西藏喜马拉雅山地区冰湖溃决非线性预测研究
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摘要
近年来,由于受全球气候变化的影响,喜马拉雅山地区冰湖灾害日益突出,可能发生溃决的冰湖数量不断增加,给当地人们造成人员伤亡和大量的财产损失,严重制约着西藏社会经济发展。同时随着国家西部大开发战略实施,各项基础设施的建设逐步完善,冰湖的危害程度越来越严重。因此针对冰湖溃决的预测研究势在必行。
论文通过对研究区的地质环境调查及相关资料研究,阐述了喜马拉雅山地区的自然地理、地质概况,分析了喜马拉雅山地区的工程地质环境特征。在综合分析前人的研究成果和现场调查资料基础上,提出了研究区冰湖溃决的发生条件和冰湖溃决模式,用量化指标对冰湖溃决进行了预测。
在全球气温升高的大环境下,研究区冰湖溃决灾害日益严重,具有分布范围广、危害大,且尚没有一套行之有效的方法。根据冰湖溃决具有高度的非线性和不确定性的特点,论文采用了基于支持向量机-可拓学理论的非线性冰湖溃决预测模型,对研究区的冰湖溃决的可能性进行预测。预测结构表明,基于非线性理论的冰湖溃决预测模型可以较为客观的对冰湖危险性进行预测,可为喜马拉雅山地区冰湖溃决灾害防治提供科学依据。
论文通过对喜马拉雅山地区冰湖系统的研究,获得以下成果和结论:
1.以研究区已发生的冰湖溃决调查资料为基础,分析研究冰湖溃决灾害的发生条件,其中包括气候背景,汇水条件、地形地貌条件、水文条件、地震等方面;从气候背景组合形式和终碛垄受破坏形式两方面对冰湖溃决模式进行了分类,前者分为4大类、17种模式,后者可分为翻浪涌坝型、渗透融沉溃坝型,旁沟侵蚀型三种模式,后者三种模式间并没有明显的界限,在一定条件可能还会发生转换。
2.在分析冰湖溃决影响因素的基础上,构建了以母冰川-冰湖-终碛垄为主线的冰湖溃决预测指标体系,并采用补给冰川面积、冰川积雪区平均纵坡、冰舌坡度、冰舌前端距冰湖距离、冰川裂隙发育情况、冰湖面积、两岸崩塌发育情况、背水坡度,冰川坝顶宽度、受旁沟冲刷程度、水热组合等11个因子作为冰湖溃决预测的评判指标,并进行了量化。
3.冰湖溃决危险性的分类问题是对其特性与各影响因素之间的函数关系的逼近问题,也即模式识别问题。支持向量机在非线性系统方面具有避免局部极小点、过学习等缺陷的优势,本文以支持向量机的基本原理及其算法为基础,建立了冰湖溃决危险性分类模型,并把此模型成功地应用于喜马拉雅山地区的25个冰湖实例的溃决预测中。
4.在对基于支持向量机理论的预测模型进行检验时发现,学习样本通过训练所得到学习正确率90%以上的模型不止一个,这说明,通过学习样本法进行训练所得模型的正确性是不够可靠的,因此选取学习样本中的9个对模型再次进行检验,测试正确率达90%以上的仅剩下一个。据此,确定其为可靠的基于支持向量机算法的冰湖溃决预测模型。
5.在用可拓评判法对冰湖溃决进行预测时,逼真的权重是优化评价结果的关键因素。权重的分配是否合理,直接影响到评估的科学性。本文提出一种基于粗糙集理论的权重确定求法。利用粗糙集理论中的属性重要度的概念,求出各评价指标的权重系数,通过该权重值的大小可以很清晰的看出评价指标间的相对重要程度排序,从而使求得的权重具有更高的客观性,以此来解决基于可拓学理论的冰湖溃决预测中权重的求取问题。权重计算结果表明,目前对喜马拉雅山地区冰湖溃决影响最大的是冰川指标,其次是冰碛坝指标,再次是湖盆指标。在冰湖预测指标体系中,从是否有利于溃决来分析,占权重约70%的指标是致溃指标,占权重约30%的指标是阻溃指标。假设冰湖的危险等级的分布情况符合均匀分布规律,则认为目前西藏喜马拉雅山地区存在溃决危险的冰湖有七成,相对较稳定的冰湖有三成。
6.喜马拉雅山地区冰湖溃决危险度等级以高度危险居多,占待测冰湖的40%,低度危险的冰湖占待测冰湖20%。高度危险冰湖的后缓冰川覆盖区面积都比较大,冰舌基本都伸入湖面,为冰湖溃决提供了足够的水源条件;冰湖区的水热组合也都在湿热和干热两者间,为冰湖溃决提供气候条件;且它们的终碛坝坝顶宽度都较为薄弱,在湖水位突涨的情况下,终碛坝容易受破坏造成冰湖溃决。
7.将支持向量机法预测的结果、可拓评价的结果和实际情况进行比较表明:采用这两种非线性方法对冰湖溃决进行预测的结果比较相近,与实际情况比较吻合。这也说明了采用非线性理论对冰湖溃决进行预测是一种有效的方法,证明了本论文选题的理论意义和实用价值。
?In recent years, , the Himalaya Mountains area glacial lake disaster is been prominent day by day for global climate change's influence, the glacial lake which possibly bursts quantity to increase unceasingly, causes the personnel casualty and the massive property damage for the natives, the Tibet economic society develop is restricted seriously. Meanwhile, along with strategy implementation of the national west development, each infrastructure's construction consummates gradually, harmful levels of the glacial lake getting more and more serious. In summary, the forecast which the glacial lake burst to research necessarily.
Research paper on the environment and conditions of the glaciers geological surveys and research relevant information, summarizes natural geographic and geological survey of the Himalaya mountain area, analyzed engineering geology environmental conditions of the Himalayan mountains area. Reference to the research and combination of the survey data, research the outburst condition and mode of glacial lake in the investigation area; Summarizes the influencing factor of the glacial lake outburst and research values and measure for forecast the glacial lake outburst.
