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基于GIS的隧道施工超前地质预报
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摘要
本文以“浙江诸永高速公路台州段超前地质预报与监控量测”为依托,在国家自然科学基金“裂隙岩体隧道施工地质灾害三维信息化超前预报研究”(40272117)基础上,结合白鹤隧道施工阶段的实际情况,构建了隧道三维工程地质数据库。基于COM的GIS组件ArcObjects9.2进行二次开发,以Visual Basic作为开发平台,进行系统集成,开发隧道施工超前地质预报系统。在开发的平台上,对隧道实体、地层、节理裂隙、钻孔数据进行了三维实体建模,进行三维可视化模拟。将不连续面三维网络模拟与GIS结合,在3DGIS环境下进行不连续面三维网络模拟。将数据挖掘理论引入到超前地质预报系统中,针对三维工程地质数据库进行知识发现和数据挖掘,从空间和时间两个角度,利用开挖揭露的地质信息对掌子前方可能出现的塌方等灾害进行超前地质预报。空间角度上,利用粗糙集理论的属性约简,判断围岩稳定性影响因素,并进行权系数计算。利用人工神经网络、可拓学理论进行对隧道围岩的稳定性、可能出现的塌方等灾害进行预测,开拓了根据开挖揭露的地质信息进行非线性超前地质预报的方法。时间角度上,将BP神经网络与ARMA模型相结合,从趋势性和随机性两方面,对围岩压力等监测数据进行趋势提取和预测。在GIS平台上将超前地质预报结果三维可视化输出,可以利用GIS强大的查询和空间分析功能,便于结果的综合查询分析。
With the rapid development of national economic, projects of hydraulic engineering and traffic engineering is flourishing, and so is the tunnel construction, which is always confined mainly by various kinds of geological disasters. In order to ensure the normal operation of tunnel construction, it plays a decisive role to do geological prediction in the process of tunnel information-based construction.
     Although more and more attention are paid to geological prediction ahead of working face during tunnel construction at home and broad, the prediction level is not high and the method is not mature. The key reason of this situation is that the information of most prediction method is from investigations before construction, or simply depends on geophysics explorer means and ignores the geological information disclosed during construction. How to predict geological situation ahead of working face using the geological information disclosed during construction, is the core of information construction. In this thesis, this thought is through out the whole research.
     Relying on Geological Prediction Ahead of Working Face during Tunnel Construction of Zhuyong Highway (Taizhou Part) in Zhejiang Province and National Natural Science Foundation of P. R. China (40272117), some research is carried on in this thesis. Baihe tunnel, a part of Zhuyong highway in Zhejiang province, locates in Xianju County, the physiognomy features of which are mid-low hill controlled by cathaysian and neocathaysian structural system. The dominant rock mass is weakly or slightly weathered tuff. Joints and cracks are well developed, mainly trending N.W and N.N.E, widely opened, weak cementation, with a result of collapse and water inrushing.
     In this thesis, it is introduced the standard of layer division and property structure of all layers in the 3D geological information database based on GeoDataBase. 3D geological information database of Baihe tunnel is built, which consists of graphics library including contour, drilling hole, stratum information, joints and cracks, and monitoring instruments position, etc. and property databases, such as database of joints and cracks, monitoring database. And geological information disclosed in the process of tunnel excavation is spatial informationized, which provides a database support to do data mining and geological prediction ahead of working face.
     Through a deep understanding of the 3D GIS model, the 3D modeling approach working for geological prediction ahead of working face during tunnel construction is developed. The way of building 3D tunnel model based on GIS, and conversion between geodetic coordinates and construction stake number are introduced as well as 3D model of Baihe tunnel is successfully built. Besides, the way to express and construct drill data is suggested, and then the 3D stratum model of Baihe tunnel is built based on the drill data and Kriging interpolation. Finally, 3D display of Baihe tunnel as well as simulation and analysis come to fulfillment, after the construction of 3D physical model and joints and cracks model.
     Based on the GIS platform, mining useful knowledge from the previous 3D GeoDataBase, sufficiently analyzing the engineering information and geological data disclosed during construction, the intellectualized prediction model of 3D information in advance of geological disaster during construction is built. The general technical route of the study is informationized construction that is forecasting the condition of undisclosed part and modified the original design in real time according to the information of disclosed part. Thus, it provides the basis to modify support scheme, excavation method and working sequence, is a technical support and protection to safe construction reducing geological disaster.
