CN102789546B - Reference lake quantitative determination method based on human disturbance intensity - Google Patents

Reference lake quantitative determination method based on human disturbance intensity Download PDF

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CN102789546B
CN102789546B CN 201210241347 CN201210241347A CN102789546B CN 102789546 B CN102789546 B CN 102789546B CN 201210241347 CN201210241347 CN 201210241347 CN 201210241347 A CN201210241347 A CN 201210241347A CN 102789546 B CN102789546 B CN 102789546B
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reference
evaluation
lakes
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CN102789546A (en
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席北斗
霍守亮
何卓识
苏婧
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中国环境科学研究院
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Abstract

一种基于人类扰动强度的参照湖泊定量化确定方法,其主要步骤包括:1)在目标区域内,确定区域内候选参照湖泊,应用主成分分析方法确定湖泊流域人类扰动强度的指标,建立候选参照湖泊评价指标体系及其等级标准;2)确定评价指标权重,对候选参照湖泊评价指标重要性进行两两比较,建立基于层次结构的模糊互补判断矩阵A,对矩阵A进行一致性判断;其中矩阵A=(aij)6×6,且0≤aij≤1,aij+aji=1;3)用集对分析方法计算候选参照湖泊评价指标情况下,候选参照湖泊与评价等级之间的单指标联系度,以及候选参照湖泊与评价等级间的综合联系度;4)评价候选参照湖泊等级,确定参照湖泊。 A method of determining the quantitative lakes based on the reference intensity of human disturbance which mainly comprises: 1) within the target area, the candidate region is determined with reference to the lake, the principal component analysis method for determining index perturbation intensity human lake basin, with reference to the establishment of the candidate lake evaluation system level standard; 2) determine the evaluation index weight, the candidate reference pairwise comparison evaluation index importance lakes, establishing fuzzy complementary judgment matrix a hierarchy of matrix a consistency judgment; matrix wherein a = (aij) 6 × 6, and 0≤aij≤1, aij + aji = 1; 3) analysis calculated by reference to the evaluation of candidate sets and lakes, single index between the candidate reference lakes and rank Information degree, and the degree of contact between the synthesis candidate reference lakes and rank; 4) evaluation of candidate reference lake levels to determine the reference lake. 本发明对于参照湖泊的定量化选择以及湖泊的保护、评估和管理都有重要的实际意义。 The present invention is useful for quantitative selection and protection lake, lake reference assessment and management has important practical significance.

Description

一种基于人类扰动强度的参照湖泊定量化确定方法 Referring quantitative determination method based on human lake perturbation intensity

技术领域 FIELD

[0001] 本发明属于环境保护技术领域,具体涉及一种基于人类扰动强度的参照湖泊定量化确定方法。 [0001] The present invention belongs to the technical field of environmental protection, particularly to quantitatively determine referring lake human perturbation intensity based method.

背景技术 Background technique

[0002] 参照湖泊(ReferenceLake)是指未受人类影响或受人类影响非常小且维持最佳用途的湖泊,可代表该区域地区自然生物学的、物理的和化学的完整性。 [0002] Referring lake (ReferenceLake) refers unaffected by human or human influence and impact a very small lake maintain best use of the natural region may represent the region of biological, chemical and physical integrity. 参照湖泊是一个区域的代表,它们的状态应代表该区域内可预测的类似湖泊中受影响最小状态的最佳范围。 Referring lake is representative of a region, which should be representative of the state of the optimum range of predictable similar region least affected lakes state. 通常情况下,没有受到人类干扰的湖泊是不存在的。 Normally, the lake is not subject to human interference does not exist. 欧洲水框架指令中建议湖泊参照状态可以有较小的波动范围,这意味着人类影响是允许的,只要没有或只有很小的生态影响。 European Water Framework Directive proposed in reference lakes state may have a small fluctuation range, which means that human impacts are allowed, as long as no or only minimal ecological impact. 因此,一般会选择受人类影响最小的湖泊作为参照湖泊。 Thus, the general will choose the smallest human-influenced lakes as reference lakes. 参照湖泊是确定区域湖泊参照状态的重要方法之一,也是确定湖泊恢复到最佳状态的基线。 Referring lake region is an important method to determine reference state lake, lake is determined to restore the best baseline. 不同区域的湖泊在成因、类型、演变过程、营养物效应以及物理、化学、生物学特性等方面均存在着显著的地域性差异,同时湖泊流域人口密集、社会经济发达,湖泊普遍受人类扰动大,科学地筛选出不同生态分区的参照湖泊是建立生态分区湖泊营养物基准,进行湖泊的保护、评估和管理的重要基础。 Lakes in different regions of the causes, types, evolution, nutrient effect as well as physical, chemical and biological characteristics there are significant regional differences, while densely populated lake basin, socio-economic development, human disturbance by large lakes universal scientifically selected reference lakes of different ecological zoning is the establishment of ecological zoning lake nutrient criteria, be an important foundation for the protection of lakes, assessment and management.

[0003]目前,国际上尚未形成统一的定量化确定参照湖泊的标准方法,没有统一的指标体系,只是根据定性和定量指标分步筛选确定参照湖泊。 [0003] Currently, no international unified quantification determined by reference to standard methods lakes, no unified index system, but is determined with reference to screening according to qualitative and quantitative indicators lakes step. 研究结果受研究人员的人为主观影响很大。 Great influence of subjective findings by the researchers.