Disaster of glacial lake outburst is serious day by day in research area, with wide distribution the characteristics of large damage under the global temperature rises to the environment. At present, glacial lake burst for the study area is still not an effective disaster prediction method. The first use of paper-based support vector machine - extension theory of nonlinear prediction model glacial lake outburst, and applied to paper and make it rely on the glacial lake in the project survey, as glacial lake outburst with a high degree of nonlinearity and uncertainty. Studies have shown that glacial lake outburst based on nonlinear theory prediction model can be more objective to predict the risk of glacial lake, provide a scientific basis for disaster prevention for glacial lake outburst of Himalayan region.
Articles by glacial lake system of the Himalayan region to obtain the following results and conclusions:
1.To study the area of glacial lake outburst has occurred based on survey data, analysis of conditions of glacial lake outburst disasters; including Climatic background, catchment conditions, terrain conditions, hydrological conditions, earthquakes, etc. The glacial lake outburst model are considered both ways, the combination of the climatic background and the different failure modes of moraine, in which the former one is divided into 4 categories ,17 modes,as the latter one 3 modes:wave overflow,seepage deformation, tributaries ditch erosion . No clear boundaries could be seen between the latter three modes, transformation is also available under certain conditions as well.
2.Factor in the analysis of glacial lake outburst, constructed by the glacier - glacier lakes - the main line of morained dam glacial lake outburst prediction index system. With supply glacier area, glacier snow area average longitudinal, tongue slope, the front tongue distance from the glacial lake, glacier fractured situation, glacial lakes area, development of cross-strait situation of collapse, defection slope degree,glacier crest width of the ditch by the side degree of erosion, water and heat combination of 11 factors such as glacial lake outburst forecast evaluation indicators.
3. Risk of glacial lake outburst is the classification of various factors on its characteristics and relationship between the function approximation problem, namely the pattern recognition problem. Support vector machines for nonlinear system has to avoid the local minimum, over the advantages of learning defects. In this paper, based on the support vector machine algorithm and basic principles established risk classification model of glacial lake outburst, and successfully applied this model to the Himalayan region of 25 instances of glacial lake outburst prediction.
