基于可变模糊集理论的径流预报方法研究
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摘要
水库调度是缓解我国水资源短缺问题、实现洪水资源化的一项重要非工程措施。而科学、合理水库调度需要建立在充分掌握客观水文规律的基础上。因此,水库的水文预报是合理调度的基础,是提高水库的径流调节能力、充分发挥水库综合效益的重要前提。本文以可变模糊集理论为基础,重点研究了基于可变模糊集理论的径流中长期推理预报方法,为提高水库调度水平、缓解我国水资源短缺问题提供技术支持;同时研究了流域洪水模糊可变分类预报方法:最后是可变模糊集理论中模糊可变评价方法及与人工神经网络相结合时的应用研究。
主要研究内容及成果如下:
(1)隶属度与隶属函数是模糊集合论中最重要的概念。在可变模糊集理论中,考虑区间值的相对隶属函数可以合理、简便地计算模糊集中任意元素对于该模糊集的相对隶属度。本文通过分析比较,找出了它与传统的线性模糊分布函数之间的区别与联系,即传统的模糊分布函数是考虑区间值的相对隶属函数的一些特例,考虑区间值的相对隶属函数在描述模糊现象的模糊性时更具有普遍适用性。同时指出了应用考虑区间值的相对隶属函数时应当注意的问题,为接下来的应用奠定了基础。
(2)提出了基于级别特征值的径流中长期预报单要素模糊推理方法,使已有的水文气象单要素模糊推理法得到了改进。方法应用可变模糊集理论中考虑区间值的相对隶属度函数来确立模糊子集的隶属函数,增强了模糊推理预报方法的理论基础;采用待预报径流级别特征值建立推理预报模式,避免了由于划分径流级别数目不合适造成的大量重复计算。详细介绍了方法的基本原理及步骤,并通过实例研究对其进行了验证。
(3)在深入研究了基于相似关系的近似推理法基础上,提出了考虑预报因子权重的径流中长期预报模糊推理法,丰富了水文中长期预报模糊推理方法;为说明方法的基本原理及步骤,验证方法的合理性和有效性,将其应用于大伙房水库年径流检验预报。从检验预报结果看出:考虑预报因子权重的预报结果好于不考虑预报因子权重(等权重)的预报结果,表明在径流中长期预报中,考虑预报因子对待预报径流影响的差异是十分必要的。
(4)为尝试研究径流中长期预报方法中存在的可变因素对预报信息的影响,以陈守煜教授提出的可变模糊集理论为基础和指导思想,提出了基于相似关系的径流中长期预报模糊可变推理方法,分析了方法中存在的可变参数。在实例研究中,对可变参数进行了六种组合变换,在不同的组合变换方式下分别进行了大伙房水库年径流预报检验,得到了多种预报信息。通过综合分析各种预报信息之间的异同,确定最终的预报结果及其可靠程度,可用于指导水库调度决策。
(5)以可变模糊集理论为基础,提出一种考虑分类指标区间值的流域洪水分类方法——模糊可变分类方法。该方法可根据洪水发生的前期特征,合理、简便地将洪水进行分类,按类别优选模型参数、预报未来洪水过程,以提高流域洪水预报水平,为预报实时校正和水库调度提供较准确的参考信息:给出了相应的应用研究,应用研究结果验证了方法合理性和有效性。
(6)可变模糊集理论中模糊可变评价方法可以很好地对评价标准为区间形式的问题进行综合评价。作为可变模糊集理论研究及在水文水资源领域应用的扩展,本文应用模糊可变评价方法,对黄河流域水资源可再生能力进行了综合评价;建立了基于模糊优选神经网络和可变模糊集理论的评价方法,应用该方法对黄河流域水资源可再生能力进行了综合评价。
An efficient flood-control decision-making is an important non-structural measure to relieve water resources shortage and fully utilize wate r resources. It is necessary to fully understand the objective hydrology regularities so as to make scientific and reasonable flood-control decision. Therefore, hydrology forecasting is the basis of reservoir operation. It is also a very important premise to improve the watershed runoff ability and make full use of the comprehensive benefit of reservoir. Based on the variable fuzzy set theory, this dissertation mainly studies the fuzzy reasoning methods for mid-long term runoff forecasting, which can provide the technical support for improving the reservoir operation lever and relieving the water resource shortage. On the other hand, the classified and forecasting methods for basin flood are also studied here.
