Fish school suitability index weight determination method and system, electronic equipment and computer readable storage medium
By constructing a hierarchical structure diagram and a judgment matrix to assign weights to fish school suitability indicators, the problem of incomplete fish school habitat evaluation was solved, and the accuracy and effectiveness of fish habitat evaluation in complex water networks of tributaries and high-altitude and cold regions were achieved.
Patent Information
- Application Number
- CN202511364211.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-23
- Publication Date
- 2026-01-13
Smart Images
Figure CN121328906A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to a fish population suitability index weight determination method, system, electronic device and computer readable storage medium, belonging to the technical field of water conservancy and hydropower development fish habitat protection. BACKGROUND
[0002] In recent years, with the deepening of ecological civilization construction, the ecological environment protection problem in water conservancy and hydropower development has been increasingly concerned. In the process of river cascade hydropower construction, especially when the main stream and tributaries are developed at the same time, fish passage facilities, ecological scheduling, artificial propagation and release and other fish compensation measures are difficult to fundamentally solve the problem of loss of fish diversity due to habitat destruction and fragmentation, due to the constraints of current scientific understanding, technical level, management difficulty and other factors. Therefore, the replacement habitat protection of the combined type of main stream and tributary has become a new idea for habitat protection in hydropower development. The research results of habitat suitability evaluation and restoration at this stage are mainly concentrated in the analysis of key environmental factors of habitat for a rare and endangered species or a few species, habitat suitability evaluation and other aspects.
[0003] At present, relevant theories and technical schemes have been established for tributary replacement habitat and its construction, and habitat restoration and adaptability evaluation theories mainly focus on rare and endangered species in low-altitude areas, but the coupling mechanism between key factors of fish habitat and reservoir operation and scheduling under complex water network of main stream and tributary, especially in the variable backwater zone of reservoir tail, has not been studied, and there is no research data and habitat restoration and protection case of fish in high-altitude and high-cold area of Tibet under complex water network of main stream and tributary. Therefore, the existing fish habitat evaluation results are not comprehensive and effective. Therefore, it is urgent to propose a fish population suitability index weight determination method, system, electronic device and computer readable storage medium to ensure the accuracy and effectiveness of fish habitat evaluation results. SUMMARY
[0004] To solve the above technical problems, the present application provides a fish population suitability index weight determination method, system, electronic device and computer readable storage medium.
[0005] The present application is realized by the following technical solutions: The present application provides a fish population suitability index weight determination method in the first aspect, comprising the following steps: Step 1, obtaining a hierarchical structure diagram of fish population suitability index; Step 2, constructing a judgment matrix of each level in the hierarchical structure diagram; Step 3, determining the initial weight of each element in each level to the previous level according to the judgment matrix of each level; Step 4, determining the weight of each index value in the fish population suitability index based on the initial weight of each element in each level to the previous level; The hierarchical structure diagram comprises, from top to bottom, a target layer, a sub-target layer, an index layer and a calculation parameter layer. The fish population suitability index comprises habitat suitability, river connectivity, ecological health and important habitat suitability.
