基于AIFFC算法的地质灾害易发性评价因子分级优化

陈宾; 李颖懿; 张联志; 屈添强; 魏娜; 刘宁; 黄春林

doi:10.16031/j.cnki.issn.1003-8035.202210048

基于AIFFC算法的地质灾害易发性评价因子分级优化

doi: 10.16031/j.cnki.issn.1003-8035.202210048

陈宾^{1, 2,},
李颖懿¹,
张联志^3, ,,
屈添强³,
魏娜¹,
刘宁¹,
黄春林³

1.
湘潭大学土木工程学院, 湖南湘潭　411105
2.
湘潭大学岩土力学与工程安全湖南省重点实验室, 湖南湘潭　411105
3.
湖南省国土空间调查监测所, 湖南长沙　410000

基金项目: 湖南省创新性省份建设专项（No. 2019RS1059）；国家自然科学基金项目（No. 51774131，No. 41972282）

详细信息

作者简介:
陈宾：作者简介：陈宾（1977—），男，汉族，河南驻马店人，副教授，博士，主要从事地质灾害防治方面的研究工作。E-mail：403021235@qq.com

通讯作者:
张联志（1988—），男，汉族，江苏沛县人，硕士，工程师，水工环地质方向。E-mail：2149859375@qq.com

中图分类号: P692
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出版历程
- 收稿日期: 2022-10-27
- 网络出版日期: 2023-11-20

Classification Optimization of Geological Hazard Susceptibility Evaluation Factors Based on AIFFC Algorithm

1.
School of Civil Engineering, Xiangtan University, Xiangtan　411105, China
2.
Hunan Provincial Key Laboratory of Geomechanics and Engineering Safety, Xiangtan University, Xiangtan　411105, China
3.
Hunan Provincial Territorial Space Survey and Monitoring Institute, Changsha　410000, China

摘要

摘要: 本文针对地质灾害易发性评价因子分级数不确定的问题，引入自适应膨胀因子模糊覆盖分级方法（AIFFC）对易发性评价因子分级进行优化。以湖南省湘乡市为研究区，提取了坡度、坡向、高程、年平均降雨量、归一化植被指数（NDVI）、道路、断层、岩性和土地利用9类评价因子，运用AIFFC及自然断点法对连续型因子进行分级，并分别代入加权信息量模型和随机森林模型，获取研究区易发性区划图。采用单因子分级结果精度对比、灾积比分析和易发性分区结果ROC曲线对比对AIFFC分级法的优越性进行检验，结果表明：各因子采用AIFFC算法分级的AUC值均高于自然断点法；基于AIFFC的随机森林模型及加权信息量模型的高易发区灾积比分别提升了56.3%、74.6%，低易发区灾积比分别降低了48%、58.1%，AUC值分别提升了7.6%、2.7%。采用AIFFC分级方法优化了地质灾害易发性评价因子分级，显著提高了地质灾害易发性评价的合理性。
- 膨胀因子 /
- 模糊覆盖 /
- 加权信息量 /
- 随机森林 /
- 易发性评价
Abstract: This paper addresses the issue of uncertainty in the grading of geological hazard susceptibility evaluation factors and introduces the adaptive expansion factor fuzzy coverage grading method (AIFFC) to optimize the grading of geological hazard susceptibility evaluation factors. Taking Xiangxiang city, Hunan province as the research area, nine evaluation factors, including slope, slope direction, elevation and average annual rainfall, normalized difference vegetation index (NDVI) for land use, roads, faults, lithology, were extracted. The AIFFC method and the natural breakpoint method were used to grade continuous factors. These graded factors were then incorporated into a weighted information model and random forest model to obtain a susceptibility zoning map for the study area. The superiority of the AIFFC classification method was tested through the comparison of single-factor grading results, disaster product ratio analysis,and ROC curve comparison of susceptibility zoning results. Based on AIFFC, the hazard accumulation ratio of the random forest model and the weighted information entropy model in the high susceptibility areas increased by 56.3% and 74.6%, respectively, while in the low susceptibility areas, it decreased by 48% and 58.1%, respectively. The AUC values increased by 7.6% and 2.7%, respectively. The AIFFC classification method is used to optimize the evaluation factor classification of geological disaster susceptibility, which significantly improves the rationality of the evaluation of geological disaster susceptibility.
- expansion factor /
- fuzzy covering /
- weighted information entropy /
- random forest /
- susceptibility assessment