4. In the theory of support vector machine based prediction models were tested and found, Learning samples obtained through training to learn the correct rate of 90% or more than one model. This shows that, sampling method for training by learning from the model is correct is not enough reliable.Studying samples of 20 randomly selected models were tested again, test results showed that more than 90% correct, leaving only one, finally ,identified as a reliable algorithm based on support vector machine prediction model ?glacial lake outburst.
5.In the extenics prediction method of glacial lake outburst, the key to the evaluation result perfection is precise weighing. The science in the evaluation calls for weights of reason. This article introduces a weighing methods based on rough set theory. The weight coefficient of each evaluation indicators has been determined under the concept of attribute importance in rough set theory. Thus weights have been given more objectivity as the indicator priorities can be easily seen thought the values of weights. The weighing problem in glacial lake outburst prediction is therefore solved based on extenics theory . In the results, the most influential indicators to the Himalaya glacial lake outburst are glacier indicators, followed by moraine dam indicators and lake indicators. Analyzing on outburst-positive or negative, about 70% indicators are outburst-positive with 30% negative.. Given the danger ranks of glacial lakes follow uniform distribution, outburst danger exists in 70% glacial lakes in the Himalaya areas, while 30% are comparatively stable.
6. More glacial lakes in Himalaya areas are highly dangerous, about 40% of those remaining to survey, while 20% with low danger. Highly dangerous lakes commonly appear with large glacier coverage on the trailing edge and glacier tongue into the lakes, supplying abundant water for the outburst. The positive climate condition for outburst are wet-hot and dry-hot on water-heat combination in the areas. Moreover, danger is seen when it is narrow and weak on the top of the moraine dam, as damage and breakdown can be easily produced when the lake is flooded.
7. Compare support vector machine method to predict the results and evaluate the results of extension as well as the actual results, the results show that, both nonlinear method using glacial lake outburst compared to predict the results of similar, consistent with the actual situation. Visible by means of a combination of both linear comparison can be drawn is the result of reasonable and objective, this also explains the nonlinear theory for the nonlinear problems studied are the most effective way, once again proved the topic of this paper is scientific and practical significance