发明内容 SUMMARY

[0004]本发明的目的在于提供一种基于人类扰动强度的参照湖泊定量化确定方法。 [0004] The object of the present invention is to provide a method for quantitative determination of human disturbance lakes based on the reference intensity.

[0005]为实现上述目的,本发明提供的基于人类扰动强度的参照湖泊定量化确定方法, 其主要步骤包括: [0005] To achieve the above object, the present invention provides a method for determining quantitatively lakes based on the reference intensity of human disturbance which mainly comprises the step of:

[0006] 1)在目标区域内,确定区域内候选参照湖泊,应用主成分分析方法确定湖泊流域人类扰动强度的指标,建立候选参照湖泊评价指标体系及其等级标准; [0006] 1) within the target area, the candidate region is determined with reference to the lake, the principal component analysis method for determining human lake basin index perturbation intensity, the establishment of the candidate reference lake grading and evaluation system;

[0007]2)确定评价指标权重 [0007] 2) determining evaluation weights

[0008]对候选参照湖泊评价指标重要性进行两两比较,建立基于层次结构的模糊互补判断矩阵A,对矩阵A进行一致性判断;其中矩阵A= (¾) 6X6,且0彡%彡I,aij+aji = 1 (式中的i、j为候选参照湖泊评价指标); [0008] Referring to the candidate evaluation index importance lakes pairwise comparison, establishing fuzzy complementary judgment matrix A hierarchy of matrix A consistency judgment; where the matrix A = (¾) 6X6, and 0% San San I , aij + aji = 1 (formula i, j for the evaluation of candidate reference lake);

[0009]3)用集对分析方法计算候选参照湖泊评价指标情况下,候选参照湖泊与评价等级之间的单指标联系度,以及候选参照湖泊与评价等级间的综合联系度; [0009] 3) Calculation Method for Evaluating candidate reference to the evaluation and lakes, with reference to the candidate contact between the single index of lakes and evaluation level, and the degree of contact between the candidate reference Comprehensive evaluation grade and lakes;

[0010] 4)评价候选参照湖泊等级,确定参照湖泊。 [0010] 4) Evaluation of candidate reference lake levels to determine the reference lake.

[0011] 所述基于人类扰动强度的参照湖泊定量化确定方法,其中,湖泊流域人类扰动强度的指标包括:湖泊流域的自然植被、湖岸带宽度、农业、点源排放、最小栖息地得分和城市用地;建立的候选参照湖泊评价指标体系及其等级标准分为AF六类,其中: [0011] The determination method based on the reference lake quantification of human disturbance intensity, wherein the index perturbation intensity human lake basin comprising: a lake basin natural vegetation, Lake width, agriculture, point source emissions, and the minimum score urban habitat land; candidate reference lake established grading and evaluation system is divided into six AF, wherein:

[0012]A类为理想的流域和湖泊状态,没有人类干扰的流域; [0012] A class over the lake basin and state without human interference basin;

[0013] B类是优良的流域和湖泊状态; [0013] Class B and lake basin is an excellent state;

[0014] C类为临界的流域和湖泊状态,有一定的人类干扰,但湖泊水生态系统稳定; [0014] Class C and lake basin is critical state, a certain degree of human interference, but the lake water ecosystem stability;

[0015] D类是低于临界流域和湖泊状态的湖泊,在湖泊或流域有相当的人类干扰出现; [0015] Class D lakes below the critical state and lake basin, or lake basin considerable human interference occurs;

[0016] E类为差的湖泊和流域状态,在湖泊和流域都有相当的人类干扰出现; [0016] E class lake basin and a poor state, and lake basin has a considerable human interference occurs;

[0017] F类是非常差的湖泊和流域状态,人类干扰大范围的贯穿湖泊和流域。 [0017] F class is very poor and lake basin state, a wide range of human interference and lakes throughout the basin.

[0018] 所述基于人类扰动强度的参照湖泊定量化确定方法,其中,确定评价指标权重是采用基于模拟退火算法混合加速遗传算法的层次分析法,以一致性指标系数最小化为目标,对各指标的权重进行计算;修正的模糊互补判断矩阵B= (I3ij)6x6各指标的权重为{ωiIi= 1,2, . . .,6},则使下式最小的B为A的最优模糊一致判断矩阵: [0018] The determination method based on the reference lake quantification of human disturbance intensity, wherein determining evaluation weights are accelerating hybrid genetic algorithm Simulated Annealing algorithm AHP, consistency index coefficient to minimize the total for each calculating the weight of indicators; corrected fuzzy judgment matrix B = (I3ij) weight of each index for the 6x6 {... ωiIi = 1,2,, 6}, so that the minimum B of the formula a optimal Fuzzy consistent judgment matrix:

Figure CN102789546BD00051

[0022] 所述基于人类扰动强度的参照湖泊定量化确定方法,其中,采用的集对分析方法如下式: [0022] Quantitative determination method with reference to the lakes based on human perturbation intensity, wherein the set of analysis employed the following formula:

Figure CN102789546BD00052

[0026] 式中,i是候选参照湖泊,j代表候选参照湖泊评价指标,k是评价等级,uiA是评价等级之间的单指标联系度。 [0026] wherein, i is the candidate reference lakes, j representative of the candidate evaluation reference lakes, k is the evaluation grade, uiA single connection degree between the evaluation index level.

