A cloud data processing-based water conservancy planning information platform construction method

Abstract

The application discloses a water conservancy planning information platform construction method based on cloud data processing, relates to the field of water conservancy information technology, and comprises the following steps: forming at least one planning processing node, collecting the planning processing nodes into a water conservancy planning information platform, dividing the planning processing nodes into formal planning processing nodes and preparatory planning processing nodes, reserving the planning processing nodes as the formal planning processing nodes in the water conservancy planning information platform, obtaining a periodic evaluation score, performing sorting optimization on the planning processing nodes, performing feature extraction on a water conservancy project, generating a target planning processing node, planning the water conservancy project by the target planning processing node, and optimizing the planning processing nodes according to the planning result of the water conservancy project. Through the construction of the water conservancy planning information platform and the setting of the multiple planning processing nodes, different water conservancy planning can be performed, and the parameters of the planning processing nodes can be adjusted according to the planning result.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of water conservancy information technology, in particular to a water conservancy planning information platform construction method based on cloud data processing. BACKGROUND

[0002] Water conservancy planning is an overall arrangement made according to the present situation of natural geography and water regime for preventing and controlling water and flood disasters and rationally developing and utilizing water and soil resources, which is an important preliminary work of water conservancy construction and also an important branch of water conservancy science. Water conservancy planning mainly studies the present situation and characteristics of water conservancy, proposes the direction, main measures and phased implementation steps of governance and development, arranges the comprehensive and long-term plan of water conservancy construction, and guides water conservancy engineering design and management.

[0003] However, the existing planning is usually designed manually, and even if there is an automatic system for planning, the planning intelligence is insufficient, and manual assistance is still needed in the planning process, so the planning efficiency needs to be improved. SUMMARY

[0004] To solve the above technical problems, a water conservancy planning information platform construction method based on cloud data processing is provided, which solves the problems proposed in the background technology.

[0005] To achieve the above purposes, the technical scheme adopted by the present application is as follows:

[0006] A water conservancy planning information platform construction method based on cloud data processing, comprising:

[0007] forming at least one planning processing node, and collecting the planning processing nodes into a water conservancy planning information platform;

[0008] dividing the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes, and reserving the planning processing nodes as formal planning processing nodes in the water conservancy planning information platform;

[0009] periodically evaluating the planning quality of the planning processing nodes to obtain a periodic evaluation score;

[0010] sorting and optimizing the planning processing nodes according to the periodic evaluation score of the planning processing nodes;

[0011] extracting features of the water conservancy project;

[0012] generating a target planning processing node according to the features of the water conservancy project, the target planning processing node planning the water conservancy project;

[0013] optimizing the planning processing nodes according to the planning result of the water conservancy project;

[0014] The functions of feature extraction, target planning processing node generation and optimization of the planning processing node are integrated into the water conservancy planning information platform.

[0015] Preferably, the forming of the at least one planning processing node comprises the following steps:

[0016] Recording all the procedures of the water conservancy planning process to obtain at least one planning procedure;

[0017] Identifying the criticality of the planning procedure to obtain at least one critical index;

[0018] Obtaining the parameter range of the critical index, and uniformly obtaining at least one identification point within the parameter range;

[0019] Randomly selecting one of the at least one identification point of the critical index to assign to the critical index, forming a parameter setting combination of the critical index;

[0020] Using the parameter setting combination of the critical index as the node of the planning parameter, as the planning processing node.

[0021] Preferably, the identifying of the criticality of the planning procedure to obtain at least one critical index comprises the following steps:

[0022] Obtaining at least one sample water conservancy project and its corresponding sample planning result;

[0023] Summarizing the at least one planning procedure to obtain a planning procedure set;

[0024] Selecting one of the planning procedures in the planning procedure set as a target planning procedure;

[0025] Using the planning procedure set from which the target planning procedure is removed as a target planning procedure set;

[0026] Planning the sample water conservancy project using the planning procedures of the target planning procedure set to obtain a first planning result;

[0027] Planning the sample water conservancy project using the planning procedures of the planning procedure set to obtain a second planning result;

[0028] Comparing the first planning result and the second planning result in terms of functions, if the first planning result has functional defects, then the target planning procedure is a critical index, otherwise, no further processing is performed;

[0029] When the target planning procedure traverses the planning procedure set, at least one critical index is obtained.

