Abstract
The karst collapse is very complicated and its influential factors are various and interdependent, besides, the geologic body itself is heterogeneous and uncertain.The fuzzy pattern recognition,which is a new fuzzy recognition method and can make the sorting more exactly, has been used in many territories.Therefore, it is necessary to adopt the fuzzy pattern recognition to forecast harzard of karst collapse.Because the existing adjoined degree couldn’t recognize efficiently, weight value was mingled with adjoined degree, then the fuzzy pattern recognition based on generalized euclidean weight distance adjoined degree was made in this paper, the reasonableness for the application of this model to forecast karst collpase hazard was discussed. Taking the karst collpase in Wuhan city as an example, 13 influence factors were chose, based on the new fuzzy pattern recognition method, the harzard of karst collapse in Wuhan city was forecast, it was found that the forecasting result was pretty accurate. Therefore, it could be concluded that the applicaition of fuzzy pattern recognition based on generalized eclidean weight distance adjoined degree in forecasting hazard of karst collpase was effective and reasonable.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jixian, X., Chengping, L.: Fuzzy mathematics and its application. Huazhong university of science and technology press, Wuhan (2006)
Hucheng, Zhihua, C.: The application of Gis to forecast karst collpase. Journal of GuiLin University of Technology 20, 117–119 (2000)
Hucheng, Zhihua, C., Xuejun, C.: Forecasting the karst collpase based on ANN and GIS techniques. Journal of China University of geoscience 28, 557–561 (2003)
Lixia, Z., Dajun, X.: Forecasting the karst collpase in Laiwu city. Journal of Shandong geology 18, 32–35 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Feng, Y., Chen, W. (2010). Fuzzy Pattern Recognition Based on Generalized Euclidean Weight Distance Adjoined Degree and Its Application in Forecasting Hazard of Karst Collapse . In: Cai, Z., Tong, H., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2010. Communications in Computer and Information Science, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16388-3_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-16388-3_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16387-6
Online ISBN: 978-3-642-16388-3
eBook Packages: Computer ScienceComputer Science (R0)