[0006] The target layer comprises a suitability index. The sub-target layer comprises habitat suitability, river connectivity, ecological health and important habitat suitability. The index layer comprises hydrological condition suitability, hydrodynamic condition suitability, water environment suitability, river topography suitability, river bank ecological suitability, longitudinal connectivity, lateral connectivity, biodiversity, three-field habitat suitability. The calculation parameter layer comprises flow, water temperature, flow velocity, water depth, water surface width, flow velocity and depth combination characteristics, water quality, water quality physical properties, sinuosity, deep pool and shoal, bottom type, habitat complexity, river bed gradient, river bank stability, river change, vegetation diversity, human activity intensity, river bank land use type, longitudinal connectivity index, lateral connectivity index, fish species, fish resource amount, endangered species protection species, fish three-field size, fish three-field species. The habitat suitability in the sub-target layer comprises the hydrological condition suitability, the hydrodynamic condition suitability, the water environment suitability, the river topography suitability, the river bank ecological suitability in the index layer. The river connectivity in the sub-target layer comprises the longitudinal connectivity and the lateral connectivity in the index layer. The ecological health in the sub-target layer comprises the biodiversity in the index layer. The important habitat suitability in the sub-target layer comprises the three-field habitat suitability in the index layer. The hydrological condition suitability in the index layer comprises the flow and the water temperature in the calculation parameter layer. The hydrodynamic condition suitability in the index layer comprises the flow velocity, the water depth, the water surface width and the flow velocity and depth combination characteristics in the calculation parameter layer. The water environment suitability in the index layer comprises the water quality and the water quality physical properties in the calculation parameter layer. The river topography suitability in the index layer comprises the sinuosity, the deep pool and shoal, the bottom type, the habitat complexity and the river bed gradient in the calculation parameter layer. The river bank ecological suitability in the index layer comprises the river bank stability, the river change, the vegetation diversity, the human activity intensity and the river bank land use type in the calculation parameter layer. The longitudinal connectivity in the index layer comprises a longitudinal connectivity index in the parameter layer; The transverse connectivity in the index layer comprises a transverse connectivity index in the parameter layer; The biodiversity in the index layer comprises a fish species category, a fish resource amount, and a protected endangered species category in the parameter layer. The three-field habitat suitability in the index layer comprises a fish three-field size and a fish three-field species category in the parameter layer.
[0007] The method for constructing the judgment matrix of each layer in the hierarchical structure in step 2 is that whether the number of elements corresponding to each element in the target layer, the sub-target layer and the index layer in the next layer is greater than or equal to 3 is judged respectively, if yes, the analytic hierarchy process is used to construct the judgment matrix of each layer, otherwise, the weight is directly assigned based on the preset value.
[0008] The judgment matrix of each layer comprises a sub-target layer judgment matrix, an index layer judgment matrix, a calculation parameter judgment matrix of hydrodynamic condition suitability, a calculation parameter judgment matrix of river topography and geomorphology suitability, a calculation parameter judgment matrix of river bank ecology suitability, and a calculation parameter judgment matrix of biodiversity.
[0009] The calculation formula of the judgment matrix of each layer is as follows: , In the formula, is the rth judgment matrix in the qth layer, is the importance ratio of the nth element to the nth element.
[0010] The step 3 comprises the following steps: Step 31, determining the characteristic vector corresponding to each judgment matrix according to the value of each row element in each judgment matrix; Step 32, determining the initial weight of each element in each layer to the previous layer according to the characteristic vector corresponding to each judgment matrix.
[0011] Each judgment matrix is a judgment matrix that has passed consistency check.
[0012] The step 4 comprises the following steps: Step 41, determining the weight proportion of each element in the sub-target layer according to the initial weight of each element in the sub-target layer to the previous layer; Step 42, determining the weight proportion of each element in the index layer under the weight proportion of each element in the sub-target layer; Step 43, determining the weight proportion of each element in the parameter layer under the weight proportion of each element in the index layer; Step 44, based on the weight proportion of each element in the calculation parameter hierarchy, and the initial weight of each element in the calculation parameter hierarchy to the upper level, the weight of each calculation parameter in the fish population suitability index is determined; Step 45, based on the weight of each calculation parameter in the fish population suitability index, the weight of each index value in the fish population suitability index is determined.
[0013] The second aspect of the present application provides a fish population suitability index weight determination system, comprising: The acquisition module is used for acquiring a hierarchical structure diagram of the fish population suitability index; The construction module is used for constructing a judgment matrix of each level in the hierarchical structure diagram; The first determination module is used for determining the initial weight of each element in each level to the upper level according to the judgment matrix of each level; The second determination module is used for determining the weight of each index value in the fish population suitability index based on the initial weight of each element in each level to the upper level; The hierarchical structure diagram comprises a target layer, a sub-target layer, an index layer and a calculation parameter layer from top to bottom. The fish population suitability index comprises habitat suitability, river connectivity, ecological health and important habitat suitability.
[0014] The third aspect of the present application is an electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor executes the computer program to realize the method of the first aspect.
[0015] A computer readable storage medium, having a computer program stored thereon, wherein the computer program is executed by a processor to realize the method of the first aspect.