     Introduce data mining theory to the system of geological prediction in advance to do knowledge finding and data mining in 3D engineering geological database and predict in advance the disaster possibly existing ahead of tunnel working face in the view of time and space using the disclosed geological information. From the standpoint of space, draw information of dominant instruction surface after analyzing the joint data from excavation process using 3D net work numerical modeling technique for random discontinuities of rock mass and fuzzy clustering analysis; build decision information table of tunnel geo-disaster using rough set theory; do data mining and knowledge finding in 3D engineering geological database adopting the function of attribution reduction in rough set theory; judge the influence factors to rock mass stability as well as the weight coefficient computing; and predict the possible disaster and stability of rock mass applying artificial net work and extenics theory. From the standpoint of time, combining the BP net work and ARMA model, do trend abstract and prediction of the monitoring data of rock mass pressure in both aspects of trendy and random. 3D visual output of prediction result on the platform of GIS, which is powerful in query and spatial analysis, is convenient to query and analysis of result.
     The main algorithms adopted in this thesis are rough set theory, fuzzy clustering analysis, artificial neural network, and Extenics in data mining theory. Based on the Arc Objects 9.2—GIS component of COM, with the development platform of Visual Basic, the system of tunnel construction forecasts in advance is developed on the basis of GIS. The system comprises some modules such as the management of spatial database, the construction of 3D model, the simulation of 3D net, spatial overlay analysis, spatial query, geological forecast, etc. what the system can do are data inputting, inquiring and managing of drilling data, joints statistic data and monitoring data; 3D model building of drilling hole, stratum and tunnel; 3D net simulation of discontinuities based on GIS, as well as computing RQD, abstracting dominant surface; spatial analysis and inquiring characterized by click inquiry and location query by special property; geological prediction ahead of working face by both approach of ANN and extenics; 3D rock classification, and analyzing the influence basin of shuttered zone applying the 3D analysis of the buffer zone in GIS; and forecasting time series of monitoring data by both approaches of BP network and BP-ARMA.
     Adopting the way and the system mentioned in this thesis, geological prediction ahead of working face is pursued in typical part of Baihe tunnel, and some conclusions can be obtained as below:
     1. The main origins of collapse and water inrushing in Baihe tunnel are its considerable length, developed joints and cracks, widely opened structure surface and its weak cohesion.
     2. By the attribute reduction in rough set, to analyze the affect factor of the stability of rock mass in Baihe tunnel, the result suggests that RQD, the angel between the tunnel axes and the controlling structural plane, the type of structure plane, the length of structure plane, etc. influenced the stability by different level, especially the type of structure plane as well as the character of groundwater.
     3. Comparing the results of stability of rock mass predicting from extenics and BP network, it can be found that these two prediction results are similar and accordant actual situation, which indicate that nonlinear theory is effect in dealing with geological prediction ahead in tunnel construction
     4. Time series analysis of rock mass pressure using BP-ARMA model indicate that this model can be used to analysis and predict monitoring data of rock mass pressure. Trend term extracted by BP reflects the overall trend of rock mass pressure, and ARMA reflects the random induced by rock mass structure and excavation progress. Compared with BP prediction, this method has higher accuracy.
     5. The prediction result of rock mass stability indicate that geological prediction ahead in tunnel construction using geological information disclosed in excavation is scientific and feasible. The research method is innovative and has application and promotion value.
引文
[1].中国科学院地质研究所.军都山隧道快速施工超前地质预报指南[M].北京:中国铁道出版社, 1990.
    [2].邓雄业,李明高.靠椅山隧道大塌方的处理[J].西部探矿工程, 2000(4): 91-93.
    [3].余良济.大瑶山隧道DK1995+703治水的地质分析[J].铁道勘测与设计, 1993(3): 9-12.
    [4].谢勇谋.国道317线鹤鸽山隧道施工地质预报研究[D].成都理工大学硕士学位论文, 2004.
    [5].郭伟伟.隧道施工超前地质预测预报综合技术方法研究[D].西南交通大学硕士学位论文, 2006.
    [6].何发亮,李苍松,陈成宗.隧道地质超前预报[M].成都:西南交通大学出版社, 2006.
    [7].徐则民,黄润秋.深埋特长隧道及其施工地质灾害[M].成都:西南交通大学出版社, 2000.
    [8].张志龙.越岭长大公路隧道地质预报中的关键技术问题研究[D].成都理工大学博士学位论文, 2006.
    [9].李术才,李树忱,张庆松,等.岩溶裂隙水与不良地质情况超前预报研究[J].岩石力学与工程学报, 2007, 26(2): 217-225.
    [10].毛建安.秦岭特长隧道施工地质超前预报技术的应用[J].现代隧道技术, 1998(04).
    [11].陈建峰.隧道施工地质超前预报技术比较[J].地下空间, 2003, 23(01): 5-8.