[0027] 所述基于人类扰动强度的参照湖泊定量化确定方法,其中,评判候选参照湖泊的等级时,将级别特征值 [0027] The determination method based on the reference lake quantification of human disturbance intensity, wherein when the candidate reference level evaluation lakes, the eigenvalue level

[0028] [0028]

Figure CN102789546BD00053

[0029] 作为评判候选参照湖泊评价指标的等级,得到候选参照湖泊等级后,即可选取适当湖泊作为参照湖泊;式中,Iii是候选参照湖泊i的等级。 After [0029] As evaluation of candidate reference level evaluation lake, lake obtained candidate reference level, as a reference to select a suitable lake lakes; wherein, Iii candidate reference level i of the lake.

[0030] 所述基于人类扰动强度的参照湖泊定量化确定方法,其中,评判候选参照湖泊的等级时,采用置信度准则评判候选参照湖泊i的等级比: [0030] Quantitative determination method with reference to the lakes based on human perturbation intensity, wherein, when the evaluation of candidate reference level lakes, using confidence criterion evaluation of candidate reference level lake i ratio:

Figure CN102789546BD00061

卜;得到候选参照湖泊等级后,即可选取适当湖泊作为参照湖泊。 Bu; to give the candidate reference level lake, lake as a reference to select the appropriate lake.

[0031] 本发明在进行候选参照湖泊评价时引入了一致性判别分析,既考虑了专家判断, 又进行了客观调整,使得参照湖泊的确定结果更加科学、客观。 [0031] The present invention introduces a candidate performed when the evaluation reference lake consistency discriminant analysis, considering both the expert judgment, adjustment and objectively, such lakes with reference to the determination result more scientific objective. 对于参照湖泊的确定,以及建立生态分区湖泊营养物基准,进行湖泊的保护、评估和管理有着重要的实际意义。 For determining the reference lakes, as well as the establishment of ecological zoning lake nutrient criteria, to protect lakes, assessment and management has important practical significance.

附图说明 BRIEF DESCRIPTION

[0032] 图1是本发明基于人类扰动强度的参照湖泊定量化确定方法的流程示意图。 [0032] FIG. 1 is a schematic flow diagram of the method of determining the quantitative lakes of the present invention is based on human perturbation intensity reference.

具体实施方式 Detailed ways

[0033] 本发明针对国际上现有参照湖泊确定方法主观影响大,缺乏定量化方法的问题, 提供了一种基于人类扰动强度的参照湖泊的定量化确定方法。 [0033] The present invention for determining the existing international reference method Great Lakes subjective impact, lack of quantitative methods of problem, a quantitative reference lakes based on human perturbation intensity determination method.

[0034] 本发明的技术方案如下:应用主成分分析方法建立候选参照湖泊评价指标体系及其等级标准;对候选参照湖泊评价指标重要性进行两两比较,确定初始指标权重矩阵;用基于模拟退火算法混合加速遗传算法的层次分析法对初始指标权重矩阵进行矩阵一致性修正,并计算各指标的权重;用集对分析方法计算指标、候选参照湖泊与评价等级之间的联系度,然后运用模糊集的思想计算候选参照湖泊隶属于"评价等级"的隶属度,最后确定候选参照湖泊等级,以此确定参照湖泊。 [0034] aspect of the present invention is as follows: Principal Component Analysis method for establishing the candidate reference lake grading and evaluation system; candidate reference pairwise comparison evaluation index lakes importance, to determine the initial weight matrix index; based on simulated annealing algorithm mixing acceleration AHP GA initial index weight matrix for improving the consistency of, and to calculate the weight of each index; calculation index analysis method set, the candidate reference to the connection degree between the lakes and rating scale, then fuzzy candidate set of calculation ideological reference lakes under the "rank" of membership, to finalize the candidate reference lake level, in order to determine the reference lakes. 其具体步骤如下(请参阅图1): The specific steps are as follows (see Figure 1):

[0035] (1)建立候选参照湖泊评价指标体系及其等级标准 [0035] (1) establishing a candidate reference lake Evaluation System Level Standard

[0036] 在目标区域内,确定区域内候选参照湖泊,针对湖泊流域的自然植被、湖岸带宽度、农业、点源排放、最小栖息地得分和城市用地等,建立候选参照湖泊评价指标体系及其等级标准分为AF六类,其中,A类为理想的流域和湖泊状态,没有人类干扰的流域;B类是优良的流域和湖泊状态;C类为临界的流域和湖泊状态,有一定的人类干扰,但湖泊水生态系统稳定。 [0036] within the target area, to determine the intra-area candidate reference lakes for natural vegetation Lakes Basin, Lake width, agriculture, point source discharges, the minimum score habitat and urban land, the establishment candidate reference evaluation system and its lakes AF grade standards are divided into six categories, wherein, a and class over the lake basin state, without human interference basin; class B is an excellent state and lake basin; class C and lake basin is critical state, a certain human interference, but the lake water ecosystem stability. D类是低于临界流域和湖泊状态的湖泊,在湖泊或流域有相当的人类干扰出现。 Class D is lower than the critical watershed lakes and lakes state, lake or river basin has a considerable human interference occurs. E类为差的湖泊和流域状态,在湖泊和流域都有相当的人类干扰出现。 Class E lakes and watersheds poor state, in lakes and watersheds have considerable human interference occurs. F类是非常差的湖泊和流域状态,人类干扰大范围的贯穿湖泊和流域。 Class F is very poor and lake basin state, a wide range of human interference and lakes throughout the basin. 细化的参照湖泊评价指标体系及其等级标准参见表1。 Refinement of reference lakes evaluation system and its grading standards in Table 1.