[0030] Preferably, the dividing of the planning processing node into a formal planning processing node and a preliminary planning processing node comprises the following steps:

[0031] The sample water conservancy project is planned using the planning processing node to obtain an actual planning result;

[0032] The actual planning result is compared with the sample planning result to obtain a coverage rate of the actual planning result on the sample planning result;

[0033] The coverage rates of the planning processing nodes are averaged to obtain an average coverage rate;

[0034] The maximum and minimum values of the average coverage rate are used as end points to form an identification interval, and the value of the midpoint of the identification interval is used as a characteristic value;

[0035] The planning processing nodes with the average coverage rate greater than the characteristic value are used as formal planning processing nodes, and the planning processing nodes with the average coverage rate not exceeding the characteristic value are used as preliminary planning processing nodes.

[0036] Preferably, the periodic evaluation of the planning quality of the planning processing node comprises the following steps:

[0037] At least one real planning result completed by the planning processing node in the actual planning process is obtained;

[0038] The feedback result of the water conservancy project unit implementing the real planning result is obtained;

[0039] The missing functions in the feedback result are counted to obtain at least one missing function, and the estimated service life reduction ratio of the project, the construction time exceeding ratio of the project, and the cost exceeding budget ratio of the project are obtained in the feedback result;

[0040] The analytic hierarchy process is used to form the key weight of the missing function, and the key weight of the missing function is accumulated to obtain a missing coefficient;

[0041] The missing coefficients of all planning processing nodes are averaged to obtain a missing average coefficient;

[0042] If the missing coefficient does not exceed the missing average coefficient, the missing ratio is 0, otherwise, the missing ratio is equal to the part of the missing coefficient exceeding the missing average coefficient divided by the missing average coefficient;

[0043] The missing ratio of the planning processing node, the estimated service life reduction ratio of the project, the construction time exceeding ratio of the project, and the cost exceeding budget ratio of the project are accumulated as the periodic evaluation score of the planning processing node.

[0044] Preferably, the sorting optimization of the planning processing node according to the periodic evaluation score of the planning processing node comprises the following steps:

[0045] The planning processing nodes are sorted in ascending order of the periodic evaluation scores, and are numbered in the order of the sorting.

[0046] Preferably, the feature extraction of the water conservancy project comprises the following steps:

[0047] Obtaining the implementation function and the implementation location coordinates of the water conservancy project;

[0048] Setting a function implementation structure based on the implementation function, and performing feature extraction on the function implementation structure to obtain at least one structure feature;

[0049] Performing feature recognition on the environment at the implementation location coordinates to obtain at least one environment feature;

[0050] Performing cluster analysis on the structure features to form at least one structure feature set, and the coincidence proportion of the structure features in the structure feature set is higher than 99%;

[0051] Performing cluster analysis on the environment features to form at least one environment feature set, and the coincidence proportion of the environment features in the environment feature set is higher than 99%, thereby completing the feature extraction.

[0052] Preferably, the generating of the target planning processing node according to the features of the water conservancy project comprises the following steps:

[0053] Taking the water conservancy project processed by the planning processing node in the actual planning process as a historical water conservancy project;

[0054] Performing feature extraction on the implementation function and the implementation location coordinates of the historical water conservancy project to obtain at least one historical structure feature and at least one historical environment feature, respectively;

[0055] Performing cluster analysis on the historical structure features to form at least one historical structure feature set, and the coincidence proportion of the historical structure features in the historical structure feature set is higher than 99%;

[0056] Performing cluster analysis on the historical environment features to form at least one historical environment feature set, and the coincidence proportion of the historical environment features in the historical environment feature set is higher than 99%;

[0057] When the coincidence proportion of the historical structure features in the historical structure feature set with the structure features in the structure feature set is higher than 99%, the historical structure feature set and the structure feature set are paired, otherwise, they are not paired;

[0058] When the coincidence proportion of the historical environment features in the historical environment feature set with the environment features in the environment feature set is higher than 99%, the historical environment feature set and the environment feature set are paired, otherwise, they are not paired;

[0059] If the historical environment feature set and the historical structure feature set of the planning processing node are in one-to-one correspondence with the environment feature set and the structure feature set of the water conservancy project, the planning processing node is taken as a feature planning processing node.

[0060] In the arrangement of the planning processing nodes, the feature planning processing node with the smallest number is selected as a target planning processing node.

[0061] Preferably, the optimization of the planning processing node according to the planning result of the water conservancy project comprises the following steps:

[0062] When the coincidence proportion of the historical environment features in the historical environment feature set of two planning processing nodes is higher than 99% and the coincidence proportion of the historical structure features in the historical structure feature set is higher than 99%, the two planning processing nodes are in an approximate relationship.

[0063] The planning processing nodes with the approximate relationship are summarized as a planning processing node set.