论文通过对研究区的地质环境调查及相关资料研究,阐述了喜马拉雅山地区的自然地理、地质概况,分析了喜马拉雅山地区的工程地质环境特征。在综合分析前人的研究成果和现场调查资料基础上,提出了研究区冰湖溃决的发生条件和冰湖溃决模式,用量化指标对冰湖溃决进行了预测。
在全球气温升高的大环境下,研究区冰湖溃决灾害日益严重,具有分布范围广、危害大,且尚没有一套行之有效的方法。根据冰湖溃决具有高度的非线性和不确定性的特点,论文采用了基于支持向量机-可拓学理论的非线性冰湖溃决预测模型,对研究区的冰湖溃决的可能性进行预测。预测结构表明,基于非线性理论的冰湖溃决预测模型可以较为客观的对冰湖危险性进行预测,可为喜马拉雅山地区冰湖溃决灾害防治提供科学依据。
论文通过对喜马拉雅山地区冰湖系统的研究,获得以下成果和结论:
1.以研究区已发生的冰湖溃决调查资料为基础,分析研究冰湖溃决灾害的发生条件,其中包括气候背景,汇水条件、地形地貌条件、水文条件、地震等方面;从气候背景组合形式和终碛垄受破坏形式两方面对冰湖溃决模式进行了分类,前者分为4大类、17种模式,后者可分为翻浪涌坝型、渗透融沉溃坝型,旁沟侵蚀型三种模式,后者三种模式间并没有明显的界限,在一定条件可能还会发生转换。
2.在分析冰湖溃决影响因素的基础上,构建了以母冰川-冰湖-终碛垄为主线的冰湖溃决预测指标体系,并采用补给冰川面积、冰川积雪区平均纵坡、冰舌坡度、冰舌前端距冰湖距离、冰川裂隙发育情况、冰湖面积、两岸崩塌发育情况、背水坡度,冰川坝顶宽度、受旁沟冲刷程度、水热组合等11个因子作为冰湖溃决预测的评判指标,并进行了量化。
3.冰湖溃决危险性的分类问题是对其特性与各影响因素之间的函数关系的逼近问题,也即模式识别问题。支持向量机在非线性系统方面具有避免局部极小点、过学习等缺陷的优势,本文以支持向量机的基本原理及其算法为基础,建立了冰湖溃决危险性分类模型,并把此模型成功地应用于喜马拉雅山地区的25个冰湖实例的溃决预测中。
4.在对基于支持向量机理论的预测模型进行检验时发现,学习样本通过训练所得到学习正确率90%以上的模型不止一个,这说明,通过学习样本法进行训练所得模型的正确性是不够可靠的,因此选取学习样本中的9个对模型再次进行检验,测试正确率达90%以上的仅剩下一个。据此,确定其为可靠的基于支持向量机算法的冰湖溃决预测模型。
5.在用可拓评判法对冰湖溃决进行预测时,逼真的权重是优化评价结果的关键因素。权重的分配是否合理,直接影响到评估的科学性。本文提出一种基于粗糙集理论的权重确定求法。利用粗糙集理论中的属性重要度的概念,求出各评价指标的权重系数,通过该权重值的大小可以很清晰的看出评价指标间的相对重要程度排序,从而使求得的权重具有更高的客观性,以此来解决基于可拓学理论的冰湖溃决预测中权重的求取问题。权重计算结果表明,目前对喜马拉雅山地区冰湖溃决影响最大的是冰川指标,其次是冰碛坝指标,再次是湖盆指标。在冰湖预测指标体系中,从是否有利于溃决来分析,占权重约70%的指标是致溃指标,占权重约30%的指标是阻溃指标。假设冰湖的危险等级的分布情况符合均匀分布规律,则认为目前西藏喜马拉雅山地区存在溃决危险的冰湖有七成,相对较稳定的冰湖有三成。
6.喜马拉雅山地区冰湖溃决危险度等级以高度危险居多,占待测冰湖的40%,低度危险的冰湖占待测冰湖20%。高度危险冰湖的后缓冰川覆盖区面积都比较大,冰舌基本都伸入湖面,为冰湖溃决提供了足够的水源条件;冰湖区的水热组合也都在湿热和干热两者间,为冰湖溃决提供气候条件;且它们的终碛坝坝顶宽度都较为薄弱,在湖水位突涨的情况下,终碛坝容易受破坏造成冰湖溃决。
7.将支持向量机法预测的结果、可拓评价的结果和实际情况进行比较表明:采用这两种非线性方法对冰湖溃决进行预测的结果比较相近,与实际情况比较吻合。这也说明了采用非线性理论对冰湖溃决进行预测是一种有效的方法,证明了本论文选题的理论意义和实用价值。
?In recent years, , the Himalaya Mountains area glacial lake disaster is been prominent day by day for global climate change's influence, the glacial lake which possibly bursts quantity to increase unceasingly, causes the personnel casualty and the massive property damage for the natives, the Tibet economic society develop is restricted seriously. Meanwhile, along with strategy implementation of the national west development, each infrastructure's construction consummates gradually, harmful levels of the glacial lake getting more and more serious. In summary, the forecast which the glacial lake burst to research necessarily.
Research paper on the environment and conditions of the glaciers geological surveys and research relevant information, summarizes natural geographic and geological survey of the Himalaya mountain area, analyzed engineering geology environmental conditions of the Himalayan mountains area. Reference to the research and combination of the survey data, research the outburst condition and mode of glacial lake in the investigation area; Summarizes the influencing factor of the glacial lake outburst and research values and measure for forecast the glacial lake outburst.