[0016] The present application has the beneficial effects that different indexes are respectively given weight values to reflect their relative importance, so as to ensure the accuracy and effectiveness of the fish habitat evaluation result. Meanwhile, in the hierarchical structure diagram of the fish population suitability index, all factors affecting the fish population suitability are covered as much as possible, so as to ensure the comprehensiveness, accuracy and effectiveness of the fish habitat evaluation result. BRIEF DESCRIPTION OF DRAWINGS
[0017] Figure 1 The method flowchart of the present application; Figure 2 The hierarchical structure diagram of the fish population suitability index of the present application; Figure 3 The structure schematic diagram of the system of the present application; In the figure: 100 - acquisition module, 200 - construction module, 300 - first determination module, 400 - second determination module. DETAILED DESCRIPTION
[0018] The technical solutions of the present application are further described below, but the scope of protection is not limited to the description.
[0019] Example one: As Figure 1 shown, the fish population suitability index weight determination method comprises the following steps: Step 1, obtaining a hierarchical structure diagram of fish population suitability indexes; Step 2, constructing a judgment matrix of each level in the hierarchical structure diagram; Step 3, determining the initial weight of each element in each level to the upper level according to the judgment matrix of each level; Step 4, determining the weight of each index value in the fish population suitability index based on the initial weight of each element in each level to the upper level; Among them, the hierarchical structure diagram includes target layer, sub-target layer, index layer and calculation parameter layer from top to bottom; The fish population suitability index includes habitat suitability, river connectivity, ecological health and important habitat suitability.
[0020] Different indexes are respectively assigned weight values to reflect their relative importance to ensure the accuracy and effectiveness of the fish habitat evaluation results.
[0021] The hierarchical structure diagram of fish population suitability indexes is as shown in Figure 2 .
[0022] The target layer includes suitability index; The sub-target layer includes habitat suitability, river connectivity, ecological health and important habitat suitability; The index layer includes hydrological condition suitability, hydrodynamic condition suitability, water environment suitability, river topography suitability, river bank ecology suitability, longitudinal connectivity, lateral connectivity, biodiversity, three-field habitat suitability; The calculation parameter layer includes flow, water temperature, flow rate, water depth, water surface width, flow rate and depth combination characteristics, water quality, water quality physical properties, sinuosity, deep pool and shoal, bottom type, habitat complexity, river bed gradient, river bank stability, river change, vegetation diversity, human activity intensity, river bank land use type, longitudinal connectivity index, lateral connectivity index, fish species, fish resources, endangered species, fish three-field size, fish three-field species; The habitat suitability in the sub-target layer includes hydrological condition suitability, hydrodynamic condition suitability, water environment suitability, river topography suitability, and river bank ecological suitability in the index layer. The river channel connectivity in the sub-target layer includes longitudinal connectivity and transverse connectivity in the index layer. The ecological health in the sub-target layer includes biodiversity in the index layer. The important habitat suitability in the sub-target layer includes three-field habitat suitability in the index layer. The hydrological condition suitability in the index layer includes flow and water temperature in the calculation parameter layer. The hydrodynamic condition suitability in the index layer includes flow velocity, water depth, water surface width, and flow velocity-depth combination characteristics in the calculation parameter layer. The water environment suitability in the index layer includes water quality and water quality physical properties in the calculation parameter layer. The river topography suitability in the index layer includes sinuosity, deep pool and shallow beach, bottom type, habitat complexity, and river bed gradient in the calculation parameter layer. The river bank ecological suitability in the index layer includes river bank stability, river channel change, vegetation diversity, human activity intensity, and river bank land use type in the calculation parameter layer. The longitudinal connectivity in the index layer includes longitudinal connectivity index in the calculation parameter layer. The transverse connectivity in the index layer includes transverse connectivity index in the calculation parameter layer. The biodiversity in the index layer includes fish species, fish resource amount, and endangered species in the calculation parameter layer. The three-field habitat suitability in the index layer includes fish three-field size and fish three-field species in the calculation parameter layer.
[0023] In the hierarchical structure diagram of the fish population suitability index, all factors affecting the fish population suitability are covered as much as possible, and the comprehensiveness, accuracy and effectiveness of the fish population habitat evaluation result are ensured.