HTML全文

图 1 湘乡市地质灾害分布图

Figure 1. Geological disaster distribution map of Xiangxiang City

下载: 全尺寸图片幻灯片

图 2 易发性各评价因子图层

Figure 2. Layers of susceptibility evaluation factors

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图 3 各模型易发性分区图

Figure 3. Susceptibility zoning maps of each model

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图 4 单因子ROC曲线分析图

Figure 4. Single-factor ROC curve analysis

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图 5 各模型ROC曲线图

Figure 5. ROC curve for various models

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表 1 各评价因子AIFFC分级参数

Table 1. AIFFC classification parameters for each evaluation factor

评价因子	研究区范围	灾害点分布范围	d_i	λ	分级数（l）	分级区间（{ρ_l}）
坡度/（°）	[0,71.26]	[2,70]	1.0～2.0	8	7	{1, 12, 125, 35, 14, 49, 34}
坡向/（°）	[0,360]	[0,360]	1.0～1.67	20	12	{10, 11, 19, 23, 38, 52, 25, 30, 25, 15, 9, 13}
高程/m	[31.90,800.44]	[113.12,456.70]	1.0～2.0	40.33	8	{112, 92, 34, 22, 5, 3, 1, 1}
年平均降雨量/mm	[1202.70,1600.43]	[1221.03,1554.89]	1.0～1.9	22.81	10	{1, 2, 14, 19, 59, 70, 60, 36, 8, 1}
NDVI	[0,0.61]	[0.015,0.417]	1.0～1.5	0.04	6	{7, 27, 48, 89, 85, 14}
距道路距离/m	[0,大于3483.20]	[326.11,3483.20]	1.0～1.79	230.84	10	{102, 55, 33, 37, 16, 10, 10, 5, 1, 1}
距断层距离/m	[0,大于4634.35]	[423.71,4634.35]	1.0～1.5	236.17	11	{75, 57, 43, 38, 10, 16, 10, 6, 5, 5, 5}

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表 2 AIFFC分级结果

Table 2. AIFFC classification results

评价因子	分级数	分级结果
坡度/（°）	8	0～2；2～22；22～35；35～48；48～55；55～65；65～70；大于70
坡向/（°）	12	0～30；30～68；68～90；90～125；125～162；162～190；190～225；225～260；260～280；280～310；310～338；338～360
高程/m	9	31.9～113.12；113.12～165.57；165.57～221.23；221.23～278.54；278.54～333.59；333.59～367.50；367.50～408.51；408.51～456.70；大于456.70
年平均降雨量/mm	11	1 202.70～1 221.03；1 221.03～1 283.85；1 283.85～1 336.92；1 336.92～1 368.54；1 368.54～1 410.03； 1 410.03～1 446.28；1 446.28～1 484.91；1 484.91～1 516.62；1 516.62～1 536.87；1 536.87～1 554.89；大于1 554.89
NDVI	7	0～0.015；0.015～0.180；0.180～0.246；0.246～0.316；0.316～0.377；0.377～0.417；大于0.417
距道路距离/m	11	0～326.11；326.11～664.23；664.23～989.03；989.03～1368.63；1 368.63～1 688.75；1 688.75～2 075.72； 2 075.72～2 497.47；2 497.47～2 831.94；2 831.94～3 065.30；3 065.30～3 483.20；大于3 483.20
距断层距离/m	12	0～423.71；423.71～850.88；850.88～1 272.26；1 272.27～1 694.48；1 694.49～2 150.42；2 150.43～2 485.00；2 485.01～3 005.74；3 005.75～3 523.15；3 523.16～4 107.21；4 107.22～4 248.58；4 248.59～4 634.35；大于4 634.35