Disaster of glacial lake outburst is serious day by day in research area, with wide distribution the characteristics of large damage under the global temperature rises to the environment. At present, glacial lake burst for the study area is still not an effective disaster prediction method. The first use of paper-based support vector machine - extension theory of nonlinear prediction model glacial lake outburst, and applied to paper and make it rely on the glacial lake in the project survey, as glacial lake outburst with a high degree of nonlinearity and uncertainty. Studies have shown that glacial lake outburst based on nonlinear theory prediction model can be more objective to predict the risk of glacial lake, provide a scientific basis for disaster prevention for glacial lake outburst of Himalayan region.
Articles by glacial lake system of the Himalayan region to obtain the following results and conclusions:
1.To study the area of glacial lake outburst has occurred based on survey data, analysis of conditions of glacial lake outburst disasters; including Climatic background, catchment conditions, terrain conditions, hydrological conditions, earthquakes, etc. The glacial lake outburst model are considered both ways, the combination of the climatic background and the different failure modes of moraine, in which the former one is divided into 4 categories ,17 modes,as the latter one 3 modes:wave overflow,seepage deformation, tributaries ditch erosion . No clear boundaries could be seen between the latter three modes, transformation is also available under certain conditions as well.
2.Factor in the analysis of glacial lake outburst, constructed by the glacier - glacier lakes - the main line of morained dam glacial lake outburst prediction index system. With supply glacier area, glacier snow area average longitudinal, tongue slope, the front tongue distance from the glacial lake, glacier fractured situation, glacial lakes area, development of cross-strait situation of collapse, defection slope degree,glacier crest width of the ditch by the side degree of erosion, water and heat combination of 11 factors such as glacial lake outburst forecast evaluation indicators.
3. Risk of glacial lake outburst is the classification of various factors on its characteristics and relationship between the function approximation problem, namely the pattern recognition problem. Support vector machines for nonlinear system has to avoid the local minimum, over the advantages of learning defects. In this paper, based on the support vector machine algorithm and basic principles established risk classification model of glacial lake outburst, and successfully applied this model to the Himalayan region of 25 instances of glacial lake outburst prediction.
4. In the theory of support vector machine based prediction models were tested and found, Learning samples obtained through training to learn the correct rate of 90% or more than one model. This shows that, sampling method for training by learning from the model is correct is not enough reliable.Studying samples of 20 randomly selected models were tested again, test results showed that more than 90% correct, leaving only one, finally ,identified as a reliable algorithm based on support vector machine prediction model ?glacial lake outburst.
5.In the extenics prediction method of glacial lake outburst, the key to the evaluation result perfection is precise weighing. The science in the evaluation calls for weights of reason. This article introduces a weighing methods based on rough set theory. The weight coefficient of each evaluation indicators has been determined under the concept of attribute importance in rough set theory. Thus weights have been given more objectivity as the indicator priorities can be easily seen thought the values of weights. The weighing problem in glacial lake outburst prediction is therefore solved based on extenics theory . In the results, the most influential indicators to the Himalaya glacial lake outburst are glacier indicators, followed by moraine dam indicators and lake indicators. Analyzing on outburst-positive or negative, about 70% indicators are outburst-positive with 30% negative.. Given the danger ranks of glacial lakes follow uniform distribution, outburst danger exists in 70% glacial lakes in the Himalaya areas, while 30% are comparatively stable.
6. More glacial lakes in Himalaya areas are highly dangerous, about 40% of those remaining to survey, while 20% with low danger. Highly dangerous lakes commonly appear with large glacier coverage on the trailing edge and glacier tongue into the lakes, supplying abundant water for the outburst. The positive climate condition for outburst are wet-hot and dry-hot on water-heat combination in the areas. Moreover, danger is seen when it is narrow and weak on the top of the moraine dam, as damage and breakdown can be easily produced when the lake is flooded.
7. Compare support vector machine method to predict the results and evaluate the results of extension as well as the actual results, the results show that, both nonlinear method using glacial lake outburst compared to predict the results of similar, consistent with the actual situation. Visible by means of a combination of both linear comparison can be drawn is the result of reasonable and objective, this also explains the nonlinear theory for the nonlinear problems studied are the most effective way, once again proved the topic of this paper is scientific and practical significance
引文
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