[0024] The method for constructing the judgment matrix of each layer in the hierarchical structure diagram in step 2 is that whether the number of elements corresponding to each element in the target layer, the sub-target layer and the index layer in the next layer is greater than or equal to 3, if yes, the analytic hierarchy process is used to construct the judgment matrix of each layer, otherwise the weight is directly assigned based on the preset value.
[0025] It should be noted that when the number of elements corresponding to each element in the target layer, the sub-target layer and the index layer in the next layer is less than 3, the average random consistency index RI value cannot be obtained for random consistency ratio CR test. Therefore, when the number of elements is less than 3, the weight is directly assigned based on the preset value.
[0026] The judgment matrix of each level includes: the sub-target layer judgment matrix, the index layer judgment matrix, the calculation parameter judgment matrix of the hydrodynamic condition suitability, the calculation parameter judgment matrix of the river topography and geomorphology suitability, the calculation parameter judgment matrix of the river bank ecology suitability, and the calculation parameter judgment matrix of the biological diversity.
[0027] The calculation formula of the judgment matrix of each level is as follows: , In the formula, is the rth judgment matrix in the q level, is the importance ratio of the nth element to the nth element.
[0028] Based on the above, the sub-target layer can generate one judgment matrix, and the sub-target layer judgment matrix is shown in Table 1: Table 1 Sub-target layer judgment matrix
[0029] The index layer can generate one judgment matrix, and the index layer judgment matrix is shown in Table 2: Table 2 Index layer judgment matrix
[0030] The calculation parameter layer can generate four judgment matrices. Among them, the calculation parameter judgment matrix of the hydrodynamic condition suitability is shown in Table 3: Table 3 Calculation parameter judgment matrix of hydrodynamic condition suitability
[0031] The calculation parameter judgment matrix of the river topography and geomorphology suitability is shown in Table 4: Table 4 Calculation parameter judgment matrix of river topography and geomorphology suitability
[0032] The calculation parameter judgment matrix of the river bank ecology suitability is shown in Table 5: Table 5 Calculation parameter judgment matrix of river bank ecology suitability
[0033] The calculation parameter judgment matrix of the biological diversity is shown in Table 6: Table 6. Judgment matrix of calculation parameters of biodiversity
[0034] The step 3 comprises the following steps: Step 31, determining the eigenvector corresponding to each judgment matrix according to the value of each row element in the judgment matrix.
[0035] It should be noted that the elements of each layer in the hierarchical structure diagram can be compared with each other in turn with respect to the elements of the previous layer, and the importance is valued, and the judgment matrix is established accordingly. In the judgment matrix, a ij is the importance comparison result of element i and element j, where a ii = 1, a ij = 1 / a ji . The relative importance of two indicators is valued by using a scale of 1-9, and the specific scale and meaning are shown in Table 7: Table 7. Specific scale and meaning
[0036] Step 32, determining the initial weight of each element in each layer to the previous layer according to the eigenvector corresponding to each judgment matrix. It comprises the following steps: a. Calculate the product of the elements in the i-th row of the judgment matrix , b. Calculate the nth root of , Solving the nth root of each row element, the eigenvector corresponding to each judgment matrix is obtained.
[0037] Further, the initial weight of each element in each layer to the previous layer is determined according to the eigenvector corresponding to each judgment matrix, and the calculation formula of the initial weight of the i-th row element is as follows: .
[0038] Each of the judgment matrices is a judgment matrix that has passed consistency check.
[0039] It should be noted that in order to ensure the credibility of the weight, the judgment matrix needs to be checked for consistency. According to the matrix theory, the negative average value of the remaining eigenvalues other than the largest eigenvalue of the judgment matrix is introduced in the analytic hierarchy process as an index for measuring the deviation of the judgment matrix from consistency. The specific inspection is as follows: a. Calculate the largest eigenvalue of the judgment matrix : , wherein, is the initial weight vector to be solved; b. Calculate the consistency index : , c. Calculate the random consistency ratio CR: , wherein: CI is the consistency index, and RI is the average random consistency index.