The main objectives and results for this research are as follows.
(1) The relative membership degree and relative membership function are the most important definitions in the fuzzy set theory. In the variable fuzzy set theory, the relative membership function based on interval pattern value can be used to determine the relative membership degree of any element in a fuzzy set. The difference and connection between the relative membership function based on interval pattern value and the existing fuzzy distribution function are found, i.e. the existing fuzzy distribution is a special case of the relative membership function based on interval pattern value. The relative membership function based on interval pattern value has universality and extensive adaptablity. Finally, the noticeable problem for this relative membership function is considered.
(2) The fuzzy reasoning method with single factor for mid-long runoff forecasting based on rank feather value is proposed. This method applies the interval pattern value to determine the relative membership degree by relative membership function and enhances the theory basis of existing fuzzy reasoning method. The reasoning model in the proposed method is established by the rank feather value of forecasting runoff, which can avoid a lot of repeated calculation. The fuzzy reasoning method principles are presented in detail and verified by case studies in this thesis. It shows that the fuzzy reasoning method can improve the existing hydrology and meteorology fuzzy reasoning method.
In order to enrich and improve the fuzzy reasoning method for runoff forecasting, a fuzzy reasoning method with factor weight for runoff forecasting is developed on the basis of approximate fuzzy reasoning similarity relationship. This method is applied to study the Dahuofang reservoir yearly runoff forecasting. The results with factor weight are better than those with equal weigh, which shows the method with factor weight is necessary.
(4) The fuzzy variable reasoning method for mid-long runoff forecasting is proposed on the basis of approximate fuzzy reasoning similarity relationship. The variable parameters in the variable method are found out. A case study of Dahuofang reservoir yearly runoff forecasting is given by six combination conversion of variable parameters. The final forecast result can be obtained by analyzing the relationship among different forecasting information and used to guide the schedule of reservoir operation.
(5) A classified forecasting method for basin floods is proposed based on the variable fuzzy sets theory. This method can be used to classify the basin floods according to the early stage characteristics of floods. Then the parameters in flood forecast model are optimized respectively and applied to forecast the corresponding type of basin floods. The application study shows that the proposed method is reasonable and valuable.
(6) The fuzzy variable evaluation method is applied to assess the water resources renewability for nine administrative divisions in the Yellow River basin. Based on variable fuzzy set theory and artificial neural network, an innovative evaluation model is proposed and used to study water resources renewability.
主要研究内容及成果如下:
(1)隶属度与隶属函数是模糊集合论中最重要的概念。在可变模糊集理论中,考虑区间值的相对隶属函数可以合理、简便地计算模糊集中任意元素对于该模糊集的相对隶属度。本文通过分析比较,找出了它与传统的线性模糊分布函数之间的区别与联系,即传统的模糊分布函数是考虑区间值的相对隶属函数的一些特例,考虑区间值的相对隶属函数在描述模糊现象的模糊性时更具有普遍适用性。同时指出了应用考虑区间值的相对隶属函数时应当注意的问题,为接下来的应用奠定了基础。
(2)提出了基于级别特征值的径流中长期预报单要素模糊推理方法,使已有的水文气象单要素模糊推理法得到了改进。方法应用可变模糊集理论中考虑区间值的相对隶属度函数来确立模糊子集的隶属函数,增强了模糊推理预报方法的理论基础;采用待预报径流级别特征值建立推理预报模式,避免了由于划分径流级别数目不合适造成的大量重复计算。详细介绍了方法的基本原理及步骤,并通过实例研究对其进行了验证。
(3)在深入研究了基于相似关系的近似推理法基础上,提出了考虑预报因子权重的径流中长期预报模糊推理法,丰富了水文中长期预报模糊推理方法;为说明方法的基本原理及步骤,验证方法的合理性和有效性,将其应用于大伙房水库年径流检验预报。从检验预报结果看出:考虑预报因子权重的预报结果好于不考虑预报因子权重(等权重)的预报结果,表明在径流中长期预报中,考虑预报因子对待预报径流影响的差异是十分必要的。
(4)为尝试研究径流中长期预报方法中存在的可变因素对预报信息的影响,以陈守煜教授提出的可变模糊集理论为基础和指导思想,提出了基于相似关系的径流中长期预报模糊可变推理方法,分析了方法中存在的可变参数。在实例研究中,对可变参数进行了六种组合变换,在不同的组合变换方式下分别进行了大伙房水库年径流预报检验,得到了多种预报信息。通过综合分析各种预报信息之间的异同,确定最终的预报结果及其可靠程度,可用于指导水库调度决策。
(5)以可变模糊集理论为基础,提出一种考虑分类指标区间值的流域洪水分类方法——模糊可变分类方法。该方法可根据洪水发生的前期特征,合理、简便地将洪水进行分类,按类别优选模型参数、预报未来洪水过程,以提高流域洪水预报水平,为预报实时校正和水库调度提供较准确的参考信息:给出了相应的应用研究,应用研究结果验证了方法合理性和有效性。