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表 3 自然断点法分级结果

Table 3. Natural break point method grading results

评价因子	分级数	分级结果
坡度/（°）	8	0～3.91；3.91～9.50；9.50～15.37；15.37～20.95；20.95～26.26；26.26～31.85；31.85～38.56；38.56～71.26
坡向/（°）	12	0～24.48；24.48～ 57.04；57.04～88.18；88.18～ 117.91；117.91～147.64；147.64～ 177.37；177.37～ 208.52；208.52～239.66；239.66～269.39；269.39～ 299.12；299.12～ 328.85；328.85～ 360.00
高程/m	9	31.90～79.93；79.93～121.96；121.96～166.99；166.99～218.03；218.03～275.07；275.07～341.11；341.11～425.17；425.17～542.26；542.26～800.44
年平均降雨量/mm	11	1 202.70～1 289.62；1 289.62～1 333.91；1 333.91～1 363.46；1 363.46～1 386.40；1 386.40～1 405.55；1 405.55～1 425.18；1 425.18～1 444.75；1 444.75～1 463.71；1 463.71～1 488.88；1 488.88～1 523.98；1 523.98～1 600.42
NDVI	7	0～0.051；0.051～0.152；0.152～0.208；0.208～0.259；0.259～0.303；0.303～0.347；0.347～0.611
距道路距离/m	11	0～71.14；71.14～167.93；167.93～287.96；287.96～398.67；398.67～534.77；534.77～757.79；757.79～1 088.95；1 088.95～1 532.08；1 532.08～2 160.22；2 160.22～3 483.20；大于3 483.20
距断层距离/m）	12	0～93.41；93.41～195.93；195.93～317.53；317.53～464.40；464.40～667.68；667.68～850.88；850.88～1 059.58；1 059.58～1 363.72；1 363.72～1 914.46；1 914.46～2 795.16；2 795.16～4 634.35；大于4 634.35

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表 4 易发性评价结果灾积比统计表

Table 4. Statistical table of disaster accumulation ratio - product ratio for susceptibility evaluation results

评价模型	易发性分区	面积占比	灾积比	评价模型	易发性分区	面积占比	灾积比
NBC-MIV	高易发	13.62%	0.611	AIFFC-MIV	高易发	11.73%	0.955
	中易发	25.42%	0.178		中易发	19.61%	0.147
	低易发	60.96%	0.050		低易发	68.76%	0.026
NBC-RF	高易发	15.03%	0.755	AIFFC-RF	高易发	9.68%	1.318
	中易发	28.53%	0.096		中易发	25.86%	0.083
	低易发	56.44%	0.031		低易发	64.45%	0.013

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参考文献(29)