[0037] (2)确定评价指标权重 [0037] (2) determine the evaluation index weight

[0038] 对候选参照湖泊评价指标重要性进行两两比较,建立基于层次结构的模糊互补判断矩阵A= (aij)6X6,且0彡%彡LaiJaji = 1。 [0038] Referring to the candidate evaluation index importance lakes pairwise comparison based hierarchy established fuzzy judgment matrix A = (aij) 6X6, and 0% San San LaiJaji = 1. 对矩阵A进行一致性判断,若矩阵的一致性指标函数 A consistency determination matrix, if the matrix is ​​a function of the consistency index

Figure CN102789546BD00062

小于〇. 01,则进行步骤3,否则须对模糊互补判断矩阵A进行一致性修正。 Less than square. 01, step 3 is performed, it shall be determined for the fuzzy complementary matrix A Consistency. 本发明采用基于模拟退火算法混合加速遗传算的层次分析法,以一致性指标系数(ConsistencyIndexCoefficient)最小化为目标,对各指标的权重进行计算。 The present invention uses hybrid accelerating genetic algorithm Simulated Annealing algorithm AHP to consistency index coefficient (ConsistencyIndexCoefficient) minimize the total weight of each index is calculated. 修正的模糊互补判断矩阵B= (I3ij)6x6各指标的权重为{ω」ί= 1,2,...,6}, 则使下式最小的B为A的最优模糊一致判断矩阵: The modified fuzzy complementary judgment matrix B = (I3ij) weight of each index for the 6x6 {ω "ί = 1,2, ..., 6}, so that the minimum B of the formula A Optimal Fuzzy Consistent Matrix:

Figure CN102789546BD00071

[0042] 设种群个数为η,最大进化代数为Τ,具体运算步骤如下: [0042] The number of population is set η, the maximum evolution algebra Τ, the specific operation steps are as follows:

[0043] 步骤1:实数编码。 [0043] Step 1: Real coding.

[0044] 步骤2 :生成初始父代个体。 [0044] Step 2: generating an initial parent individuals. 在可行域范围内随机产生η个初始父代群体Ρ(0),设置进化代数器t= 0,设置最大进化代数T。 Randomly generated within a range of feasible region η initial parent population Ρ (0), is provided evolution generation t = 0, set the maximum evolution generation T.

[0045] 步骤3:个体评价。 [0045] Step 3: individual evaluation. 计算群体P(t)中各个个体的适应度,第i个个体的适应度F(I) =IAf(I)Xf(1)+0. 000001),目标函数值f(i)越小,表述该个体的适应度F(i)越高。 Calculating for a population the fitness of each individual P (t), the i-th individual fitness F (I) = IAf (I) Xf (1) +0. 000001), the value of the objective function f (i) is smaller, the expression (i) the higher the fitness of the individual F.

[0046] 步骤4:选择运算。 [0046] Step 4: Select operation. 采用最优保存策略和比例选择法相结合的思路,即首先找出当前群体中适应值最高和最低的个体,将最佳个体保留,并用其替换掉最差个体。 Elitist strategy and the use of proportional selection Combination of ideas that first identify the current population to adapt to the highest and lowest of the individual, the individual will retain the best and the worst individual to replace it with. 当前最佳个体不被交叉、变异,直接进入下一代。 The current best individual is not crossover, mutation, directly into the next generation. 将剩下的个体按比例选择法(也叫赌轮盘算法)进行操作,供选择2*n-4个个体。 The remaining proportion of individual selection method (also called roulette algorithm) operates to select for 2 * n-4 individuals. 为增强SAHAGA进行持续全局优化搜索能力,这里把最优秀的个体直接加进子代群体中,进行移民操作后,得到2n-2个子代个体Pl(t)。 After SAHAGA continue to enhance the global optimization search capabilities, where the most outstanding individuals directly added to the progeny groups, immigration was obtained 2n-2 sub-generation individuals Pl (t).

[0047] 步骤5:杂交运算。 [0047] Step 5: hybridization operation. 采用两点交叉法,按杂交概率随机选择一对父代个体作为双亲,并进行随机线性组合,产生2n-2个子代个体P2 (t)。 A two-point cross method, by selecting a pair of hybridization probability parent individuals as a parent, and a random linear combination of 2n-2 to produce progeny individual P2 (t).

[0048]步骤6:变异运算。 [0048] Step 6: mutation operation. 在SAHAGA中,任意父代个体P(t),若其适应度数值F(t)越小, 其选择概率越小,则对该个体进行变异的概率应越大,因此SAHAGA的变异操作是采用变异概率对个体P(t)进行变异,从而得到子代个体P3 (t)。 In SAHAGA, any parent individuals P (t), if the fitness value F (t), the smaller its selection probability, the probability of the individual variability should be greater, so is the use of mutation operations SAHAGA individual mutation probability P (t) for mutation, thereby obtaining offspring P3 (t).

[0049] 步骤7:进化迭代。 [0049] Step 7: Evolution iteration. 由步骤4-6得到的3(2n_2)个子代个体,按其适应度值从大到小进行排序,用上面所产生的最优秀的前10个个体作为初值,利用模拟退火法搜索得到局部最优解,如果所得解满足精度要求,则停止。 Obtained from Step 4-6 3 (2n_2) progeny individuals according to their fitness value decreasing order, with the above produced the best individuals before 10 as the initial value, the simulated annealing method to obtain a local search the optimal solution, if the solution obtained meet the accuracy requirements, is stopped. 否则所得解替代上面所产生的第n,n-1, n-2, . . .,n-9个优秀个体,取排在最前面的η个子代个体作为新的父代群体。 The resulting solution or replacement of the n, n-1, n-2 produced above,..., N-9 an excellent individuals, taken at the top of η progeny individual as a new parent population. 算法转入步骤3。 The algorithm proceeds to step 3.

