吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 547-551.

Previous Articles     Next Articles

Extenics in debris flow risk evaluation based on minimum entropy analysis

WANG Ying-jie1, WANG Lei1, RONG Qi-guo2   

  1. College of Construction Engineering, Jilin University, Changchun 130026, China
  • Received:2012-08-02 Published:2013-06-01

PDF (PC)

404

Abstract:

Sixteen conventional evaluation-factors such as watershed area, maximum altitude difference wre chosen to evaluate the debris flow risk. Analyzing of the impact level of various factors on the debris flow and eliminated the correlation of the factors based on the minimum entropy analysis(MEA). According to the contribution rate to the debris system,the main factors and their weights were determined. On the basis of matter-element theory,extension set theory and dependent funetion ealeulation,a matter-element model evaluating the risk of debris flow.By practical calculation of dependent degree to the risk level of debris flow,the risk level is evaluated by extenics.Compared with the evaluation results of the literature,the debris flow evaluation results obtained by the extenics method can more precisely reflect the practical risk level of debris flow.This shows that the application of MEA to select the main factors and determine their weights has a certain rationality.

Key words: debris flow, risk evaluation, MEA, select the main factors, weight, Extenics

CLC Number: 

  • P642.23

[1] Badoux A, Graf C, Rhyner J, Kuntner R, McArdell BW (2009) A debris-flow alarm system for the Alpine Illgraben. Nat Hazards 49:517-539.

[2] 张晨,王清,陈剑平,等. 金沙江流域泥石流的组合赋权法危险度评价[J].岩土力学,2011,32(3):831-836. Zhang Chen,Wang Qing,Chen Jian-ping,et al. Evaluation of debris flow risk in Jinsha River based oncombined weight process[J]. Rock and Soil Mechanics, 2011,32(3):831-836.

[3] 刘希林,唐川.泥石流危险度评价[M].北京:科学出版社,1995.

[4] Lin P S, Lin J Y, Hung J C, et al.Assessing debris-flow hazard in a watershed in Taiwan[J]. Engineering Geology,2002, 66:295-313.

[5] Chang T C. Risk degree of debris flow applying neural networks[J]. Nature hazards,2007, 42:209-224.

[6] Hu¨rlimann M, Rickenmann D, Medina V, et al. Evaluation of approaches to calculate debrisflow parameters for hazard assessment. Eng Geol[J].2008, 102:152-163.

[7] Harris H J, Wenger R B, Harris V A, Devault D S. A method for assessing environmental risk: a case study of Green BayLake, Michigan, USA[J]. Environ Manage,1994,18:295-306.

[8] Liu X L, Lei J Z. A method for assessing regional debris flow risk: an application in Zhaotong of Yunnan province (SW China)[J]. Geomorphology,2003,52:181-191.

[9] Michel-Leiba M, Baynes F, Scott G, et al.Regional landslides risk to the Cairns community[J]. Nat Hazards,2003, 30:233-249.

[10] Chen Chien-chih, Tseng Chih-Yuan, Jia-Jyun Dong . New entropy-based method for variables selection and its application to the debris-flow hazard assessment[J]. Engineering Geology,2007, 94:19-26.

[11] Johnson V E, Albert J H. Ordinal Data Modeling[M]. Sringer, New York.USA,1999.

[12] Pareschi M T, Santacroce R, Sulpizio R, et al. Volcaniclastic debris flows in the Clanio Valley(Campania, Italy): in sights for the assessment of hazard potential[J]. Geomorphology,2002, 43:219-231.

[13] Rupert M G, Cannon S H, Gartner J E.Using logistic regression to predict the probability of debris flows occurring in areas recently Burned by Wildland Fires. US Geological Survey.2003, Open-file Report OF 03-500.
[1] DAI Cun-jie,LI Yin-zhen,MA Chang-xi,CHAI Huo,MU Hai-bo. Multi-criteria optimization for hazardous materials distribution routes under uncertain conditions [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1694-1702.
[2] LIU En-ze,WU Wen-fu. Agricultural surface multiple feature decision fusion disease judgment algorithm based on machine vision [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1873-1878.
[3] SHAN Ze-biao,LIU Xiao-song,SHI Hong-wei,WANG Chun-yang,SHI Yao-wu. DOA tracking algorithm using dynamic compressed sensing [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1938-1944.
[4] LIU Fu, LAN Xu-teng, HOU Tao, KANG Bing, LIU Yun, LIN Cai-xia. Metagenomic clustering method based on k-mer frequency optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1593-1599.
[5] ZHANG Man, SHI Shu-ming. Analysis of state transition characteristics for typical vehicle driving cycles [J]. 吉林大学学报(工学版), 2018, 48(4): 1008-1015.
[6] WANG Ji-xin, ZHAI Xin-ting, BI Ye-hong-tian, LI Ying-ying. Estimation of piecewise mixed load distribution based on AIC-K-means [J]. 吉林大学学报(工学版), 2018, 48(4): 1092-1098.
[7] YOSHINO Tatsuo, FAN Lu-lu, YAN Lei, XU Tao, LIN Ye, GUO Gui-kai. Multiobjective optimization design for dummy chest structure based on MBNWS algorithm [J]. 吉林大学学报(工学版), 2018, 48(4): 1133-1139.
[8] JIA Hong-lei, WANG Wan-peng, CHEN Zhi, ZHUANG Jian, WANG Wen-jun, LIU Hui-li. Real-time pressure measurement of profiling elastic press roller based on soil cone index [J]. 吉林大学学报(工学版), 2018, 48(4): 1169-1175.
[9] WANG Xu, OUYANG Ji-hong, CHEN Gui-fen. Measurement of graph similarity based on vertical dimension sequence dynamic time warping method [J]. 吉林大学学报(工学版), 2018, 48(4): 1199-1205.
[10] MOU Zong-lei, SONG Ping, ZHAI Ya-yu, CHEN Xiao-xiao. High accuracy measurement method for synchronous triggering pulse transmission delay in distributed test system [J]. 吉林大学学报(工学版), 2018, 48(4): 1274-1281.
[11] LIU Xue-juan, YUAN Jia-bin, XU Juan, DUAN Bo-jia. Quantum k-means algorithm [J]. 吉林大学学报(工学版), 2018, 48(2): 539-544.
[12] TAN Si-qiao, ZHANG Xi, LI Qian, AI Chen. Information push model-building based on maximum mutual information coefficient [J]. 吉林大学学报(工学版), 2018, 48(2): 558-563.
[13] HOU Xian-yao, CHEN Xue-wu. Use of public transit information market segmentation based onattitudinal factors [J]. 吉林大学学报(工学版), 2018, 48(1): 98-104.
[14] LIU Nian, XU Tao, XU Tian-shuang, HU Xian-lei, LIU Wei-hai. Lightweight design of TRB dashboard cross beam [J]. 吉林大学学报(工学版), 2018, 48(1): 199-204.
[15] LIU Yun, KANG Bing, HOU Tao, WANG Ke, LIU Fu. Optimal initialization-based C-means method [J]. 吉林大学学报(工学版), 2018, 48(1): 306-311.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd