavy atmospheric precipitation, hydrothermal processes, and so on). The algorithms proposed in this work can be used both for the automation of expert work in operating monitoring systems and in investigations aimed at the identification of typical morphologic sequences in time series of data of various origins.[PUBLICATION ABSTRACT] |
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| AbstractList | The expert processing of monitoring data of large networks on hazardous natural phenomena becomes increasingly more complicated due to an increase in the initial data flow. An approach alternative to the visual recognition of signals is proposed. A number of recognition algorithms and results of their application to the analysis of geoelectric potential monitoring data are discussed. Data of monitoring La Fournaise Volcano (Réunion Island) obtained in the vicinity of the intense volcanic eruption of 1988 are used. The obtained results show that these algorithms are capable of recognizing anomalous segments of records and discriminating between several types of anomalies presumably associated with the effects of various physical factors (heavy atmospheric precipitation, hydrothermal processes, and so on). The algorithms proposed in this work can be used both for the automation of expert work in operating monitoring systems and in investigations aimed at the identification of typical morphologic sequences in time series of data of various origins.[PUBLICATION ABSTRACT] |
| Author | Le Mouél, J L Graeva, E M Agayan, S M Rodkin, M V Zlotnicki, J Bogoutdinov, Sh R Gvishiani, A D |
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| DOI | 10.1134/S1069351307070099 |
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| SubjectTerms | Algorithms Monitoring systems Precipitation Volcanic eruptions Volcanoes |
| Title | Fuzzy logic algorithms in the analysis of electrotelluric data with reference to monitoring of volcanic activity |
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