[0050] 步骤8:引进加速搜索算子,用上面第一次、第二次演化迭代所产生的前s个优秀个体,这一子群所对应的变量变化区间,作为变量新的初始变化区间,SAHAGA算法转入步骤1,如此加速循环,优秀个体的变化区间将逐步调整和收缩,与最优点的距离将越来越近,直到迭代满足算法的终止准则,此时优化个体将逼近最优点。 [0050] Step 8: search operator to accelerate the introduction, for the first time with the above, an excellent self s before the second iteration evolution generated, this change of variable section corresponding subgroup, the new variables as initial change interval , SAHAGA algorithm proceeds to step 1, so acceleration cycle, outstanding individuals will gradually change interval adjustment and contraction, and the optimum distance will be closer and closer, until the termination criterion to meet iterations of the algorithm, then the individual will be close to the best advantage of optimization . 即可得到各评价指标的权重。 You can get each index weights.

[0051] (3)用集对分析方法计算指标、候选参照湖泊与评价等级之间的联系度 [0051] (3) Analysis method of calculation index set, with reference to the connection degree between the candidate and lakes Rank

[0052] 用集对分析方法计算指标j情况下候选参照湖泊i与评价等级k之间的单指标联系度,以及候选参照湖泊i与评价等级间的综合联系度: [0052] collector where index j is calculated by the following with reference to a single candidate of the link between the index i and lakes Rank k, and the degree of contact between the candidate reference integrated lakes and Rank i Method of Analysis:

[0053] [0053]

Figure CN102789546BD00081

[0056]若候选参照湖泊i与评价等级k间的差异性越大,则《ft越接近于-1,样本i倾向于不隶属于评价等级k;若样本i与评价等级k间的同一性越大,则珥^^越接近于1,样本i 越倾向于隶属于评价等级k。 [0056] If the candidate reference to the greater dissimilarity between the lakes and evaluation level k i, the "ft closer to -1, the samples tend not affiliated Rank i k; i identity between samples and if the evaluation level k is larger, the closer to 1 ^^ Joel, the more inclined the sample under evaluation level i k. 故候选参照湖泊i隶属于模糊集"评价等级k"的相对隶属度为Afc = 0,5 + Therefore, the candidate reference lake i belonging to fuzzy sets "evaluation level k" relative degree of membership Afc = 0,5 +

[0057] (4)评价候选参照湖泊等级,确定参照湖泊 [0057] (4) Evaluation of candidate reference level lake, lake determined with reference to

[0058] 评判候选参照湖泊i的等级h。 [0058] Evaluation of candidate reference level h i of the lake. 为避免应用最大隶属度原则进行模糊模式识别所可能造成的失真,提高等级评判的精度,可以把级别特征值, To avoid the application of the principle of maximum membership degrees of the fuzzy pattern recognition may cause distortion and improve accuracy class evaluation, you can put the level of eigenvalues,

Figure CN102789546BD00082

[0060] 作为评判候选参照湖泊i的等级hi。 [0060] As evaluation of candidate reference level hi of the i lake. 为进一步提高等级评价结果的稳妥性,本发明采用置信度准则评判候选参照湖泊i的等级hi: To further improve the sound level of the evaluation of the results, the present invention employs a confidence criterion evaluation of candidate reference level hi i lake of:

Figure CN102789546BD00083

. 得到候选参照湖泊等级后,即可选取适当湖泊作为参照湖泊。 Later. Referring to obtain candidate lake level, as a reference to select a suitable lake lakes.

[0061] 本发明的优点在于采用层次分析法对主观判断矩阵进行客观化修改,使得参照湖泊的确定结果更加科学、客观。 [0061] The advantage of the present invention is that the subjective judgment of the objective matrix modified by AHP, such lakes with reference to the determination result more scientific objective. 其次,本发明采用模拟退火算法混合加速遗传算法对模糊一致判断矩阵进行修正,可以加速判断矩阵的修正速度。 Secondly, the present invention employs simulated annealing algorithm hybrid accelerating genetic algorithm fuzzy consistent judgment matrix correction, the correction speed can be accelerated Analyzing matrix. 最后本发明运用置信度准则评判候选参照湖泊等级,从而进一步提高等级评价结果的稳妥行。 Finally, the present invention is the use of confidence criterion evaluation of candidate reference lake levels, thereby further improving the sound level of the evaluated results.

[0062]下面以云贵湖区参照湖泊的确定为实施案例进一步说明本发明。 [0062] In the following is determined with reference to the lake to lake Guizhou case further embodiment of the present invention is described.

[0063] 1)建立候选参照湖泊评价指标体系及其等级标准 [0063] 1) establishing a candidate reference lake Evaluation System Level Standard

[0064]选取云贵湖区9个湖泊作为候选参照湖泊,采用主成分分析方法,确定候选参加湖泊评价指标,根据候选参照湖泊评价指标体系(见表1),采用调查、勘测和资料收集等方法,获得湖泊流域的自然植被、湖岸带宽度、农业、点源排放、最小栖息地得分和城市用地等指标数据,如表2。 [0064] Select Guizhou Lakes 9 lakes as candidate reference lakes, principal component analysis, evaluation index determining a candidate to participate in lakes, with reference to the candidate evaluation system according lakes (Table 1), using surveys, survey data collection, and the like, natural vegetation index data obtained lakes basin lakeshore width, agriculture, point source emissions, and the minimum score habitat urban land use, as shown in table 2.

