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模糊统计决策理论基础上的大型工程项目风险评估方法研究

发布时间:2016-07-17 14:12

  本文关键词:模糊统计决策理论基础上的大型工程项目风险评估方法研究,由笔耕文化传播整理发布。


        随着社会经济长期快速发展,地球在为人类提供了生命必须的粮食、水和必要的能源和矿产资源的同时,也给人类带来了很多自然灾难,诸如火山、地震、海啸等。人类面临日益突出的环境、资源、能源等问题,这不仅是人类探求自然奥秘经过的历程,更是人类向大自然获取能源、资源同时为保障自身安全做出努力的过程,因此急需发展深部探测及其相关技术,以支撑解决以上方面遇到的各种问题。近百年来,各国的地球物理学家、地质学家进行着不懈的努力对其不断探索。我国科学家也意识到必须开展中国地球深部探测计划,才能解决所面临的重大资源环境问题全面实现地球科学的创新与发展。然而全世界地球科学家不得不面对一个事实就是:人类对自身赖以生存的地球内部结构了解太少,目前我们的直接钻探仅达到12km,与庞大的地球体系相比,所涉及的只是地球的表面结构。在一直以来的研究中,研究人员渐渐发现一个不争的事实:可谓上天不易,入地更难。所谓“入地”就是通过深部探测工程,了解地下物质、结构的过程。而以上所要解决的问题都将依赖于深部探测手段——大陆深部科学钻探工程。大陆深部科学钻探工程不仅仅是一个名词,更不单纯是一个简单的工程,它是现代地球科学研究领域中不可或缺的重要工具,它能够提供随着深度的增加直接获得信息,同时无疑也是验证地球物理研究成果和结果正确性的可靠手段。我国超深科学钻探设计万米深度,将面临一系列挑战。随着深度的增加,温度、压力等环境因素也在不断变化,设备的安全性以及钻探过程中事故发生的概率也随之大大增加,对风险的预测和防范增加了难度。实际大陆深部科学钻探工程的实施可以作为实验室研究成果的验证手段,同时对于探索地球奥秘、改进研究起着关键性作用,同时也扮演着极其重要的角色,与社会能源经济有着紧密的联系。其中随钻设计的动态实时量化风险评估针对这项工作展开,能够直接在人力物力财力上减少大量不必要的损失,降低大陆深部科学钻探的整体风险,因此,启动该项研究具有现实意义。然而,现有的风险评估方法满足不了大陆科学深部钻探的需要。原因是:(1)信息来源单一,目前进行项目风险评估的信息源往往是专家系统的经验和单一手段获得的数据,在有经验可循的项目或事件中,专家的经验可以作为判断的依据,遇到无经验可以参照或者经验很少的情况下,这种方法就会变成一种相对主观的判断,很多问题会由于主观经验不足,引起判断上的失误;(2)在对风险评估整体评价维度上,以往的方法是简单地将风险发生的概率与事后影响相乘,这样虽然能够评价出风险的大小,但是得到结果是宽泛、粗线条的,有时甚至可能会遗漏一些风险,或者把一些并不重要的风险归入其中,这样会对进一步的工作带来干扰。(3)现有风险评估的方法大部分是静态的,虽然近年来风险评估会应用在石油勘探企业的管理中,但绝大多数解决的是事前关于项目预算和时间估计与预先评定方面的应用,对于大型工程项目,只做这些方面的风险评估是远达不到要求,加强动态风险评估是解决问题的重要途径,因此,针对具体问题发展一套行之有效的解决方案尤为必要。随着深部钻探技术的不断改进,获取数据信息的手段也不断增加,如何将获得的海量数据有效利用,是获得优质风险评估结果的前提,这就涉及在数据处理阶段用有效的方法将得到的信息进行多尺度多源信息融合。这些数据主要来自于重力勘探、磁法测量、电法测量、地震手段、随钻测井等信息手段。这些信息具有以下特点:多类型、多尺度、多时态,同时数据量庞大数据结构复杂,但是如果恰当运用,这些数据信息之间将能相互配合弥补、彼此之间的不足,从不同角度反映相同地质体特征。除了以上客观数据信息外,我们还有专家系统,这也是一个巨大的信息来源。另外,在深部探测过程中进行实时风险评估可以解决钻进过程中客观条件不断变化带来的问题,例如:压力、温度以及地质岩层结构,直接导致风险因素也会随之发生变化,风险发生的可能性也会发生变化,这就需要在钻探过程中对风险因素进行实时更新与识别,随时监控钻探各项风险发生可能性的大小,以便及时采取防范措施。因此,针对数据特点发展一套行之有效的融合技术需要进行跨学科技术融合和针对性攻关研究。综上所述,深部探测所提供的参数特点具有诸多不确定性,运用结合针对对比开发建立在统计基础上的风险评估数学模型,可以解决在该行业中未解决的问题,因此,对超深钻探进行随钻实时风险评估方法的研究具有理论意义和应用价值。针对大陆超深科学钻探过程中不确定性风险预测和防范问题所设定的研究目标,提出一套基于多尺度多源信息融合的动态风险评估方法,同时建立多指标风险综合评价体系,通过利用随钻测量数据实时更新和完善评估手段,修正评估参数,实现钻进过程中及时发现风险、规避风险和降低风险的应用目标。本文的研究内容:主要分析如何充分考虑大陆深部钻探工程的特点,针对深部钻探随钻过程缺乏有效实时评估钻进风险的方法和技术等问题,尤其是超深钻探过程对此需求更为迫切,本项目将基于实际参数的多尺度多源信息特性,以及在随钻过程中数据实时、递归的特点,研究随钻深度动态参数融合的风险评估方法,对钻进过程中可能出现的随机风险作出预测,提高实时风险评估的准确性,并在复杂的工程实践中得到加强和完善。由此,本论文形成了一个逻辑比较合理的研究框架,在此框架下本论文系统地研究了风险评估方法的相关问题。从研究工作流程上可分为以下7个章节:第一章:摘要。主要介绍本论文的研究背景以及研究的目的和意义。第二章:研究综述。将论文中涉及的两大概念给出定义与性质的描述,同时对国内外的研究现状进行综述。第三章:论文的核心章节之一,属于静态风险评估方法的研究部分。在这一章中主要目的是对各个因素进行风险评估从而进行风险排序,根据以往研究的经验总结出不足之处,提出一种新的4维度评价标准,这4个评价标准分别是:风险发生的概率、风险严重性、不可预知性和恶化后果严重性,这4种维度的评价标准,能够更加适合本项目的特点进行风险评价,以期达到在项目施工前期更加贴近实际风险发生情况概率的预测,给项目实施方以一个量化的标准来看待将要执行的项目,首先是会在哪些方面遇到风险,这些可能发生的风险的大小是怎样的,使之能更加直观明朗。第四章:论文的另一核心章节,也属于静态风险评估方法的研究部分。在这一章中主要目的是对项目整体风险进行风险评估,应用了集成的解释结构模型(ISM)和网络分析法(ANP)对其进行评估。第五章:论文的又一核心章节,动态风险评估方法研究部分。这项研究的主要目的是根据项目实施的具体特点提出的,本项目的特点是:有很多因素会在钻探过程中发生变化,而这些因素的变化在施工前期是无法准确得到的,也就是说在施工前期所得到的情况并非准确信息,这样就加大了项目实施过程中的风险。另外,还有一些影响因素是随着钻进的加深而不断变化,我们在施工前期只能知道这影响因素的大概变化趋势,这样在很大程度上也加大了施工的风险。同时需要明确的是,由于本项目的特殊性,如果在本文中所提出的风险发生,带来的将是十分严重的后果,这样就需要我们在项目施工过程中,不断增强风险预测概率的准确性,以期能够提前给项目实施人员以预警,尽量做到防患于未然的目的。第六章:案例研究。