[1]	焦伟之,张明,谢鑫鹏,等. 基于GIS与加权信息量模型的城镇地质灾害易发性评价——以大新镇为例[J]. 安全与环境工程,2022,29(4):119 − 128. [JIAO Weizhi,ZHANG Ming,XIE Xinpeng,et al. Susceptibility evaluation of urban geological disaster based on GIS and weighted information value model—a case study of Daxin town[J]. Safety and Environmental Engineering,2022,29(4):119 − 128. (in Chinese with English abstract) JIAO Weizhi, ZHANG Ming, XIE Xinpeng, et al. Susceptibility evaluation of urban geological disaster based on GIS and weighted information value model—a case study of Daxin town［J］. Safety and Environmental Engineering, 2022, 29（4）: 119 − 128. （in Chinese with English abstract）
[2]	赵魁. 基于ArcGIS的云安区地质灾害易发性分区评价[J]. 地质灾害与环境保护,2020,31(4):38 − 42. [ZHAO Kui. The study of geological disaster susceptible division in Yun’an district based on arcgis[J]. Journal of Geological Hazards and Environment Preservation,2020,31(4):38 − 42. (in Chinese with English abstract) ZHAO Kui. The study of geological disaster susceptible division in Yun’an district based on arcgis［J］. Journal of Geological Hazards and Environment Preservation, 2020, 31（4）: 38 − 42. （in Chinese with English abstract）
[3]	许冲,戴福初,姚鑫,等. 基于GIS与确定性系数分析方法的汶川地震滑坡易发性评价[J]. 工程地质学报,2010,18(1):15 − 26. [XU Chong,DAI Fuchu,YAO Xin,et al. GIS platform and certainty factor analysis method based Wenchuan earthquake-induced landslide susceptibility evaluation[J]. Journal of Engineering Geology,2010,18(1):15 − 26. (in Chinese with English abstract) XU Chong, DAI Fuchu, YAO Xin, et al. GIS platform and certainty factor analysis method based Wenchuan earthquake-induced landslide susceptibility evaluation［J］. Journal of Engineering Geology, 2010, 18（1）: 15 − 26. （in Chinese with English abstract）
[4]	刘福臻,王灵,肖东升. 机器学习模型在滑坡易发性评价中的应用[J]. 中国地质灾害与防治学报,2021,32(6):98 − 106. [LIU Fuzhen,WANG Ling,XIAO Dongsheng. Application of machine learning model in landslide susceptibility evaluation[J]. The Chinese Journal of Geological Hazard and Control,2021,32(6):98 − 106. (in Chinese with English abstract) LIU Fuzhen, WANG Ling, XIAO Dongsheng. Application of machine learning model in landslide susceptibility evaluation［J］. The Chinese Journal of Geological Hazard and Control, 2021, 32（6）: 98 − 106. （in Chinese with English abstract）
[5]	孙德亮,马祥龙,唐小娅,等. 基于不同因子分级的滑坡易发性区划对比——以万州区为例[J]. 重庆师范大学学报(自然科学版),2021,38(5):43 − 54. [SUN Deliang,MA Xianglong,TANG Xiaoya,et al. Comparison of landslide susceptibility mapping based on different factor classifications:taking Wanzhou district as an example[J]. Journal of Chongqing Normal University (Natural Science),2021,38(5):43 − 54. (in Chinese with English abstract) SUN Deliang, MA Xianglong, TANG Xiaoya, et al. Comparison of landslide susceptibility mapping based on different factor classifications: taking Wanzhou district as an example［J］. Journal of Chongqing Normal University （Natural Science）, 2021, 38（5）: 43 − 54. （in Chinese with English abstract）
[6]	闫举生,谭建民. 基于不同因子分级法的滑坡易发性评价——以湖北远安县为例[J]. 中国地质灾害与防治学报,2019,30(1):52 − 60. [YAN Jusheng,TAN Jianmin. Landslide susceptibility assessment based on different factor classification methods—a case study in Yuan’an County of Hubei Province[J]. The Chinese Journal of Geological Hazard and Control,2019,30(1):52 − 60. (in Chinese with English abstract) YAN Jusheng, TAN Jianmin. Landslide susceptibility assessment based on different factor classification methods—a case study in Yuan’an County of Hubei Province［J］. The Chinese Journal of Geological Hazard and Control, 2019, 30（1）: 52 − 60. （in Chinese with English abstract）
[7]	解明礼,巨能攀,赵建军,等. 区域地质灾害易发性分级方法对比分析研究[J]. 武汉大学学报(信息科学版),2021,46(7):1003 − 1014. [XIE Mingli,JU Nengpan,ZHAO Jianjun,et al. Comparative analysis on classification methods of geological disaster susceptibility assessment[J]. Geomatics and Information Science of Wuhan University,2021,46(7):1003 − 1014. (in Chinese with English abstract) XIE Mingli, JU Nengpan, ZHAO Jianjun, et al. Comparative analysis on classification methods of geological disaster susceptibility assessment［J］. Geomatics and Information Science of Wuhan University, 2021, 46（7）: 1003 − 1014. （in Chinese with English abstract）
[8]	凌晓,刘甲美,王涛,等. 基于致灾因子对称法分级的信息量模型在地震滑坡危险性评价中的应用[J]. 国土资源遥感,2021,33(2):172 − 181. [LING Xiao,LIU Jiamei,WANG Tao,et al. Application of information value model based on symmetrical factors classification method in landslide hazard assessment[J]. Remote Sensing for Land & Resources,2021,33(2):172 − 181. (in Chinese with English abstract) LING Xiao, LIU Jiamei, WANG Tao, et al. Application of information value model based on symmetrical factors classification method in landslide hazard assessment［J］. Remote Sensing for Land & Resources, 2021, 33（2）: 172 − 181. （in Chinese with English abstract）
[9]	郭建华,刘初群,刘翠. 基于遗传算法优化的城市标准循环工况构建[J]. 科学技术与工程,2017,17(15):327 − 333. [GUO Jianhua,LIU Chuqun,LIU Cui. The construction of standard driving cycle based on genetic algorithm optimization[J]. Science Technology and Engineering,2017,17(15):327 − 333. (in Chinese with English abstract) GUO Jianhua, LIU Chuqun, LIU Cui. The construction of standard driving cycle based on genetic algorithm optimization［J］. Science Technology and Engineering, 2017, 17（15）: 327 − 333. （in Chinese with English abstract）
[10]	陈绪钰,倪化勇,李明辉,等. 基于加权信息量和迭代自组织聚类的地质灾害易发性评价[J]. 灾害学,2021,36(2):71 − 78. [CHEN Xuyu,NI Huayong,LI Minghui,et al. Geo-hazard susceptibility evaluation based on weighted information value model and ISODATA cluster[J]. Journal of Catastrophology,2021,36(2):71 − 78. (in Chinese with English abstract) CHEN Xuyu, NI Huayong, LI Minghui, et al. Geo-hazard susceptibility evaluation based on weighted information value model and ISODATA cluster［J］. Journal of Catastrophology, 2021, 36（2）: 71 − 78. （in Chinese with English abstract）
[11]	陈伟. 山区村镇滑坡灾害风险评估研究[D]. 武汉:武汉大学,2019. [CHEN Wei. Study on landslide risk assessment in mountainous villages and towns[D]. Wuhan:Wuhan University,2019. (in Chinese with English abstract) CHEN Wei. Study on landslide risk assessment in mountainous villages and towns[D]. Wuhan: Wuhan University, 2019. （in Chinese with English abstract）
[12]	孙娟娟,江南,刘缵武. 基于自适应膨胀因子的模糊覆盖分级方法[J]. 测绘科学技术学报,2007,24(5):384 − 386. [SUN Juanjuan,JIANG Nan,LIU Zuanwu. Fuzzy cover approach for clustering based on adaptive inflation factor[J]. Journal of Zhengzhou Institute of Surveying and Mapping,2007,24(5):384 − 386. (in Chinese with English abstract) SUN Juanjuan, JIANG Nan, LIU Zuanwu. Fuzzy cover approach for clustering based on adaptive inflation factor［J］. Journal of Zhengzhou Institute of Surveying and Mapping, 2007, 24（5）: 384 − 386. （in Chinese with English abstract）
[13]	孙娟娟. 专题地图数据分级模型的研究——现代数学在地图数据分级中的应用[D]. 郑州:解放军信息工程大学,2007. [SUN Juanjuan. Research of classification model for thematic mapping data[D]. Zhengzhou:PLA Information Engineering University,2007. (in Chinese with English abstract) SUN Juanjuan. Research of classification model for thematic mapping data[D]. Zhengzhou: PLA Information Engineering University, 2007. （in Chinese with English abstract）
[14]	姚宇婕,陈毓芬. 引导型专题数据分级处理研究[J]. 测绘工程,2012,21(1):25 − 29. [YAO Yujie,CHEN Yufen. Research on guiding thematic data classification[J]. Engineering of Surveying and Mapping,2012,21(1):25 − 29. (in Chinese with English abstract) doi: 10.3969/j.issn.1006-7949.2012.01.007 YAO Yujie, CHEN Yufen. Research on guiding thematic data classification［J］. Engineering of Surveying and Mapping, 2012, 21（1）: 25 − 29. （in Chinese with English abstract） doi: 10.3969/j.issn.1006-7949.2012.01.007