[0040] Compare the CR value with 0.1, when CR < 0.1, it is judged that the judgment matrix has satisfactory consistency, that is, the initial weight coefficient; otherwise, the values of the judgment matrix need to be adjusted again until the satisfactory consistency is obtained.
[0041] In the embodiment of the present disclosure, for the sub-target layer judgment matrix, the random consistency ratio CR value = 0.076 < 0.1 after consistency test, and the judgment matrix has satisfactory consistency. Therefore, the weight of each sub-target layer relative to the target layer, that is, the initial weight is shown in Table 8; Table 8 Weight of each sub-target layer relative to the target layer
[0042] For the index layer judgment matrix, the random consistency ratio CR value = 0.09 < 0.1 after consistency test, and the judgment matrix has satisfactory consistency. Therefore, the weight of each index layer relative to the sub-target layer, that is, the initial weight is shown in Table 9: Table 9 Weight of each index layer relative to the sub-target layer
[0043] Since the number of index layers of river connectivity is 2, the random consistency ratio test cannot be performed, and therefore the weight is directly assigned. The initial weights of longitudinal connectivity and transverse connectivity are 83% and 17%, respectively. Ecological health and important habitat suitability each have only one index layer, and therefore the weight distribution is not needed.
[0044] At the same time, the number of calculation parameters of hydrological condition suitability is 2, and the random consistency ratio test cannot be performed, and therefore the weight is directly assigned. The initial weights of flow and water temperature are 20% and 80%, respectively.
[0045] For the calculation parameter judgment matrix of hydrodynamic condition suitability, the random consistency ratio CR value = 0.02 < 0.1 after consistency test, and the judgment matrix has satisfactory consistency. Therefore, the weight of each index layer relative to the sub-target layer, that is, the initial weight is shown in Table 10: The weight of each index layer relative to the sub-target layer is shown in Table 10
[0046] It should be noted that the number of calculation parameters of water environment suitability is 2, which cannot be subjected to random consistency ratio test, and therefore the weight is directly assigned, and the initial weights of water quality and water quality physical properties are 50% and 50%, respectively.
[0047] For the calculation parameter judgment matrix of river terrain suitability, the random consistency ratio CR value is 0.04<0.1 through consistency test, and the judgment matrix has satisfactory consistency. Therefore, the weight of each index layer relative to the sub-target layer, i.e. the initial weight, is shown in Table 11: Table 11 The weight of each index layer relative to the sub-target layer
[0048] For the calculation parameter judgment matrix of river bank ecology suitability, the random consistency ratio CR value is 0.03<0.1 through consistency test, and the judgment matrix has satisfactory consistency. Therefore, the weight of each index layer relative to the sub-target layer, i.e. the initial weight, is shown in Table 12: Table 12 The weight of each index layer relative to the sub-target layer
[0049] It should be noted that both longitudinal connectivity and horizontal connectivity have only one calculation parameter, and therefore weight distribution is not needed.
[0050] For the calculation parameter judgment matrix of biological diversity, the random consistency ratio CR value is 0.01<0.1 through consistency test, and the judgment matrix has satisfactory consistency. Therefore, the weight of each index layer relative to the sub-target layer, i.e. the initial weight, is shown in Table 13: Table 13 The weight of each index layer relative to the sub-target layer
[0051] It should be noted that the number of calculation parameters of fish three-field habitat suitability is 2, which cannot be subjected to random consistency ratio test, and therefore the weight is directly assigned, and the initial weights of fish three-field scale and fish three-field species are 67% and 33%, respectively.
[0052] The step 4 comprises the following steps: Step 41, determining the weight proportion of each element in the sub-target layer according to the initial weight of each element in the sub-target layer to the upper level; Step 42, determining the weight proportion of each element in the index layer under the weight proportion of each element in the sub-target layer; Step 43: Determine the weight ratio of each element in the indicator level and then calculate the weight ratio of each element in the parameter level. Step 44: Based on the weight ratio of each element in the calculation parameter hierarchy and the initial weight of each element in the calculation parameter hierarchy to its upper level, determine the weight of each calculation parameter in the fish population suitability index. Step 45: Determine the weight of each index value in the fish school suitability index based on the weight of each calculated parameter in the fish school suitability index.