将以上三个核心章节中的方法应用到大陆科学深部钻探工程中,运用在项目中实际得到的数据对以上方法进行验证,一方面是能够对上述工程项目的风险有一个全面量化的结果,另外方面也是验证所提出方法的正确性和可行性。第七章:对全文的总结和展望,在这一章中提出了本研究的不足之处以及未来的研究方向。通过大量国内外文献的阅读以及调研,发现了下面7个在风险评估中的具体问题,因此本论文围绕大型工程的风险评估方法进行研究,就发现的问题展开探讨:(1)如何确定评语集中每个权重的合理性;(2)如何确定每个风险的相对重要性;(3)现有的评价方法并不完善,如何使其能够更加完善,评价结果能够更加合理并且不遗漏或增加风险;(4)如何更加准确地对各个风险因素进行排序;(5)如何对项目整体风险指数予以较客观的评价;(6)在动态风险评估中获得的海量数据,如何将其进行有效的数据过滤;(7)如何有效地对动态过程进行监控的问题。针对以上提出的问题,就现有研究中很少涉及动态风险评估方法这一不足提出解决方案、针对静态风险评估中对每个风险因素进行评价的维度进行了改进,就此,本文在改进措施、调整方案、集成处理手段、处理流程思路、处理技巧等方面提出了以下的创新和改进之处:(1)用层次分析法和网络分析法来确定每个的权重的合理性。(2)用ANP方法确定每个风险的相对重要性。(3)在模糊综合评价法中提出一种新的四维度评价方法。(4)用ISM方法是用来识别风险之间的相互依存关系。进行基于模糊综合评价法的项目风险因素评估方法的研究。从预备阶段的识别风险因素开始,然后进行评语集的建立和评价标准的建立,然后确定每个风险指标的权重,建立模糊评价矩阵,最后计算出风险因素的风险指数。(5)针对风险的重要性排序问题提出一种整合了ISM和ANP的方法。基于集成的ISM和ANP方法的项目整体风险评估方法研究,将ISM和ANP方法有效集成最后计算出项目的整体风险指数。(6)以Kalman滤波为基础,提出一种扩展的Kalman滤波方法对多尺度海量数据进行过滤。(7)在研究动态风险评估方法是,结合实际特点,提出基于多尺度信息融合的动态风险评估方法模型。针对在动态过程中所采集数据的特点,进行动态风险评估方法上的研究,从数据过滤到算法再到模型的逐步推进,最终得到在动态过程中对风险的评估结果。(8)将本论文的所有创新研究方法应用在SinoProbe大陆深部科学钻探项目中,以验证其可行性得到评价结果。对于静态风险评估方法研究的研究思路和技术路线包括以下几个方面:(1)利用模糊综合评价法对项目风险因素进行评估从预备阶段的识别风险因素开始,然后进行评语集的建立和评价标准的建立,然后确定每个风险指标的权重,建立模糊评价矩阵,最后计算出风险因素的风险指数。(2)集成解释结构模型(ISM)和网络分析法(ANP)进行项目整体风险评估将ISM和ANP方法有效集成以计算出项目的整体风险指数。首先确定每个风险的相互依赖程度的大小,构建可达矩阵,随后建立有向图并形成解释结构模型,接下来应用ANP构建网络结构形成超矩阵,在超矩阵的基础上构建聚类矩阵和加权超级矩阵,最终得到项目整体风险大小的评价。对于动态风险评估方法研究的研究思路和技术路线包括以下几个方面:(1)多源信息数据过滤问题本项目中获得数据是多元化的,获得手段包括:重力测量、磁力测量、电法测量、地震测量以及在钻井过程中的测井以及录井的数据,针对某一风险因素,不是所有的数据信息都可以利用得上,有时虽然几个测量指标都能够指征同一个地质特征,但是测量精度、表征的准确度却不尽相同,如何有效利用这些数据信息,将不必要的冗余信息剔除做到数据过滤。本文中所指的多传感器概念和以往的并非完全相同,在这里是广义的多传感器的概念,将多种获取数据的手段看成是多传感器的目标。引入多尺度Kalman滤波的概念,由于其有实时性和递归性以及融合性的特点适应于我们应用领域,建立多传感器的多尺度算法,这是研究的内容之一。(2)动态过程多尺度信息融合表示方法和建模。建立动态过程的信息融合表示方法和建模方法,随后应用这一方法进行动态过程的过程监控以最终得到对于动态过程风险评估的目的。三、四、五、六章是文章的核心章节,提出评价标准,另一个是建立动态风险评估模型,并在实际项目中进行验证。以上的研究成果包括:静态风险评估方法的研究和动态风险评估方法的研究,在研究过程中针对动态风险评估的过程,由于工作量比较大,没有对项目所涉及的所有主要风险进行动态风险评估验证,这是本文的不足之处。同时在今后的研究中,由于本项目的特点,涉及的数据是多尺度、大数据量的,在数据处理方面需要进行更进一步的优化,这是可以开展进一步研究的地方。

    With the sustainable quick development of Chinese economy, the Earthserves us with food, water, and energy sources. However, it bringsdisaster, such as volcano, earthquake, Tsunami as well. Problems we faced,of environment, resource and energy, they are not only the process ofseeking the secrecy of nature, but also the effort of obtaining theresource and energy. Therefore, we need solve them by developing deepexploration technology.Geologists and geophysics are making every effort in recent100years.Scientists in China realized that to solve the problems we have to carryout the program of deep exploration, to achieve the innovation anddevelopment of geosciences. However, geoscientists from all over theworld have to face the fact that we know little about the inner structureof the world. The deepest drilling until now is12km, which is just thesurface layer of the Earth comparing with the whole geological system.During the researches, scientists realized that it was much more difficultfor getting into the earth than into the sky. By getting into the earth,we mean to get to know the inner structure of the earth. The most efficientway of doing this is Deep Continental Scientific Drilling Program, whichis a necessary tool of modern geosciences. It can provide the directinformation with the increase of the depth, and also the most reliableway to prove the result of geophysics research. Chinese super deepdrilling is designed to drill10km, which will face a series of challenges.With the increase of the depth, temperature, pressure and the probabilityof the accident will increase as well, that makes the forecast of the riskbecome more importation. The implement of the Deep Continental ScientificDrilling Program could be a verification mean in the lab, and also it plays the important role in the secret seeking and research improvement. Andthe launch of dynamic real-time quantitative risk assessment can decrease theloss in manpower, physics, the financial resource, and reduce the riskof program, which is really meaningful.However, the methods exist cannot satisfy the need of deep continentalscientific drilling, for the following reasons.(1) The informationresources of risk analyze are the experience of experts andsingle-resource data. In some situation, those could be criterion. Butin others, the experience could make mistakes for the subjective judgments.(2) In the general evaluation of risk analyze, we used to multiply theprobability by the influence, which is too general to make every necessaryrisks into consideration.(3) The exist risk analyze methods are static.Even though some are already applied to the management of oil exploration,most of them are about the budget and time evaluation. Those methods arenot really competent for a program like this. We need to put more effortin dynamic risk analyze. Therefore, it is necessary to make a solution.How to get mass data and make effective use of them is the premiseof the result of risk analyze, which involves data fusion of multi-scalemulti-source information, with the improvement of drilling technology andmeasures to get data.These data comes from gravity prospecting, magnetic prospecting,electrical prospecting, seismic prospecting and LWD information, whichare multi-type, multi-scale, multi-temporal, large-scale andcomplex-structure. However, if we use them properly, those data canconcert with and make up for each other. Besides, we developed an expertsystem, which is a huge resource of information. The problems that broughtwith the changing objective condition could be solved by a real time riskassessment. For example, pressure, temperature and the geologicalstructure could change the risk factor, thus the probability that the risk happens could be changed also. We need to keep indentifying and updatingthe factors, monitoring the probability of the risk during the drillingprocess, to take prevention measures in time. As the result, it needs todevelop a series of methods which are interdisciplinary and specific.In summary, the data from deep exploration are uncertainty. To solvethose problems, we need to combine the data with the risk assessmentmathematical models based on statistics. Therefore, it is reallymeaningful to do a study on a real time risk assessment while drilling.The research objects are to forecast and prevent risks, to build a riskassessment system of multi-index, by making use of data updating andassessment method improvement. This article is aimed to analyze how totake all the necessary characteristics into consideration in deepcontinental scientific drilling program, especially in super deepdrilling, for the shortage of method and technology of a real time riskassessment while drilling. The article will study on dynamic parameter fusionmethod of risk assessment to prevent random risk and to improve the assessmentbased on multi-scale, multi-source, real time and recursion data. Thusthis article studies some related issues that forms a logical framework,which can divided as following7sections.The first chapter is the abstract, which mainly introduces thebackground, purpose and significance of the study.The second chapter is the literature review, obtained by acomprehensive analysis based on literature research, which primarilydefines two important concepts involved in this dissertation anddescribes their nature.The third chapter is the first part of the three core chapters in thedissertation. It is the research on the static risk assessment methods,mainly in which risk sequencing is done according to the risk evaluationsof all the factors. Furthermore, based on the conclusions of pastexperiences and implications, a new set of four-dimensional evaluation standards is created, which includes the risk probability, the riskconsequence severity, the unpredictability and the consequencesseriousness of deterioration. For the risk assessment of this project,the new set is much more appropriate than the standards used before, sinceit can more precisely offer a forecast of risk probability closer to thefact. More intuitively and clearly it provides the project implementationparty with a quantitative standard to determine the upcoming projects,including the list of which aspects the risk occur in firstly and thecalculation of the possible risk.The fourth chapter is the second part of the core. The same as thelast, it also belongs to the research on the static risk assessment methods.But it mainly does the whole risk assessment of the project, with theapplication of integrated ISM and ANP.The fifth chapter is another part of the core. It is about the dynamicrisk assessment methods. The aim of this part research is raisedprincipally according to specific characteristics of the projectimplementation, which are presented as followings. Many factors maychange during the drilling, but it is impossible to get enough accurateinformation of changing during its initial work process. It means thatthe risk of project execution increases without obtaining sufficientaccurate information during the pre-construction. Also some factors arechanging while it is drilling deeper, but there is only a general forecastof trend in the preliminary stage. That increases the danger, too.Meanwhile it is obvious that because of the specificity of this project,there do be very serious consequences if the risk mentioned in thisdissertation occurs. So it is necessary to increase the predictabilityof risk continuously, in order to provide the executive staff with earlywarning for preparing in advance. The sixth chapter is a case study, which applies the methods mentionedin the three core chapters above to the continental scientific deepdrilling project. The results of the project in the case offer averification of the methods. It surely draws an integrated picture ofquantitative description of the project risk on one hand, and on the otherhand confirms the feasibility and correctness of the methods used.The seventh chapter is the conclusion of the whole dissertation andperspective, which contains some recommendations about the lack of thestudy done here and its direction for further research.Based on a large number of domestic and foreign literature readingand research, there raised are7specific questions of risk assessment.This dissertation does the research on the risk evaluation methods oflarge projects and discusses the problems discovered as follows:(1)How to determine the rationality of each weight in the comment set?(2)How to determine the relative importance of each risk?(3)How to achieve the perfection of the existing deficient evaluationmethods in order to get more reasonable evaluation results but withoutmissing or increasing the risk?(4)How to sort various risk factors more accurately?(5)How to evaluate the whole risk index of the project objectively?(6)How to effectively filter mass data obtained from the dynamic riskassessment?(7)How to effectively monitor the dynamic process?In view of the questions above, a solution is put forward to solvethe problem that the existing dynamic risk assessment methods are rarelyinvolved in the study, and also the evaluation dimensions of each riskfactor are improved in the process of static risk assessing.Thisdissertation deals with the improved measures, the adjustment scheme,integrated processing methods, ideas of handling process, processing technique and so on.These innovations and improvements are listed asfollows:(1)The rationality of every weight is confirmed by using analytichierarchy process and network analysis.(2)The relative importance of each risk is determined by using ANP.(3)An approach of application of a new four-dimensional assessmentmethod is presented in the method of fuzzy-synthetic evaluation.(4)The interdependence between risks is identified by using ISM andthe factor assessment method of project risk is studied on the base offuzzy-synthetic evaluation method. How to do it? Firstly identify riskfactors in the preliminary phase; and then establish the comment set andevaluation standards; thirdly determine the weight of each risk index andestablish fuzzy evaluation matrix; finally calculate the risk index ofrisk factors.(5)In order to rank the importance of risk, a method is proposed byintegrating the ISM and ANP. Based on this integration method of the wholeproject risk assessment, ISM and ANP are effectively integrated, and usedto calculate the project overall risk index.(6)Based on Kalman filter, this dissertation puts forward a kind ofextended method for filtering multi-scale data.(7)In the research of dynamic risk assessment method, combined withthe actual characteristics, this dissertation presents dynamic riskassessment model based on multi-scale information fusion.(8)This dissertation applies the creative method in SinoProbecontinental scientific deep drilling project in order to verify itsfeasibility.The research thinking and technical route of static method of riskassessment includes the following aspects: (1)The fuzzy comprehensive evaluation method is used to assessproject risk factors.Firstly identify risk factors in the preliminary phase; and thenestablish the comment set and evaluation standards; thirdly determine theweight of each risk index and establish fuzzy evaluation matrix; finallycalculate the risk index of risk factors.(2)The method of the whole project risk assessment, which integratesISM and ANP, is applied in the whole project risk assessment.ISM and ANP are effectively integrated in order to calculate theproject overall risk index. First, determine the degree ofinterdependence between each risk and build a reachable matrix; then,establish a directed graph and an interpretive structural model; thirdly,with the application of ANP, build net structure in order to set up supermatrix; next, on the basis of the super matrix, design clustering matrixand weighted super matrix; finally, get the result of the whole projectrisk assessment.The research thinking and technical route of dynamic method of riskassessment includes the following aspects:(1)The problem about filtering multi-source informationThe data of this project is gained in diversified ways, includinggravity measuring, magnetic density surveying, resistivity checking,seismic surveying, well logging and mud logging in the process of drillingand so on. For a certain risk factors, not all data can be used. Sometimesseveral measurements are able to refer to the same geologicalcharacteristics, but the accuracy of their precision and characterizationare different from each other. To deal with this, the dissertation focuseson how to efficiently use these data without redundant information. inThe referred concept of multi-sensor here is not completely the same aspast, but a generalized one, regarding various means of obtaining data as a multi-sensor target. Partly the research focuses on introducing theconcept of multi-scale Kalman filtering and establishing multi-sensormulti-scale algorithm.(2)The expressing method and the modeling approach of Multi-scaleinformation fusion used in the dynamic processThe expressing method and the modeling approach of Multi-scaleinformation fusion used in the dynamic process are established, andapplied in monitoring the dynamic process in order to assess the risk ofprocess.Chapter3-6are core in the dissertation.The research results include the static risk assessment methodresearch and the research of dynamic risk assessment method. One of theshortages of this article is that it has not verified the risks by dynamicrisk assessment for the reason that dynamic risk assessment needs largeamount of workload. In the future study, we need to improve the dataprocessing to deal with the multi-scale and large amount data based onthis program.

