Skip to main content
main-content

Tipp

Weitere Artikel dieser Ausgabe durch Wischen aufrufen

01.10.2019 | Original Article | Ausgabe 20/2019

Environmental Earth Sciences 20/2019

The multiple logistic regression recognition model for mine water inrush source based on cluster analysis

Zeitschrift:
Environmental Earth Sciences > Ausgabe 20/2019
Autoren:
Hao Zhang, Haofeng Xing, Duoxi Yao, Liangliang Liu, Daorui Xue, Fei Guo
Wichtige Hinweise

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

Mine water inrush is one of the major geological hazards that threaten safe production in coal mines. The accurate identification of mine water inrush sources plays a vital role in mine water disaster control, and it is the key to preventing mine water inrush incidents. Ninety-three water samples were extracted from the three types of aquifers in the Qinan coal mine. The cluster analysis method was then used to analyze 82 of the original water samples, and the other 11 water samples that did not meet the requirements were removed. Then, the remaining 82 water samples were regarded as training samples, and the principal component analysis was completed. Taking the scores of the principal components as the independent variable and the types of water inrush sources as the dependent variable, the multiple logistic regression recognition model was established. Meanwhile, this recognition model was used to recognize the types of mine water inrush sources and verify the recognition accuracy for the 82 training samples. The comprehensive recognition accuracy reached 86.6%, which is much higher than the traditional recognition methods of water inrush sources. Based on cluster analysis, the multiple logistic regression recognition model fully considers the ion content measurement errors and the complex relationships between the internal ions, and this recognition model is more reasonable and improves the accuracy of water inrush source recognition. This paper provides a new method for recognizing the problem of water inrush sources, which also provides an effective basis for mine water inrush prevention and control.

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 69.000 Bücher
  • über 500 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Umwelt
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 50.000 Bücher
  • über 380 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Umwelt
  • Maschinenbau + Werkstoffe




Testen Sie jetzt 30 Tage kostenlos.

Literatur
Über diesen Artikel

Weitere Artikel der Ausgabe 20/2019

Environmental Earth Sciences 20/2019 Zur Ausgabe