    [12].谢勇谋.国道317线鹧鸪山隧道施工地质预报研究[D].成都理工大学硕士学位论文, 2004.
    [13].龚固培.超前地质预报在北京市八达岭高速公路隧道施工中的应用[J].现代隧道技术, 2000, 2000(05): 38-41.
    [14].何发亮,李苍松.隧道施工期地质超前预报技术的发展[J].现代隧道技术, 2001, 38(3): 12-15.
    [15].刘志刚,刘秀峰.断层参数预测法预报隧道断层[J].岩石力学与工程学报, 2003, 22(9): 1547-1550.
    [16].Cremer F, Jong De W, Schutte K. Fusion of polarimetric infrared features and GPR features for landmine detection[C]. The 2nd International Workshop on Advanced Ground Penetrating Radar (IWAGPR). Delft,Netherlands: 2003.
    [17].曲海锋,刘志刚,朱合华.隧道信息化施工中综合超前地质预报技术[J].岩石力学与工程学报, 2006, 25(6): 1246-1251.
    [18].Casas A, Lazaro R, Vilas M, et al. Detecting karstic cavities with ground penetrating radar at different geological environments in Spain[C].Proceedings of the 6th International Conference on Ground Penetrating Radar. Sendai,Japan: 1996.
    [19].夏照华.地质雷达在探测地下溶洞中的应用[J].西部探矿工程, 2005(1): 91-92.
    [20].Foessel A, Apostolopoulos D, Whittaker W L. Radar sensor for an autonomous Antarctic explorer[C].Mobile Robots XIII and Intelligent Transportation Systems. Proc. Spie.
    [21].赵永贵,刘浩,孙宇,等.隧道地质超前预报研究进展[J].地球物理学进展, 2003, 18(3): 460-464.
    [22].陈晓明,伍毅敏,朱学坤.地质雷达在浅埋隧道覆盖层地质扫描中的应用[J].公路, 2008(05).
    [23].姜汶泉,刘亚玲,汪林平.地质雷达在公路隧道超前地质预报中的应用[J].地下空间与工程学报, 2008, 4(4): 649-652.
    [24].吴国晓.锦屏二级水电站辅助洞超前地质预报技术研究[D].河海大学硕士学位论文, 2007.
    [25].张晓.齐岳山隧道岩溶超前预报及综合集成系统研究[D].北京交通大学硕士学位论文, 2008.
    [26].肖书安,吴世林.复杂地质条件下的隧道地质超前探测技术[J].工程地球物理学报, 2004, 1(2): 159-165.
    [27].何刚,沙椿,丁陈奉,等. TSP-203系统数据采集的改进方案[J].地球物理学进展, 2006(04).
    [28].李志祥,何振起,刘国伍. TSP-203在大支坪隧道超前预报中的应用[J].地球物理学进展, 2005(02).
    [29].戴前伟,何刚,冯德山. TSP-203在隧道超前预报中的应用[J].地球物理学进展, 2005(02).
    [30].温树林,吴世林. TSP203在云南元磨高速公路隧道超前地质预报中的应用[J].地球物理学进展, 2003(03).
    [31].邓尤东.超前地质预报在乌鞘岭特长隧道中的应用[J].岩石力学与工程学报, 2004, 23(S2): 5140-5146.
    [32].钟世航,曹大明.隧道中用陆地声纳法在开挖的岩面或衬砌表面测围岩松弛带深度[J].岩石力学与工程学报, 2005, 24(10): 1722-1727.
    [33].钟世航.陆地声纳法及其应用效果[J].物探与化探, 1997(03).
    [34].李彦军.红外探测技术在隧道工程中的适用性分析[J].铁道勘察, 2008, 24(2): 45-48.
    [35].李术才,李树忱,张庆松,等.岩溶裂隙水与不良地质情况超前预报研究[J].岩石力学与工程学报, 2007, 26(2): 217-225.
    [36].王鹰,陈强,魏有仪,等.红外探测技术在圆梁山隧道突水预报中的应用[J].岩石力学与工程学报, 2003, 22(5): 855-857.
    [37].杜立志.隧道施工地质地震波法超前探测技术研究[D].吉林大学博士学位论文, 2008.
    [38].朱劲,李天斌,李永林,等. Beam超前地质预报技术在铜锣山隧道中的应用[J].工程地质学报, 2007, 15(2): 258-262.
    [39].刘玉山,陈建平. TRT技术在乌池坝隧道超前预报中的应用[J].铁道建筑, 2008: 59-61.
    [40].陈剑平,肖树芳,王清.随机不连续面三维网络计算机模拟原理[M].长春:东北师范大学出版社, 1995.
    [41].陈剑平.岩体随机不连续面三维网络数值模拟技术[J].岩土工程学报, 2001, 23(4): 397-402.
    [42].王良奎.应用三维节理网络模拟技术进行隧道块体危岩超前地质预报[J].世界地质, 1998(04).
    [43].Petronio L, Poletto F, Schleifer A. Interface prediction ahead of the excavation front by the tunnel-seismic-while-drilling (TSWD) method[J]. GEOPHYSICS, 2007, 72(4): G39-G44.
    [44].叶英.岩溶隧道施工超前地质预报方法研究[D].北京交通大学博士学位论文, 2006.
    [45].黄栋良,吴湘滨,罗伟奇,等.断层错动机制解在雪峰山隧道地质超前预报中的应用[J].铁道建筑, 2007(10).
    [46].司建涛,贾留杰.综合超前地质预报方法在宜万铁路云雾山隧道施工中的应用[J].地质灾害与环境保护, 2008, 19(1): 102-104.
    [47].闫超平,杨家松,陈寿根.综合超前地质预报在锦屏辅助洞F6断层中的应用[J].公路隧道, 2008(1): 34-38.
    [48].王洪勇.综合超前地质预报在圆梁山隧道中的应用[J].现代隧道技术, 2004, 41(3): 55-61.
    [49].王青海,李晓红,夏彬伟,等.超前预测预报在笔架山隧道施工中的应用[J].岩土力学, 2005, 26(6): 951-954.
    [50].张旭东.歌乐山隧道与重庆轻轨大坪隧道的信息化施工[D].西南交通大学硕士学位论文, 2005.
    [51].Yoo C, Kim J M. Tunneling performance prediction using an integrated GIS and neural network[J]. COMPUTERS AND GEOTECHNICS, 2007, 34(1): 19-30.
    [52].Li X H, Wang X F, Kang Y, et al. Artificial neural network for prediction of rockburst in deep-buried long tunnel[J]. ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS, 2005,3498: 983-986.
    [53].Alimoradi A, Moradzadeh A, Naderi R, et al. Prediction of geological hazardous zones in front of a tunnel face using TSP-203 and artificial neural networks[J]. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2008, 23(6): 711-717.
    [54].朱合华,姜勇,夏才初,等.复杂地质条件下隧道信息化施工综合技术研究[J].岩石力学与工程学报, 2002, 21(S2): 2548-2553.
    [55].夏彬伟.公路隧道施工地质灾害预测预报研究[D].重庆大学硕士学位论文, 2006.
    [56].许勇.隧道超前地质预报计算机辅助系统初步开发[D].成都理工大学硕士学位论文, 2008.
    [57].王浩.地下工程监测中的数据分析和信息管理、预测预报系统[D].中国科学院研究生院(武汉岩土力学研究所)2007.
    [58].邬伦,刘瑜.地理信息系统--原理、方法和应用[M].北京:科学出版社, 2004.
    [59].李青元,曹代勇,高文泰.基于体划分的二维矢量结构GIS拓扑关系[M].北京:测绘出版社, 1996.
    [60].夏炎.三维矢量结构地质模型及其微机可视化图形显示系统研究[D].北京:中国矿业大学博士学位论文, 2000.
    [61].李清泉.基于混合数据结构的三维GIS数据模型与空间分析研究[D].武汉:武汉测绘科技大学博士学位论文, 1998.
    [62].Lee Y. A Methodological Study of the Application of the maximum Entropy Estimator to spatial interpolation[J]. Journal of Geographic Information and Decision Analysis, 1998, 2(2): 265-276.
    [63].Kavouras M, Masry S. An Information System for Geosciences: Design Considerations[C].Proc. of 8th International Symposium on Computer Assisted Cartography. Baltimore: 1987.
    [64].李德仁,李清泉.一种三维GIS混合数据结构研究[J].测绘学报, 1997, 26(2): 128-133.
    [65].Bistacchi A, Massironi M, Dal Piaz G V, et al. 3D fold and fault reconstruction with an uncertainty model: An example from an Alpine tunnel case study[J]. COMPUTERS & GEOSCIENCES, 2008, 34(4): 351-372.
    [66].Apel M. From 3d geomodelling systems towards 3d geoscience information systems: Data model, query functionality, and data management[J]. COMPUTERS & GEOSCIENCES, 2006, 32(2): 222-229.
    [67].Chang Y S, Park H D. Development of a web-based Geographic Information System for the management of borehole and geological data[J]. COMPUTERS & GEOSCIENCES, 2004, 30(8): 887-897.
    [68].Kaufmann O, Martin T. 3D geological modelling from boreholes, cross-sections and geological maps, application over former natural gas storages in coal mines[J]. COMPUTERS & GEOSCIENCES, 2008, 34(3): 278-290.
    [69].Tonini A, Guastaldi E, Massa G, et al. 3D geo-mapping based on surface data for preliminary study of underground works: A case study in Val Topina (Central Italy)[J]. ENGINEERING GEOLOGY, 2008, 99(1-2): 61-69.
    [70].Tonini A, Guastaldi E, Meccheri M. Three-dimensional reconstruction of the Carrara Syncline (Apuane Alps, Italy): An approach to reconstruct and control a geological model using only field survey data[J]. Computers & Geosciences, 2009, 35(1): 33-48.
    [71].Choi Y, Yoon S, Park H. Tunneling Analyst: A 3D GIS extension for rock mass classification and fault zone analysis in tunneling[J]. Computers & Geosciences, , In Press, Corrected Proof.
    [72].朱合华,李晓军.数字地下空间与工程[J].岩石力学与工程学报, 2007, 26(11): 2277-2288.
    [73].朱合华,王长虹,李晓军,等.数字地下空间与工程数据库模型建设[J].岩土工程学报, 2007, 29(7): 1098-1102.
    [74].钟登华,李明超,王刚.大型水电工程地质信息三维可视化分析理论与应用[J].天津大学学报:自然科学与工程技术版, 2004, 37(12): 1046-1052.
    [75].钟登华,李明超,王刚,等.基于三维地层模型的岩体质量可视化分级[J].岩土力学, 2005, 26(1): 11-16.
    [76].钟登华,李明超,杨建敏.复杂工程岩体结构三维可视化构造及其应用[J].岩石力学与工程学报, 2005, 24(4): 575-580.
    [77].钟登华,宋洋.基于GIS的水利水电工程三维可视化图形仿真方法与应用[J].工程图学学报, 2004, 25(1): 52-58.
    [78].钟登华,王刚,李明超,等.三维地质模型信息可视化与工程应用[J].天津大学学报:自然科学与工程技术版, 2005, 38(1): 36-40.
    [79].何满潮,李学元,刘斌,等.工程岩体三维构模中钻孔数据处理方法[J].岩石力学与工程学报, 2005, 24(11): 1821-1826.
    [80].何满潮,李学元,刘斌,等.非层状岩体三维可视化构模技术研究[J].岩石力学与工程学报, 2005, 24(5): 774-779.
    [81].何满潮,李学元,刘斌,等.侵入型岩体三维可视化构模技术研究[J].煤田地质与勘探, 2004, 32(4): 29-32.
    [82].徐能雄,何满潮.层状岩体三维构模方法与空间数据模型[J].中国矿业大学学报, 2004, 33(1): 103-108.
    [83].徐能雄,何满潮.褶皱岩体三维可视化构模技术及其工程应用[J].岩土工程学报, 2003, 25(4): 418-421.
    [84].徐能雄,何满潮,景海河.非连续型非褶皱岩体三维可视化构模技术及应用[J].岩石力学与工程学报, 2004, 23(15): 2534-2538.
    [85].徐能雄,何满潮,景海河.岩体结构三维构模技术及其可视化系统研制[J].岩土工程学报, 2004, 26(3): 373-377.
    [86].柴贺军,黄地龙.大型矿山岩土工程可视化模型与应用[J].岩石力学与工程学报, 2005, 24(14): 2526-2530.
    [87].柴贺军,黄地龙,等.岩体结构三维可视化及其工程应用研究[J].岩土工程学报, 2001, 23(2): 217-220.
    [88].高明忠,谢和平,李洪,等.基于GIS的地层剖面图形生成技术[J].岩土力学, 2006, 27(10): 1791-1794.
    [89].周翠英,陈恒,刘祚秋,等.重大工程地下环境信息系统的设计与实现[J].岩土力学, 2004, 25(9): 1469-1474.
    [90].周翠英,董立国,陈恒,等.重大工程三维地层分析的功能设计与实现[J].中山大学学报:自然科学版, 2006, 45(4): 39-43.
    [91].周翠英,赵旭升,陈恒,等.三维地层模型及可视化技术研究[J].中山大学学报:自然科学版, 2003, 42(4): 21-23.
    [92].朱良峰,潘信.地质断层三维构模技术研究[J].岩土力学, 2008, 29(1): 274-278.
    [93].朱良峰,吴信才,潘信.三维地层模型误差修正机制及其实现技术[J].岩土力学, 2006, 27(2): 268-271.
    [94].屈红刚,潘懋,吕晓俭,等.城市三维地质信息管理与服务系统设计与开发[J].北京大学学报(自然科学版), 2008, 44(05).
    [95].李邵军,冯夏庭,王威,等.基于地层信息的三维洞室可视化仿真技术研究[J].岩土力学, 2008, 29(1): 235-239.
    [96].李邵军,冯夏庭,王威,等.岩土工程中基于栅格的三维地层建模及空间分析[J].岩石力学与工程学报, 2007, 26(3): 532-537.
    [97].庞大鹏.诸永高速公路隧道监控量测数据处理及地质超前预报方法研究[D].吉林大学硕士学位论文, 2008.
    [98].浙江省交通规划设计研究院,浙江省浙南综合工程勘察院.诸永高速公路台州段第2合同两阶段施工图设计工程地质勘查报告[R].杭州: , 2004.
    [99].浙江省交通规划设计研究院,浙江省浙南综合工程勘察院.诸永高速公路台州段第3合同两阶段施工图设计工程地质勘查报告[R].杭州: , 2004.
    [100].张国柱.大陈隧道围岩变形预测研究[D].吉林大学硕士学位论文, 2008.
    [101].邱道宏.括苍山高速公路隧道岩爆非线性预测研究[D].吉林大学博士学位论文, 2008.
    [102].王坛华.基于三维网络模拟技术的裂隙网络水力研究及隧道涌水非线性预测[D].吉林大学博士学位论文, 2008.
    [103].周卫滨.苍岭隧道岩爆预测和防治研究[D].杭州:浙江大学硕士学位论文, 2005.
    [104].邱道宏.括苍山高速公路隧道岩爆非线性预测研究[D].吉林大学2008.
    [105].张秉鹤.括苍山特长公路隧道相对浅埋洞段岩爆机理及防治措施研究[D].吉林大学硕士学位论文, 2007.
    [106].宋杨,万幼川.一种新型空间数据模型GeoDatabase[J].测绘通报, 2004(11): 31-33.
    [107].张佐帮,尚颖娟.基于GeoDatabase的面向对象空间数据库设计[J].地理空间信息, 2005, 3(2): 33-35.
    [108].李国标,庄雅平,王珏华.面向对象的GIS数据模型—地理数据库[J].测绘通报, 2001(6): 37-39.
    [109].Bode T, Breunig M, Cremers A B. First Experiences with GEOSTORE, an Information System for Geologically Defined Geometries[C].Proceedings IGIS. 1994.
    [110].王润怀.矿山地质对象三维数据模型研究[D].西南交通大学博士学位论文, 2007.
    [111].谭仁春. GIS中三维空间数据模型的集成与应用[J].测绘工程, 2005, 14(1): 63-66.
    [112].赵永军,李汉林,王海起. GIS三维空间数据模型的发展与集成[J].石油大学学报(自然科学版), 2001, 25(5): 24-28.
    [113].杨东来,张永波,王新春,等.地质体三维建模方法与技术指南[M].北京:地质出版社, 2007.
    [114].史文中,吴立新,李清泉,等.三维空间信息系统模型与算法[M].北京:电子工业出版社, 2007.
    [115].陈剑平,石丙飞,王清.工程岩体随机结构面优势方向的表示法初探[J].岩石力学与工程学报, 2005, 24(2): 241-245.
    [116].石丙飞.广州科学城林语山庄人工高边坡稳定性评价及设计研究[D].长春:吉林大学博士学位论文, 2006.
    [117].赵振宇,徐用懋.模糊理论和神经网络的基础与应用[M].北京:清华大学出版社, 1996.
    [118].张文修,吴伟志,梁吉业, et al.粗糙集理论与方法[M].北京:科学出版社, 2001.
    [119].高新波.模糊聚类分析及其应用[M].西安:西安电子科技大学出版社, 2004.
    [120].刘丹,李启彬.秦岭特长隧道涌水量的预测研究[J].煤田地质与勘探, 2005, 33(1): 41-44.
    [121].李志勇,邹静蓉,谢强.红层路堑边坡工程地质及系统聚类分析研究[J].工程勘察, 2002(02).
    [122].范大凯,吴健平.基于MapX的GIS应用开发实例[J]. 2001.
    [123].诸云强,宫辉力,赵文吉,等.基于组件技术的地理信息系统二次开发——以地下水资源空间分析系统为例[J].地理与地理信息科学, 2003, 19(1): 16-19.
    [124].徐爱萍,徐武平.组件技术与ComGIS[J].测绘信息与工程, 2001(2): 32-34.
    [125].李胜,王强.组件GIS在国土专题信息管理系统中的应用[J].测绘通报, 2002(8): 46-48.
    [126].宋关福,钟耳顺.组件式地理信息系统研究与开发[J].中国图象图形学报, 1998, 3(4): 313-317.
    [127].唐超,冯珊,周凯波.基于组件技术的开放式地理信息系统结构[J].华中理工大学学报, 2000(07).
    [128].郝平,李瑞麟,应时彦,等.组件式地理信息系统技术[J].浙江工业大学学报, 2001, 29(3).
    [129].刘丹,郑坤,彭黎辉.组件技术在GIS系统中的研究与应用[J].地球科学——中国地质大学学报, 2002, 27(3): 263-266.
    [130].Zhong E, Song G, Wang E. Development of a Components GIS based on Applications[C].Proceedings of IEAS '97 & IWGIS '97. Beijing China.
    [131].闪四清,陈茵,程雁.数据挖掘——概念、模型、方法和算法[M].北京:清华大学出版社, 2003.
    [132].王光宏,蒋平.数据挖掘综述[J].同济大学学报:自然科学版, 2004, 32(2): 246-252.
    [133].钟晓,马少平,张钹.数据挖掘综述[J].模式识别与人工智能, 2001, 14(1): 48-55.
    [134].Pawlak Z. An inquiry into anatomy of conflicts[J]. Journal of Information Science, 1998(109): 65-78.
    [135].Slowinski R. Intelligent Decision Support-handbook of Applications and Advances of the Rough Sets Theory[C]. Dordtrcht Kluwer Academic Publishers, 1992.
    [136].Pawlak Z. Rough Classification[J]. Int. J. Man-Machine Studies, 1984(20): 469-483.
    [137].Pawlak Z. Rough set approach to knowledge-based decision support[J]. European Journal of Operational research, 1997, 99(23): 48-57.
    [138].Pawlak Z. Rough set theory and its applications to data analysis[J]. Cybernetics and Systems: An International Journal, 1998(29): 661-688.
    [139].Pawlak Z. Rough Sets[J]. Intemational Journal of Computer and Information Sciences, 1982, 11(5): 341-356.
    [140].Pawlak Z. Rough sets and fuzzy sets[J]. fuzzy Sets and Systems, 1985(17): 99-102.
    [141].Pawlak Z. Rough Set-theoretical Aspects of Reasoning about Data[M]. Dordrecht Kluwer Academic Publishers, 1991.
    [142].Pawlak Z. Vagueness and uncertainty: A rough set perspective[J]. Computational Intelligence, 1995(11): 227-232.
    [143].Liu J, Hu Q, Yu D. A weighted rough set based method developed for class imbalance learning[J]. INFORMATION SCIENCES, 2008, 178(4): 1235-1256.
    [144].阙金声.三峡工程涪陵区水库塌岸非线性预测研究[D].长春:吉林大学博士学位论文, 2007.
    [145].张建军,张静波.一种新的基于粗糙集理念的决策表离散化算法[J].西安电子科技大学学报(自然科学版), 2004, 31(3): 469-472.
    [146].国家技术监督局,中华人民共和国建设部.工程岩体分级标准[S]. 1995.
    [147].张雪峰,田晓东,张庆灵.基于粗糙集理论和层次分析的数据约简[J].东北大学学报(自然科学版), 2008, 29(1): 21-24.
    [148].米据生,吴伟志,张文修.基于变精度粗糙集理论的知识约简方法[J].系统工程理论与实践, 2004(1): 76-82.
    [149].菅利荣,达庆利,陈伟达.基于变精度粗糙集的分层知识粒度[J].管理工程学报, 2004(2): 60-63.
    [150].张建军,张静波.一种新的基于粗糙集理念的决策表离散化算法[J].西安电子科技大学学报(自然科学版), 2004, 31(3): 469-472.
    [151].李钢,张雪婷.基于相似关系粗糙集的分解[J].计算机工程与应用, 2004(2): 85-87.
    [152].陈万里,程家兴,张持健.基于相容关系的粗糙集理论的推广[J].计算机工程与应用, 2004(4): 26-28.
    [153].连玉平,史战红.基于粗糙集属性重要度的TOPSIS方法[J].数学教学研究, 2008(2): 51-52.
    [154].Mcculloch W S, Pitts W. A logical calculus of the ideas immanent in nervous activity[J]. Bulletin of Mathematical Biophysics, 1943(5): 115-133.
    [155].Hopfield J J. Neural Networks and Physical Systems with Emergent Collective Computational Abilitie[C].Proceedings of the National Academy of Sciences of the United States of America. 1982.