(6)可变模糊集理论中模糊可变评价方法可以很好地对评价标准为区间形式的问题进行综合评价。作为可变模糊集理论研究及在水文水资源领域应用的扩展,本文应用模糊可变评价方法,对黄河流域水资源可再生能力进行了综合评价;建立了基于模糊优选神经网络和可变模糊集理论的评价方法,应用该方法对黄河流域水资源可再生能力进行了综合评价。
An efficient flood-control decision-making is an important non-structural measure to relieve water resources shortage and fully utilize wate r resources. It is necessary to fully understand the objective hydrology regularities so as to make scientific and reasonable flood-control decision. Therefore, hydrology forecasting is the basis of reservoir operation. It is also a very important premise to improve the watershed runoff ability and make full use of the comprehensive benefit of reservoir. Based on the variable fuzzy set theory, this dissertation mainly studies the fuzzy reasoning methods for mid-long term runoff forecasting, which can provide the technical support for improving the reservoir operation lever and relieving the water resource shortage. On the other hand, the classified and forecasting methods for basin flood are also studied here.
The main objectives and results for this research are as follows.
(1) The relative membership degree and relative membership function are the most important definitions in the fuzzy set theory. In the variable fuzzy set theory, the relative membership function based on interval pattern value can be used to determine the relative membership degree of any element in a fuzzy set. The difference and connection between the relative membership function based on interval pattern value and the existing fuzzy distribution function are found, i.e. the existing fuzzy distribution is a special case of the relative membership function based on interval pattern value. The relative membership function based on interval pattern value has universality and extensive adaptablity. Finally, the noticeable problem for this relative membership function is considered.
(2) The fuzzy reasoning method with single factor for mid-long runoff forecasting based on rank feather value is proposed. This method applies the interval pattern value to determine the relative membership degree by relative membership function and enhances the theory basis of existing fuzzy reasoning method. The reasoning model in the proposed method is established by the rank feather value of forecasting runoff, which can avoid a lot of repeated calculation. The fuzzy reasoning method principles are presented in detail and verified by case studies in this thesis. It shows that the fuzzy reasoning method can improve the existing hydrology and meteorology fuzzy reasoning method.
In order to enrich and improve the fuzzy reasoning method for runoff forecasting, a fuzzy reasoning method with factor weight for runoff forecasting is developed on the basis of approximate fuzzy reasoning similarity relationship. This method is applied to study the Dahuofang reservoir yearly runoff forecasting. The results with factor weight are better than those with equal weigh, which shows the method with factor weight is necessary.
(4) The fuzzy variable reasoning method for mid-long runoff forecasting is proposed on the basis of approximate fuzzy reasoning similarity relationship. The variable parameters in the variable method are found out. A case study of Dahuofang reservoir yearly runoff forecasting is given by six combination conversion of variable parameters. The final forecast result can be obtained by analyzing the relationship among different forecasting information and used to guide the schedule of reservoir operation.
(5) A classified forecasting method for basin floods is proposed based on the variable fuzzy sets theory. This method can be used to classify the basin floods according to the early stage characteristics of floods. Then the parameters in flood forecast model are optimized respectively and applied to forecast the corresponding type of basin floods. The application study shows that the proposed method is reasonable and valuable.
(6) The fuzzy variable evaluation method is applied to assess the water resources renewability for nine administrative divisions in the Yellow River basin. Based on variable fuzzy set theory and artificial neural network, an innovative evaluation model is proposed and used to study water resources renewability.
引文
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