[15]	张涵斐. 多尺度地理信息显示处理与发布技术研究[D]. 郑州:解放军信息工程大学,2012. [ZHANG Hanfei. Research on the display processing and publish technology of multi-scale geographic information[D]. Zhengzhou:PLA Information Engineering University,2012. (in Chinese with English abstract) ZHANG Hanfei. Research on the display processing and publish technology of multi-scale geographic information[D]. Zhengzhou: PLA Information Engineering University, 2012. （in Chinese with English abstract）
[16]	牟廉明,黄国兴. 一种基于自适应膨胀因子的聚类新方法[J]. 计算机工程,2003,29(9):100 − 102. [MOU Lianming,HUANG Guoxing. New approach of clustering based on adaptive inflation factor[J]. Computer Engineering,2003,29(9):100 − 102. (in Chinese with English abstract) MOU Lianming, HUANG Guoxing. New approach of clustering based on adaptive inflation factor［J］. Computer Engineering, 2003, 29（9）: 100 − 102. （in Chinese with English abstract）
[17]	赖冠中,陈文音. 基于自然断点法分析的城乡建设用地整理潜力分区研究——以汕头市濠江区为例[J]. 广西城镇建设,2019(12):123 − 127. [LAI Guanzhong,CHEN Wenyin. Study on potential zoning of urban and rural construction land consolidation based on natural breakpoint analysis—a case study of Haojiang district,Shantou city[J]. Cities and Towns Construction in Guangxi,2019(12):123 − 127. (in Chinese) doi: 10.3969/j.issn.1672-7045.2019.12.016 LAI Guanzhong, CHEN Wenyin. Study on potential zoning of urban and rural construction land consolidation based on natural breakpoint analysis—a case study of Haojiang district, Shantou city［J］. Cities and Towns Construction in Guangxi, 2019（12）: 123 − 127. （in Chinese） doi: 10.3969/j.issn.1672-7045.2019.12.016
[18]	尹子虚. 基于夜光数据的城市空间特征提取尺度研究[D]. 大连:辽宁师范大学,2021. [YIN Zixu. Study on the scale of urban spatial feature extraction based on nighttime light data[D]. Dalian:Liaoning Normal University,2021. (in Chinese with English abstract) YIN Zixu. Study on the scale of urban spatial feature extraction based on nighttime light data[D]. Dalian: Liaoning Normal University, 2021. （in Chinese with English abstract）
[19]	孟晓捷,张新社,曾庆铭,等. 基于加权信息量法的黄土滑坡易发性评价——以1∶5万天水市麦积幅为例[J]. 西北地质,2022,55(2):249 − 259. [MENG Xiaojie,ZHANG Xinshe,ZENG Qingming,et al. The susceptibility evaluation of loess landslide based on weighted information value method—taking 1∶50 000 map of Maiji district of Tianshui City As an example[J]. Northwestern Geology,2022,55(2):249 − 259. (in Chinese with English abstract) MENG Xiaojie, ZHANG Xinshe, ZENG Qingming, et al. The susceptibility evaluation of loess landslide based on weighted information value method—taking 1∶50 000 map of Maiji district of Tianshui City As an example［J］. Northwestern Geology, 2022, 55（2）: 249 − 259. （in Chinese with English abstract）
[20]	孙滨,祝传兵,康晓波,等. 基于信息量模型的云南东川泥石流易发性评价[J]. 中国地质灾害与防治学报,2022,33(5):119 − 127. [SUN Bin,ZHU Chuanbing,KANG Xiaobo,et al. Susceptibility assessment of debris flows based on information model in Dongchuan,Yunnan Province[J]. The Chinese Journal of Geological Hazard and Control,2022,33(5):119 − 127. (in Chinese with English abstract) SUN Bin, ZHU Chuanbing, KANG Xiaobo, et al. Susceptibility assessment of debris flows based on information model in Dongchuan, Yunnan Province［J］. The Chinese Journal of Geological Hazard and Control, 2022, 33（5）: 119 − 127. （in Chinese with English abstract）
[21]	BREIMAN L. Bagging predictors[J]. Machine Learning,1996,24(2):123 − 140.
[22]	马啸,王念秦,李晓抗,等. 基于RF-FR模型的滑坡易发性评价——以略阳县为例[J]. 西北地质,2022,55(3):335 − 344. [MA Xiao,WANG Nianqin,LI Xiaokang,et al. Assessment of landslide susceptibility based on RF-FR model:taking Lueyang County as an example[J]. Northwestern Geology,2022,55(3):335 − 344. (in Chinese with English abstract) MA Xiao, WANG Nianqin, LI Xiaokang, et al. Assessment of landslide susceptibility based on RF-FR model: taking Lueyang County as an example［J］. Northwestern Geology, 2022, 55（3）: 335 − 344. （in Chinese with English abstract）