[0065] 2)确定评价指标权重 [0065] 2) determining evaluation weights

[0066] 对候选参照湖泊评价指标重要性进行两两比较,建立基于层次结构的模糊互补判断矩阵A, [0066] Referring to the candidate evaluation index importance lakes pairwise comparison, establishing a hierarchy based on fuzzy complementary judgment matrix A,

Figure CN102789546BD00091

[0068]对矩阵A进行一致性判断,CIF= 0. 011 > 0. 01,则须对判断矩阵A进行一致性修正。 [0068] A consistency determination matrix, CIF = 0. 011> 0. 01, matrix A shall be determined on Consistency. 采用基于模拟退火算法混合加速遗传算对以一致性指标系数最小化为目标的最优化模型进行计算,计算出各指标修正后的权重ω= [0.20,0.25,0. 25,0.11,0.10,0.09]。 Using simulated annealing hybrid accelerating genetic algorithm optimization model for consistency index coefficient minimization target is calculated, the calculated weight of each index correction weight ω = [0.20,0.25,0. 25,0.11,0.10,0.09 ].

[0069] 3)用集对分析方法计算指标、候选参照湖泊与评价等级之间的联系度 [0069] 3) Calculation method of analysis indicators set, the connection degree between the candidate reference lakes and Rank

[0070] 将候选参照湖泊评价指标值与评价指标权重带入公式中,得到候选参照湖泊隶属于模糊集"评价等级k"的相对隶属度为uik。 [0070] The candidate reference index value and weight Evaluation Evaluation Index into equation Lake, Lake belonging to obtain fuzzy sets of candidate reference "evaluation level k" relative degree of membership uik.

[0071] V1= [0. 9000 0. 3000 0. 1000 0. 0000 0. 0000 0. 0000 0. 0000]; [0071] V1 = [0. 9000 0. 3000 0. 1000 0. 0000 0. 0000 0. 0000 0. 0000];

[0072]V2= [0. 9000 0. 4279 0. 1000 0. 0000 0. 0000 0. 0000 0. 0000]; [0072] V2 = [0. 9000 0. 4279 0. 1000 0. 0000 0. 0000 0. 0000 0. 0000];

[0073]V3= [0. 2500 0. 2168 0. 3000 0. 0832 0. 3290 0. 4500 0. 1210]; [0073] V3 = [0. 2500 0. 2168 0. 3000 0. 0832 0. 3290 0. 4500 0. 1210];

[0074]V4= [0. 2500 0. 2099 0. 3000 0. 1631 0. 3600 0. 3770 0. 0900]; [0074] V4 = [0. 2500 0. 2099 0. 3000 0. 1631 0. 3600 0. 3770 0. 0900];

[0075]V5= [0. 2500 0. 1000 0. 2588 0. 2000 0. 1952 0. 4500 0. 2960]; [0075] V5 = [0. 2500 0. 1000 0. 2588 0. 2000 0. 1952 0. 4500 0. 2960];

[0076]V6= [0. 4775 0. 3165 0. 3325 0. 3393 0. 1900 0. 0900 0. 0000]; [0076] V6 = [0. 4775 0. 3165 0. 3325 0. 3393 0. 1900 0. 0900 0. 0000];

[0077] V7= [0. 2500 0. 1000 0. 1000 0. 0000 0. 1856 0. 5348 0. 4644]; [0077] V7 = [0. 2500 0. 1000 0. 1000 0. 0000 0. 1856 0. 5348 0. 4644];

[0078] V8= [0. 5050 0. 5483 0. 4050 0. 0195 0. 0000 0. 0900 0. 0900]; [0078] V8 = [0. 5050 0. 5483 0. 4050 0. 0195 0. 0000 0. 0900 0. 0900];

[0079] V9= [0. 3631 0. 3000 0. 4157 0. 3600 0. 1313 0. 0900 0. 0900]; [0079] V9 = [0. 3631 0. 3000 0. 4157 0. 3600 0. 1313 0. 0900 0. 0900];

[0080] V10= [0. 2500 0. 1000 0. 1418 0. 2000 0. 1582 0. 4041 0. 4500]; [0080] V10 = [0. 2500 0. 1000 0. 1418 0. 2000 0. 1582 0. 4041 0. 4500];

[0081] V11= [0. 2261 0. 4563 0. 3339 0. 3437 0. 3500 0. 2000 0. 0900]; [0081] V11 = [0. 2261 0. 4563 0. 3339 0. 3437 0. 3500 0. 2000 0. 0900];

[0082]V12= [0. 3487 0. 3220 0. 3713 0. 3380 0. 1900 0. 0900 0. 0900]; [0082] V12 = [0. 3487 0. 3220 0. 3713 0. 3380 0. 1900 0. 0900 0. 0900];

[0083]V13= [0. 2685 0. 3000 0. 3737 0. 3600 0. 2678 0. 0900 0. 0900]; [0083] V13 = [0. 2685 0. 3000 0. 3737 0. 3600 0. 2678 0. 0900 0. 0900];

[0084]V14= [0. 2500 0. 1000 0. 1000 0. 0000 0. 0454 0. 4747 0. 6046]; [0084] V14 = [0. 2500 0. 1000 0. 1000 0. 0000 0. 0454 0. 4747 0. 6046];