[0064] The values of the key indicators of the planning processing nodes in the planning processing node set are paired and fitted with the periodic evaluation scores to obtain a key fitting function, wherein the values of the key indicators are independent variables and the periodic evaluation scores are dependent variables.

[0065] The value of the key indicator when the key fitting function takes a minimum value is taken as a target value.

[0066] The values of the key indicators of the planning processing nodes in the planning processing node set are all set to the target value.

[0067] Compared with the prior art, the present application has the following beneficial effects:

[0068] By constructing the water conservancy planning information platform and deploying functions such as feature extraction of the water conservancy project, generation of a target planning processing node and optimization of the planning processing node for the water conservancy planning information platform, different water conservancy planning can be performed through the setting of multiple planning processing nodes, so that a more suitable planning processing node can be matched for the water conservancy project during planning, and the parameters of the planning processing node can be adjusted according to the planning result, thereby improving the planning effect of the water conservancy planning information platform. BRIEF DESCRIPTION OF DRAWINGS

[0069] Figure 1 A flowchart of the water conservancy planning information platform construction method based on cloud data processing of the present application;

[0070] Figure 2 A flowchart of forming at least one planning processing node of the present application;

[0071] Figure 3 A flowchart for identifying criticality of a planning procedure to obtain at least one critical indicator of the present application;

[0072] Figure 4 A flowchart for dividing a planning processing node into a formal planning processing node and a preliminary planning processing node of the present application;

[0073] Figure 5 A flowchart for periodically evaluating the planning quality of a planning processing node of the present application;

[0074] Figure 6 A flowchart for feature extraction of a water conservancy project of the present application;

[0075] Figure 7 A flowchart for generating a target planning processing node according to the characteristics of a water conservancy project of the present application;

[0076] Figure 8 A flowchart for optimizing a planning processing node according to the planning result of a water conservancy project of the present application. DETAILED DESCRIPTION

[0077] The following description is used to disclose the present application so that those skilled in the art can implement the present application. The preferred embodiments in the following description are only as examples, and other obvious modifications can be made by those skilled in the art.

[0078] Reference Figure 1 As shown in the figure, a water conservancy planning information platform construction method based on cloud data processing includes:

[0079] Forming at least one planning processing node, and aggregating the planning processing nodes into a water conservancy planning information platform;

[0080] Dividing the planning processing node into a formal planning processing node and a preliminary planning processing node, and retaining the planning processing node as a formal planning processing node in the water conservancy planning information platform;

[0081] Periodically evaluating the planning quality of the planning processing node to obtain a periodic evaluation score;

[0082] According to the periodic evaluation score of the planning processing node, the planning processing node is sorted and optimized;

[0083] Feature extraction of a water conservancy project;

[0084] According to the characteristics of a water conservancy project, a target planning processing node is generated, and the target planning processing node plans the water conservancy project;

[0085] According to the planning result of a water conservancy project, a planning processing node is optimized;

[0086] The functions of feature extraction, target planning processing node generation and optimization of the planning processing node are integrated into the water conservancy planning information platform.

[0087] The water conservancy planning information platform is constructed. Since water conservancy planning involves many factors, a simple construction can obtain a platform that can plan, but the matching degree of the planning result may be insufficient. In the present scheme, multiple planning processing nodes are set, each of which has different parameters, so that differentiated planning can be performed. The planning results are sorted and matched with water conservancy projects, so that the target planning processing node can be used to plan the water conservancy projects, and the planning effect is better than that of all nodes. Moreover, the parameters of the planning processing node are optimized, thereby improving the reliability of the planning result of the water conservancy planning information platform.

[0088] Referring to Figure 2 The formation of at least one planning processing node includes the following steps:

[0089] All procedures of the water conservancy planning process are recorded to obtain at least one planning procedure;

[0090] The criticality of the planning procedure is identified to obtain at least one key indicator;

[0091] The parameter range of the key indicator is obtained, and at least one identification point is uniformly obtained within the parameter range;

[0092] One of the at least one identification point of the key indicator is randomly selected to form a parameter setting combination of the key indicator;

[0093] The parameter setting combination of the key indicator is used as a planning parameter node, which is a planning processing node.

[0094] During planning, each procedure has corresponding parameter settings. Different parameter settings will result in different planning effects. Therefore, in order to plan according to the needs of water conservancy projects, multiple parameter setting combinations are formed, which produce planning processing nodes. However, these are preliminary planning processing nodes, which need to be further reduced and optimized.