    [156].Rumelhart D E, Mcclelland J L. Parallel Distributed Processing: Explorations in the Microstructure of Cognition[M]. Cambridge, MA: MIT Press, 1986.
    [157].徐佩华.基于人工神经网络方法的锦屏一级水电站枢纽区高边坡稳定性分区研究[D].长春:吉林大学博士学位论文, 2006.
    [158].Kitahara M, Achenbach J D, Guo Q C. Neural network for crack dapth determination from ultrasonic back-scattering data[J]. Review of Progress in Quantitative Nondestructive Evaluation, 1992(11): 701-708.
    [159].戴琳.可拓学在工程质量评定中应用的研究[J].南京师范大学学报(工程技术版), 2002, 2(3): 21-25.
    [160].王小丹.荒漠化评价的物元可拓识别方法[J].山地学报, 2002, 20(5): 636-640.
    [161].王锦国,周志芳,袁永生.可拓评价方法在环境质量综合评价中的应用[J].河海大学学报, 2002, 30(1): 15-18.
    [162].胡宝清.可拓评价方法在围岩稳定性分类中的应用[J].水利学报, 2002, 2: 66-70.
    [163].周汉民.岩体质量的可拓学评价方法在边坡工程中的应用[J].矿业快报, 2003, 12: 13-15.
    [164].连建发,慎乃齐,张杰坤.基于可拓方法的地下工程围岩评价研究[J].岩石力学与工程学报, 2004, 23(9): 1450-1453.
    [165].原国红,陈剑平,马琳.可拓评判方法在岩体质量分类中的应用[J].岩石力学与工程学报, 2005, 24(9): 1539-1544.
    [166].贾超,肖树芳,刘宁.可拓学理论在洞室岩体质量评价中的应用[J].岩石力学与工程学报, 2003, 22(5): 751-756.
    [167].蔡文.物元模型及应用[M].北京:科学技术文献出版社, 1994.
    [168].蔡文,杨春燕,林伟初.可拓工程方法[M].北京:科学技术出版, 1997.
    [169].蔡文,杨春燕,何斌.可拓逻辑初步[M].北京:科学技术出版社, 1997.
    [170].杨春燕,蔡文.可拓工程研究[J].中国工程科学, 2000, 2(12): 90-96.
    [171].郭开仲.关联函数的形式[J].智囊与物元分析, 1985(1).
    [172].邓丽丽.可拓方法在采场稳定性评价中的应用[J].中国矿业, 1998, 7(4): 35-38.
    [173].杨春燕.事元及其应用[J].系统工程理论与实践, 1998, 18(2): 80-86.
    [174].王亮.岩体边坡稳定性的可拓学分析[J].河北冶金, 1999, 1: 21-23.
    [175].杨庆华,陈春光.洪灾强度的可拓学分析[J].城市道桥与防洪, 2004, 2: 46-49.
    [176].安鹏程.街下2号偏压连拱隧道围岩压力分析与现场监控量测[D].吉林大学硕士学位论文, 2008.
    [177].杨叔子,吴雅,轩建平.时间序列分析的工程应用(第二版)[M].武汉:华中科技大学出版社, 2007.
    [178].杨叔子,吴雅,王治藩.时间序列分析的工程应用[M].武汉:华中理工大学出版社, 1991.
    [179].娄峰.时间序列分析在隧道位移监测中的应用[D].大连理工大学硕士学位论文, 2002.
    [180].王铁生.地下隧洞测控技术与地表沉降动态监控模型的研究[D].河海大学2003.
    [181].贾澎涛,何华灿,刘丽,等.时间序列数据挖掘综述[J].计算机应用研究, 2007, 24(11): 15-18.
    [182].梁循.数据挖掘算法与应用[M].北京:北京大学出版社, 2006.
    [183].Box G E P, Jenkins G M. Time Series Analysis: Forecasting and Control[M]. San Francisco: Holden-Day, 1970.
    [184].Box G E P, Jenkins G M, Reinsel G C. Time Series Analysis: Forecasting and Control[M]. New Jersey: Prentice-Hall, Englewood Cliffs, 1994.
    [185].Akaike H. A new look at the statistical model identification[J]. IEEE Trans. Auto Control, 1974, AC-19: 716-723.
    [186].Schwarz G. Estimationg the dimension of a model[J]. Ann.Statistics , 1978, 6: 461-464.
    [187].赵振宇,徐用懋.模糊理论和神经网络的基础与应用[M].北京:清华大学出版社, 1996.
    [188].吴今培.现代数据分析[M].北京:机械工业出版社, 2006.

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