[0085]V15= [0. 0000 0. 2558 0. 4500 0. 4220 0. 3500 0. 2552 0. 2000]; [0085] V15 = [0. 0000 0. 2558 0. 4500 0. 4220 0. 3500 0. 2552 0. 2000];

[0086]V16= [0. 3051 0. 3073 0. 5389 0. 3528 0. 1560 0. 0900 0. 0000]; [0086] V16 = [0. 3051 0. 3073 0. 5389 0. 3528 0. 1560 0. 0900 0. 0000];

[0087]V17= [0. 2500 0. 2149 0. 3000 0. 1181 0. 3258 0. 4170 0. 1243]; [0087] V17 = [0. 2500 0. 2149 0. 3000 0. 1181 0. 3258 0. 4170 0. 1243];

[0088]V18=[0.7990 0.4536 0.1110 0.0000 0.0000 0.0900 0. 0900]; [0088] V18 = [0.7990 0.4536 0.1110 0.0000 0.0000 0.0900 0. 0900];

[0089]V19= [0. 2500 0. 0601 0. 3645 0. 4899 0. 2755 0. 1732 0. 1100]; [0089] V19 = [0. 2500 0. 0601 0. 3645 0. 4899 0. 2755 0. 1732 0. 1100];

[0090]V20= [0. 2500 0. 1803 0. 3000 0. 2820 0. 3600 0. 2878 0. 0900]; [0090] V20 = [0. 2500 0. 1803 0. 3000 0. 2820 0. 3600 0. 2878 0. 0900];

[0091]V21= [0. 3477 0. 4013 0. 5623 0. 2588 0. 0000 0. 0900 0. 0900]; [0091] V21 = [0. 3477 0. 4013 0. 5623 0. 2588 0. 0000 0. 0900 0. 0900];

[0092]V22= [0. 2500 0. 1529 0. 3000 0. 3228 0. 3270 0. 2743 0. 1230]; [0092] V22 = [0. 2500 0. 1529 0. 3000 0. 3228 0. 3270 0. 2743 0. 1230];

[0093]V23= [0. 3400 0. 3315 0. 3000 0. 1880 0. 3600 0. 2305 0. 0000]; [0093] V23 = [0. 3400 0. 3315 0. 3000 0. 1880 0. 3600 0. 2305 0. 0000];

[0094]v24 = [0. 5000 0. 1000 0. 1000 0. 1136 0. 2000 0. 2569 0. 2000] ; [0094] v24 = [0. 5000 0. 1000 0. 1000 0. 1136 0. 2000 0. 2569 0. 2000];

[0095] V25= [0. 9000 0. 2670 0. 1000 0. 0000 0. 0000 0. 0000 0. 0000] ; [0095] V25 = [0. 9000 0. 2670 0. 1000 0. 0000 0. 0000 0. 0000 0. 0000];

[0096]v26 = [0. 1536 0. 5500 0. 3964 0. 3345 0. 3600 0. 1155 0. 0900] ; [0096] v26 = [0. 1536 0. 5500 0. 3964 0. 3345 0. 3600 0. 1155 0. 0900];

[0097] V27= [0. 3400 0. 3837 0. 3000 0. 1745 0. 3600 0. 1918 0. 0000] ; [0097] V27 = [0. 3400 0. 3837 0. 3000 0. 1745 0. 3600 0. 1918 0. 0000];

[0098] 4)评价候选参照湖泊等级,确定参照湖泊 [0098] 4) Evaluation of candidate reference level lake, lake determined with reference to

[0099] 将候选参照湖泊隶属于模糊集"评价等级k"的相对隶属度进行置信度准则判断, 确定候选参照湖泊等级,结果见表3。 [0099] The fuzzy sets of candidate reference lakes under "evaluation level k" relative degree of membership for determining confidence criterion, determining a candidate reference level of the lake, the results shown in Table 3.

[0100] 依据候选参照湖泊等级确定参照湖泊为碧塔海、泸沽湖、叠溪海子。 [0100] determined based on candidate reference Bitahai lakes, lakes Luguhu reference level, diexi lake.

[0101] 表1参照湖泊评价指标体系及其等级标准 [0101] Referring to Table 1 lake Evaluation System Level Standard

[0102] [0102]

Figure CN102789546BD00101

[0103] 表2候选参照湖泊评价指标数据 [0103] Table 2 Evaluation of candidate reference data lakes

[0104] [0104]

Figure CN102789546BD00102

[0105] 表3候选参照湖泊定量化评估结果 [0105] Referring to Table 3 candidate lake quantitative assessment

[0106] [0106]

Figure CN102789546BD00111

Claims (5)