[23]	温鑫,范宣梅,陈兰,等. 基于信息量模型的地质灾害易发性评价:以川东南古蔺县为例[J]. 地质科技通报,2022,41(2):290 − 299. [WEN Xin,FAN Xuanmei,CHEN Lan,et al. Susceptibility assessment of geological disasters based on an information value model:a case of Gulin County in Southeast Sichuan[J]. Bulletin of Geological Science and Technology,2022,41(2):290 − 299. (in Chinese with English abstract) WEN Xin, FAN Xuanmei, CHEN Lan, et al. Susceptibility assessment of geological disasters based on an information value model: a case of Gulin County in Southeast Sichuan［J］. Bulletin of Geological Science and Technology, 2022, 41（2）: 290 − 299. （in Chinese with English abstract）
[24]	李萍,叶辉,谈树成. 基于层次分析法的永德县地质灾害易发性评价[J]. 水土保持研究,2021,28(5):394 − 399. [LI Ping,YE Hui,TAN Shucheng. Evaluation of geological hazards in Yongde County based on analytic hierarchy process[J]. Research of Soil and Water Conservation,2021,28(5):394 − 399. (in Chinese with English abstract) LI Ping, YE Hui, TAN Shucheng. Evaluation of geological hazards in Yongde County based on analytic hierarchy process［J］. Research of Soil and Water Conservation, 2021, 28（5）: 394 − 399. （in Chinese with English abstract）
[25]	孙长明,马润勇,尚合欣,等. 基于滑坡分类的西宁市滑坡易发性评价[J]. 水文地质工程地质,2020,47(3):173 − 181. [SUN Changming,MA Runyong,SHANG Hexin,et al. Landslide susceptibility assessment in Xining based on landslide classification[J]. Hydrogeology & Engineering Geology,2020,47(3):173 − 181. (in Chinese with English abstract) SUN Changming, MA Runyong, SHANG Hexin, et al. Landslide susceptibility assessment in Xining based on landslide classification［J］. Hydrogeology & Engineering Geology, 2020, 47（3）: 173 − 181. （in Chinese with English abstract）
[26]	范强,巨能攀,向喜琼,等. 基于结果验证的信息量法地质灾害易发性评价——以贵州省开阳县为例[J]. 人民长江,2015,46(15):65 − 68. [FAN Qiang,JU Nengpan,XIANG Xiqiong,et al. Geohazard susceptibility assessment by using information quantity model with result validation:a case study in Kaiyang County,Guizhou Province[J]. Yangtze River,2015,46(15):65 − 68. (in Chinese with English abstract) FAN Qiang, JU Nengpan, XIANG Xiqiong, et al. Geohazard susceptibility assessment by using information quantity model with result validation: a case study in Kaiyang County, Guizhou Province［J］. Yangtze River, 2015, 46（15）: 65 − 68. （in Chinese with English abstract）
[27]	陈前,晏鄂川,黄少平,等. 基于样本与因子优化的黄冈南部地区地质灾害易发性评价[J]. 地质科技通报,2020,39(2):175 − 185. [CHEN Qian,YAN Echuan,HUANG Shaoping,et al. Susceptibility evaluation of geological disasters in southern Huanggang based on samples and factor optimization[J]. Bulletin of Geological Science and Technology,2020,39(2):175 − 185. (in Chinese with English abstract) CHEN Qian, YAN Echuan, HUANG Shaoping, et al. Susceptibility evaluation of geological disasters in southern Huanggang based on samples and factor optimization［J］. Bulletin of Geological Science and Technology, 2020, 39（2）: 175 − 185. （in Chinese with English abstract）
[28]	刘月,王宁涛,周超,等. 基于ROC曲线与确定性系数法集成模型的三峡库区奉节县滑坡易发性评价[J]. 安全与环境工程,2020,27(4):61 − 70. [LIU Yue,WANG Ningtao,ZHOU Chao,et al. Evaluation of landslide susceptibility based on ROC and certainty factor method in Fengjie County,Three Gorges Reservoir[J]. Safety and Environmental Engineering,2020,27(4):61 − 70. (in Chinese with English abstract) LIU Yue, WANG Ningtao, ZHOU Chao, et al. Evaluation of landslide susceptibility based on ROC and certainty factor method in Fengjie County, Three Gorges Reservoir［J］. Safety and Environmental Engineering, 2020, 27（4）: 61 − 70. （in Chinese with English abstract）
[29]	WANG Liangjie,SAWADA K,MORIGUCHI S. Landslide susceptibility analysis with logistic regression model based on FCM sampling strategy[J]. Computers & Geosciences,2013,57:81 − 92.