        

模糊统计决策理论基础上的大型工程项目风险评估方法研究

摘要4-10Abstract10-17第1章 绪论20-29    1.1 研究背景和问题提出20-21    1.2 研究目的和意义21-23    1.3 研究思路及主要内容23-26        1.3.1 研究思路23-24        1.3.2 研究内容24-26    1.4 本文创新之处26-29第2章 研究现状综述29-40    2.1 概念定义与性质分析29-33        2.1.1 大型复杂工程项目的定义与性质29-32        2.1.2 模糊统计决策理论的定义32-33    2.2 风险评估方法研究现状33-40        2.2.1 国外研究现状33-35        2.2.2 国内研究现状35-40第3章 基于模糊综合评价法的项目风险因素评估方法研究40-57    3.1 预备阶段41-50        3.1.1 建立风险评估组41-42        3.1.2 识别风险因素42-50    3.2 评估特定风险50-56        3.2.1 确定评语集51-52        3.2.2 建立评价标准52-53        3.2.3 确定每个风险指标的权重53-54        3.2.4 建立模糊评价矩阵54        3.2.5 计算风险指数54-56    3.3 本章小结56-57第4章 基于集成ISM 和ANP方法的项目整体风险评估方法研究57-79    4.1 项目整体风险评估的基本方法57-62        4.1.1 解释结构模型法57-58        4.1.2 层次分析法58-62    4.2 集成ISM和ANP的项目整体风险评估方法研究62-77        4.2.1 确定各个风险相互依赖程度62-65        4.2.2 构建ANP网络结构65-69        4.2.5 形成未加权超矩阵69-74        4.2.6 构建聚类矩阵74-75        4.2.7 构建加权超矩阵75        4.2.8 形成极限级矩阵75-77    4.3 评估项目整体风险指数77-78    4.4 本章小结78-79第5章 基于多尺度信息融合的动态风险评估方法研究79-125    5.1 多尺度数据的过滤80-89        5.1.1 分块系统的多尺度描述81-82        5.1.2 多尺度贯序式Kalman滤波82-86        5.1.3 MSBKF算法推导86-89    5.2 多尺度多传感器数据融合89-105        5.2.1 多传感器系统描述90-91        5.2.2 多尺度序贯Kalman滤波器实时性和递归性91-99        5.2.3 多尺度序贯Kalman滤波器融合性99-105    5.3 动态过程多尺度数据融合表示方法与建模105-117        5.3.1 动态过程多尺度信息融合表示方法106-113        5.3.2 动态过程多尺度信息融合建模113-117    5.4 多尺度数据融合方法的动态过程监控117-124        5.4.1 问题描述与分析117-118        5.4.2 基于数据融合理论的动态过程监控118-122        5.4.3 基于多尺度数据融合的动态过程监控方法122-123        5.4.4 多尺度方法的优势123-124    5.5 本章小结124-125第6章 案例应用125-153    6.1 项目风险因素评估125-132        6.1.1 建立风险评估组125        6.1.2 确定风险因素125-126        6.1.3 确定评估标准126        6.1.4 建立评语集126        6.1.5 确定每个标准的权重126-128        6.1.6 建立模糊评估矩阵128-130        6.1.7 计算风险指数130-132    6.2 项目整体风险评估132-145        6.2.1 整体风险评估前期工作132-144        6.2.2 确定每个风险的权重144        6.2.3 评估总体风险144-145    6.3 动态风险评估145-153        6.3.1 数据过滤146-149        6.3.2 多尺度数据融合149-151        6.3.3 动态过程监控151-153第7章 结论与展望153-156    7.1 全文总结153-155    7.2 研究展望155-156参考文献156-166作者简介及在校期间所取得的科研成果166-168致谢168-169



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