[0053] It should be noted that a layer-by-layer weighting method is adopted, that is, first calculate the weight of the sub-target layer to the target layer, then calculate the weight of the indicator layer to the sub-target layer, calculate the weight of the parameter layer to the indicator layer, and finally calculate the total weight value of each calculation parameter, thereby obtaining the weight of each indicator value in the fish swarm suitability index.
[0054] It should be noted that, based on the weight ratios among the indicators at each level in Tables 8 to 13 above, the total weight of each calculation parameter can be obtained, as shown in Table 14: Table 14 shows the total weight of each calculation parameter.
[0055] Based on the weights of each calculation parameter in Table 14, the weights of each element in the sub-target layer can be obtained, which means the weights of each index value in the fish swarm suitability index.
[0056] In summary, the fish population suitability index weight determination method proposed in this embodiment accurately assigns different weight values to different indicators to reflect their relative importance, thereby ensuring the accuracy and effectiveness of the evaluation results.
[0057] Example 2: like Figure 3 As shown, a second aspect of the present invention provides a system for determining the weight of fish school suitability indicators, comprising: The acquisition module 100 is used to acquire a hierarchical structure diagram of fish school suitability indicators.
[0058] The hierarchical structure diagram, from top to bottom, includes: target layer, sub-target layer, index layer, and calculation parameter layer; The fish population suitability indicators include: habitat suitability, river connectivity, ecological health, and suitability for important habitats.
[0059] The target layer includes a suitability index; The sub-target layers include: habitat suitability, river connectivity, ecological health, and suitability of important habitats; The index layer comprises: hydrological condition suitability, hydrodynamic condition suitability, water environment suitability, river topography suitability, river bank ecological suitability, longitudinal connectivity, horizontal connectivity, biodiversity, three-field habitat suitability; The calculation parameter layer comprises: flow, water temperature, flow velocity, water depth, water surface width, flow velocity and depth combination characteristics, water quality, water quality physical property, sinuosity, deep pool and shoal, bottom type, habitat complexity, river bed gradient, river bank stability, river channel change, vegetation diversity, human activity intensity, river bank land use type, longitudinal connectivity index, horizontal connectivity index, fish species, fish resource amount, endangered species protection species, fish three-field scale, fish three-field species; The habitat suitability in the sub-target layer comprises the hydrological condition suitability, the hydrodynamic condition suitability, the water environment suitability, the river topography suitability, and the river bank ecological suitability in the index layer. The river channel connectivity in the sub-target layer comprises the longitudinal connectivity and the horizontal connectivity in the index layer. The ecological health in the sub-target layer comprises the biodiversity in the index layer. The important habitat suitability in the sub-target layer comprises the three-field habitat suitability in the index layer. The hydrological condition suitability in the index layer comprises the flow and the water temperature in the calculation parameter layer. The hydrodynamic condition suitability in the index layer comprises the flow velocity, the water depth, the water surface width, and the flow velocity and depth combination characteristics in the calculation parameter layer. The water environment suitability in the index layer comprises the water quality and the water quality physical property in the calculation parameter layer. The river topography suitability in the index layer comprises the sinuosity, the deep pool and shoal, the bottom type, the habitat complexity, and the river bed gradient in the calculation parameter layer. The river bank ecological suitability in the index layer comprises the river bank stability, the river channel change, the vegetation diversity, the human activity intensity, and the river bank land use type in the calculation parameter layer. The longitudinal connectivity in the index layer comprises the longitudinal connectivity index in the calculation parameter layer. The horizontal connectivity in the index layer comprises the horizontal connectivity index in the calculation parameter layer. The biodiversity in the index layer comprises the fish species, the fish resource amount, and the endangered species protection species in the calculation parameter layer. The three-field habitat suitability in the index layer comprises the fish three-field scale and the fish three-field species in the calculation parameter layer.
[0060] The constructing module 200 is configured to construct the judgment matrix of each layer in the hierarchical structure diagram.
[0061] The construction module 200 is further configured to: respectively determine whether the number of elements corresponding to each element in the target layer, the sub-target layer and the index layer in the next layer is greater than or equal to 3, if yes, the analytic hierarchy process is used to construct the judgment matrix of each level, otherwise, the weight is directly assigned based on the preset value.