1. 一种基于人类扰动强度的参照湖泊定量化确定方法,其主要步骤包括: 1) 在目标区域内,确定区域内候选参照湖泊,应用主成分分析方法确定湖泊流域人类扰动强度的指标,建立候选参照湖泊评价指标体系及其等级标准; 2) 确定评价指标权重对候选参照湖泊评价指标重要性进行两两比较,建立基于层次结构的模糊互补判断矩阵A,对矩阵A进行一致性判断;其中矩阵A= (¾) 6X6,且O彡aij彡I,aij+aji = 1 ;式中的i、j为候选参照湖泊评价指标; 确定评价指标权重是采用基于模拟退火算法混合加速遗传算法的层次分析法,以一致性指标系数最小化为目标,对各指标的权重进行计算;修正的模糊互补判断矩阵B= 0¾) 6X6各指标的权重为{ωiIi= 1,2,…,6},贝丨J使下式最小的B为A的最优模糊一致判断矩阵: 1. A method of determining the quantitative reference lakes based on the perturbation intensity human, which mainly comprises: 1) within the target area, the candidate region is determined with reference to the lake, the principal component analysis method for determining index perturbation intensity human lake basin established Referring candidate lake evaluation system level standard; 2) determining evaluation weights candidates pairwise comparison evaluation reference importance lakes, establishing fuzzy complementary judgment matrix a hierarchy, the consistency of the matrix a is determined; wherein matrix a = (¾) 6X6, and O San aij San I, aij + aji = 1; formula i, j reference lake evaluation as a candidate; determining evaluation weights are hybrid accelerating genetic algorithm simulated annealing algorithm level analysis, consistency index coefficient to minimize the total weight of each index was calculated; the modified fuzzy judgment matrix B = weight of each index 0¾) 6X6 weight {ωiIi = 1,2, ..., 6}, Tony Shu J so that the minimum B of the formula a optimal Fuzzy consistent matrix:
Figure CN102789546BC00021
3) 用集对分析方法计算候选参照湖泊评价指标情况下,候选参照湖泊与评价等级之间的单指标联系度,以及候选参照湖泊与评价等级间的综合联系度; 4) 评价候选参照湖泊等级,确定参照湖泊。 3) Analysis calculated by reference to the evaluation of candidate sets and lakes, with reference to a single candidate of the link between the index and the evaluation level of the lake, and the degree of contact between the synthesis candidate reference lakes and Rank; 4) Evaluation of candidate reference level Lake , determined with reference to the lake.
2. 根据权利要求1所述基于人类扰动强度的参照湖泊定量化确定方法,其中,湖泊流域人类扰动强度的指标包括:湖泊流域的自然植被、湖岸带宽度、农业、点源排放、最小栖息地得分和城市用地;建立的候选参照湖泊评价指标体系及其等级标准分为AF六类,其中: A类为理想的流域和湖泊状态,没有人类干扰的流域; B类是优良的流域和湖泊状态; C类为临界的流域和湖泊状态,有一定的人类干扰,但湖泊水生态系统稳定; D类是低于临界流域和湖泊状态的湖泊,在湖泊或流域有相当的人类干扰出现; E类为差的湖泊和流域状态,在湖泊和流域都有相当的人类干扰出现; F类是非常差的湖泊和流域状态,人类干扰大范围的贯穿湖泊和流域。 2. The method of claim 1 determining the quantitative reference lakes based on human perturbation intensity, wherein the index perturbation intensity human lake basin comprising: a lake basin natural vegetation, Lake width, agriculture, point source emissions, minimum habitat score, urban areas; candidate reference lake established grading and evaluation system is divided into six AF, wherein: a and class over the lake basin state, without human interference basin; class B is an excellent state and lake basin ; class C the critical state and lake basin, there are certain human interference, but the lake water ecosystem stability; class D lakes below the critical state and lake basin, or lake basin considerable human interference occurs; class E lake basin and the difference state, lake basin and has a considerable human interference occurs; lake basin and class F state is very bad, a wide range of human interference and lakes throughout the basin.
3. 根据权利要求1所述基于人类扰动强度的参照湖泊定量化确定方法,其中,采用的集对分析方法如下式: According to claim 1 based on the strength of the perturbation method for determining human lake quantitative reference, wherein the set of analysis employed the following formula:
Figure CN102789546BC00022
Figure CN102789546BC00031
式中,i是候选参照湖泊,j代表候选参照湖泊评价指标,k是评价等级,uiA是评价等级之间的单指标联系度。 Wherein, i is the candidate reference lakes, j representative of the candidate evaluation reference lakes, k is the evaluation grade, uiA single connection degree between the evaluation index level.
4. 根据权利要求1所述基于人类扰动强度的参照湖泊定量化确定方法,其中,评判候选参照湖泊的等级时,将级别特征值 4. The quantitative determination based on the reference intensity lakes human perturbation method according to claim 1, wherein the evaluation of candidate reference level of the lake, the level of the characteristic value
Figure CN102789546BC00032
作为评判候选参照湖泊评价指标的等级,得到候选参照湖泊等级后,即可选取适当湖泊作为参照湖泊; 式中,h是候选参照湖泊i的等级,Vik是候选参照湖泊i隶属于模糊集评价等级k的相对隶属度,k是候选参照湖泊的评价等级。 After a candidate reference level evaluation Evaluation lake, lake obtained candidate reference level, as a reference to select a suitable lake lakes; where, h is the candidate reference level i of the lake, lake Vik candidate reference fuzzy sets belonging Rank i relative membership degree k, k is the candidate with reference to the evaluation level of the lake.
5. 根据权利要求4所述基于人类扰动强度的参照湖泊定量化确定方法,其中,评判候选参照湖泊的等级时,采用置信度准则评判候选参照湖泊i的等级比: ",知[0A0.7]};得到候选参照湖泊等级后,即可选取适当湖泊作为参照湖泊。 5. The quantitative determination based on the reference intensity lakes human perturbation method of claim 4, wherein the evaluation of candidate reference level lakes, using confidence criterion evaluation of candidate reference level lake i ratio: "know [0A0.7 ]}; after obtaining the candidate reference level lake, lake as a reference to select the appropriate lake.
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