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基于AIFFC算法的地质灾害易发性评价因子分级优化

doi: 10.16031/j.cnki.issn.1003-8035.202210048

作者简介:
陈宾：作者简介：陈宾（1977—），男，汉族，河南驻马店人，副教授，博士，主要从事地质灾害防治方面的研究工作。E-mail：403021235@qq.com

通讯作者:
张联志（1988—），男，汉族，江苏沛县人，硕士，工程师，水工环地质方向。E-mail：2149859375@qq.com

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Classification Optimization of Geological Hazard Susceptibility Evaluation Factors Based on AIFFC Algorithm

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基于AIFFC算法的地质灾害易发性评价因子分级优化

doi: 10.16031/j.cnki.issn.1003-8035.202210048

作者简介: 陈宾：作者简介：陈 宾（1977—），男，汉族，河南驻马店人，副教授，博士，主要从事地质灾害防治方面的研究工作。E-mail：403021235@qq.com

通讯作者: 张联志（1988—），男，汉族，江苏沛县人，硕士，工程师，水工环地质方向。E-mail：2149859375@qq.com

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Classification Optimization of Geological Hazard Susceptibility Evaluation Factors Based on AIFFC Algorithm

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作者简介:
陈宾：作者简介：陈宾（1977—），男，汉族，河南驻马店人，副教授，博士，主要从事地质灾害防治方面的研究工作。E-mail：403021235@qq.com

通讯作者:
张联志（1988—），男，汉族，江苏沛县人，硕士，工程师，水工环地质方向。E-mail：2149859375@qq.com