[0062] The judgment matrix of each level includes: a sub-target layer judgment matrix, an index layer judgment matrix, a calculation parameter judgment matrix of water dynamic condition suitability, a calculation parameter judgment matrix of river topography and geomorphology suitability, a calculation parameter judgment matrix of river bank ecology suitability, and a calculation parameter judgment matrix of biological diversity.
[0063] The calculation formula of the judgment matrix of each level is as follows: , In the formula, is the rth judgment matrix in the qth level, is the importance ratio of the nth element to the nth element.
[0064] The first determination module 300 is configured to determine the initial weight of each element in each level to the upper level according to the judgment matrix of each level.
[0065] The first determination module 300 is further configured to: determine the characteristic vector corresponding to each judgment matrix according to the value of each row element in each judgment matrix; determine the initial weight of each element in each level to the upper level according to the characteristic vector corresponding to each judgment matrix.
[0066] Each judgment matrix is a judgment matrix that has passed consistency check.
[0067] The second determination module 400 is configured to determine the weight of each index value in the fish population suitability index based on the initial weight of each element in each level to the upper level.
[0068] The second determination module 400 is further configured to: determine the weight proportion of each element in the sub-target layer according to the initial weight of each element in the sub-target layer to the upper level; determine the weight proportion of each element in the index level under the weight proportion of each element in the sub-target level; determine the weight proportion of each element in the calculation parameter level under the weight proportion of each element in the index level; determine the weight of each calculation parameter in the fish population suitability index based on the weight proportion of each element in the calculation parameter level and the initial weight of each element in the calculation parameter level to the upper level; Based on the weight of each calculation parameter in the fish population suitability index, the weight of each index value in the fish population suitability index is determined.
[0069] To sum up, the fish population suitability index weight determination system accurately gives different weight values to different indexes to reflect the relative importance of the indexes, so as to ensure the accuracy and effectiveness of the evaluation results.
[0070] Embodiment three: The third aspect of the application is an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the method of the first aspect.
[0071] Embodiment four: A computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to implement the method of the first aspect.
Claims
1. A method for determining weights of fish population suitability indicators, the method comprising: The method comprises the following steps: Step 1, obtaining a hierarchical structure diagram of fish population suitability indexes; Step 2, constructing a judgment matrix of each level in the hierarchical structure diagram; Step 3, determining initial weights of each element in each level to the upper level according to the judgment matrix of each level; Step 4, determining weights of each index value in the fish population suitability indexes based on the initial weights of each element in each level to the upper level; The hierarchical structure diagram comprises a target layer, a sub-target layer, an index layer and a calculation parameter layer from top to bottom; The fish population suitability indexes comprise habitat suitability, river connectivity, ecological health and important habitat suitability.
2. The fish population suitability index weight determination method of claim 1, wherein: The target layer comprises a suitability index; The sub-target layer comprises habitat suitability, river connectivity, ecological health and important habitat suitability; The index layer comprises hydrological condition suitability, hydrodynamic condition suitability, water environment suitability, river topography suitability, river bank ecology suitability, longitudinal connectivity, lateral connectivity, biodiversity, three-field habitat suitability; The calculation parameter layer comprises flow, water temperature, flow velocity, water depth, water surface width, flow velocity and depth combination characteristics, water quality, water quality physical properties, sinuosity, deep pool and shoal, bottom type, habitat complexity, river bed gradient, river bank stability, river channel change, vegetation diversity, human activity intensity, river bank land use type, longitudinal connectivity index, lateral connectivity index, fish species, fish resource amount, endangered species protection species, fish three-field scale, fish three-field species; The habitat suitability in the sub-target layer comprises the hydrological condition suitability, the hydrodynamic condition suitability, the water environment suitability, the river topography suitability and the river bank ecology suitability in the index layer; The river connectivity in the sub-target layer comprises the longitudinal connectivity and the lateral connectivity in the index layer; The ecological health in the sub-target layer comprises the biodiversity in the index layer; The important habitat suitability in the sub-target layer comprises the three-field habitat suitability in the index layer; The hydrological condition suitability in the index layer comprises the flow and the water temperature in the calculation parameter layer; The hydrodynamic condition suitability in the index layer comprises the flow velocity, the water depth, the water surface width and the flow velocity and depth combination characteristics in the calculation parameter layer; The water environment suitability in the index layer comprises the water quality and the water quality physical properties in the calculation parameter layer; The river topography suitability in the index layer comprises the sinuosity, the deep pool and shoal, the bottom type, the habitat complexity and the river bed gradient in the calculation parameter layer; The river bank ecology suitability in the index layer comprises the river bank stability, the river channel change, the vegetation diversity, the human activity intensity and the river bank land use type in the calculation parameter layer; The longitudinal connectivity in the index layer comprises the longitudinal connectivity index in the calculation parameter layer; The lateral connectivity in the index layer comprises the lateral connectivity index in the calculation parameter layer; The biodiversity in the index layer comprises the fish species, the fish resource amount and the endangered species protection species in the calculation parameter layer; The three-field habitat suitability in the index layer comprises the fish three-field scale and the fish three-field species in the calculation parameter layer.
3. The fish population suitability index weight determination method of claim 2, wherein: The method for constructing the judgment matrix of each level in the hierarchical structure diagram in step 2 is: judging whether the number of elements corresponding to each element in the target layer, the sub-target layer and the index layer in the next layer is greater than or equal to 3, if yes, using the analytic hierarchy process to construct the judgment matrix of each level, otherwise directly assigning weights based on preset values.
4. The fish population suitability index weight determination method of claim 3 wherein: The judgment matrix of each level includes: a sub-target layer judgment matrix, an index layer judgment matrix, a water dynamic condition suitability calculation parameter judgment matrix, a river topography and geomorphology suitability calculation parameter judgment matrix, a river bank ecology suitability calculation parameter judgment matrix and a biological diversity calculation parameter judgment matrix.
5. The fish population suitability index weight determination method of claim 1, wherein: The calculation formula of the judgment matrix of each level is as follows: ， wherein is the rth judgment matrix in the q hierarchy, is the ratio of the nth element to the importance of the nth element.
6. The fish population suitability index weight determination method of claim 1 wherein: The step 3 includes the following steps: Step 31, determining the characteristic vector corresponding to each judgment matrix according to the value of each row element in each judgment matrix; Step 32, determining the initial weight of each element in each level to the previous level according to the characteristic vector corresponding to each judgment matrix.
7. The fish community suitability index weight determination method of claim 1 wherein: Each judgment matrix is a judgment matrix that has passed consistency check.
8. The fish population suitability index weight determination method of claim 1 wherein: The step 4 includes the following steps: Step 41, determining the weight proportion of each element in the sub-target layer according to the initial weight of each element in the sub-target layer to the previous level; Step 42, determining the weight proportion of each element in the index layer under the weight proportion of each element in the sub-target layer; Step 43, determining the weight proportion of each element in the calculation parameter layer under the weight proportion of each element in the index layer; Step 44, determining the weight of each calculation parameter in the fish population suitability index based on the weight proportion of each element in the calculation parameter layer and the initial weight of each element in the calculation parameter layer to the previous level; Step 45, determining the weight of each index value in the fish population suitability index based on the weight of each calculation parameter in the fish population suitability index.
9. A fish population suitability index weight determination system characterized by: It includes: An acquisition module (100) configured to acquire a hierarchical structure diagram of a fish population suitability index; A construction module (200) configured to construct a judgment matrix of each level in the hierarchical structure diagram; A first determination module (300) configured to determine an initial weight of each element in each level to a previous level according to the judgment matrix of each level; A second determination module (400) configured to determine a weight of each index value in the fish population suitability index based on the initial weight of each element in each level to the previous level; The hierarchical structure diagram includes, from top to bottom, a target layer, a sub-target layer, an index layer and a calculation parameter layer; The fish population suitability index includes habitat suitability, river connectivity, ecological health and important habitat suitability.
10. An electronic device, comprising: It includes a memory, a processor and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the method of any one of claims 1-8 is implemented.
11. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to implement the method of any one of claims 1-8.