[0095] Referring to Figure 3 The criticality of the planning procedure is identified to obtain at least one key indicator, which includes the following steps:

[0096] At least one sample water conservancy project and its corresponding sample planning result are obtained;

[0097] The at least one planning procedure is summarized to obtain a planning procedure set;

[0098] select one of the planning procedures in the set of planning procedures as a target planning procedure;

[0099] remove the set of planning procedures from the target planning procedure as a set of target planning procedures;

[0100] use the planning procedures in the set of target planning procedures to plan the sample water conservancy project to obtain a first planning result;

[0101] use the planning procedures in the set of planning procedures to plan the sample water conservancy project to obtain a second planning result;

[0102] compare the first planning result and the second planning result in function, when the first planning result has a functional defect, the target planning procedure is a key indicator, otherwise, no processing is performed;

[0103] when the target planning procedure traverses the set of planning procedures, at least one key indicator is obtained.

[0104] Among all the procedures in the planning, some are unnecessary, therefore, in order to reduce the generation of unnecessary steps during planning, identification of key indicators is required, during identification, mainly according to the comparison of the effects of planning, when it is an unnecessary step, the result of the planning will appear defects, and thus can be discarded, because it will not have a substantial impact on the result, thereby reducing the flow of planning.

[0105] Referring to Figure 4 the planning processing nodes are divided into formal planning processing nodes and preliminary planning processing nodes, including the following steps:

[0106] use the planning processing nodes to plan the sample water conservancy project to obtain an actual planning result;

[0107] compare the actual planning result with the sample planning result to obtain the coverage rate of the actual planning result to the sample planning result;

[0108] take the average of at least one coverage rate of the planning processing nodes to obtain an average coverage rate;

[0109] use the maximum and minimum values of the average coverage rate as end points to form an identification interval, and use the value of the midpoint of the identification interval as a characteristic value;

[0110] the planning processing nodes with an average coverage rate greater than the characteristic value are formal planning processing nodes, and the planning processing nodes with an average coverage rate not exceeding the characteristic value are preliminary planning processing nodes.

[0111] Since the planning processing nodes are randomly set, their parameters may not be suitable for planning, although the planning processing nodes will be optimized later, but the parameters that are too poor will prolong the time of optimizing the planning processing nodes, therefore, the planning quality of the planning processing nodes is preliminarily judged, and the planning processing nodes with obviously poor planning effect are hidden.

[0112] Referring to Figure 5 The periodic evaluation of the planning quality of the planning processing nodes includes the following steps:

[0113] Obtaining at least one real planning result completed by the planning processing nodes in the actual planning process;

[0114] Obtaining the feedback results of the hydraulic engineering units implementing the real planning results;

[0115] In the feedback results, the missing functions are counted to obtain at least one missing function, and the estimated service life reduction ratio of the project, the construction time exceeding ratio of the project and the cost exceeding budget ratio of the project are obtained in the feedback results;

[0116] Using the analytic hierarchy process, the key weight of the missing function is formed, the key weight of the missing function is accumulated, and the missing coefficient is obtained;

[0117] The missing coefficients of all planning processing nodes are averaged to obtain the missing average coefficient;

[0118] If the missing coefficient does not exceed the missing average coefficient, the missing ratio is 0, otherwise, the missing ratio is equal to the part of the missing coefficient exceeding the missing average coefficient divided by the missing average coefficient;

[0119] The missing ratio of the planning processing node, the estimated service life reduction ratio of the project, the construction time exceeding ratio of the project and the cost exceeding budget ratio of the project are accumulated as the periodic evaluation score of the planning processing node.

[0120] The planning processing nodes are sorted here, and in the subsequent selection of the planning processing nodes, the sorting results need to be relied on for screening, the basis for sorting is to comprehensively evaluate the actual application situation of the planning, here it needs to be noted that the missing functions need to be differentiated, because different missing functions cause different effects, therefore, the key weight of the missing function needs to be formed, and the missing coefficient is obtained according to this, thereby, the missing function can be differentiated, in addition, the planning is also reflected in the project quality and construction, the quality is mainly related to the life of the project, and the construction is mainly related to the cost and the construction period, when the planning is unreasonable, the life of the project cannot reach the expectation, and the cost and the construction period will all appear a certain excess.

[0121] According to the periodic evaluation score of the planning processing node, the planning processing node is sorted and optimized, including the following steps:

[0122] The planning processing nodes are sorted in ascending order of the periodic evaluation score, and numbered in the order of arrangement.

[0123] Referring to Figure 6 As shown in the figure, the feature extraction of the water conservancy project includes the following steps:

[0124] Obtain the implementation function and implementation location coordinates of the water conservancy project;

[0125] Set the function implementation structure based on the implementation function, and perform feature extraction on the function implementation structure to obtain at least one structure feature;

[0126] Feature recognition is performed on the environment at the implementation location coordinates to obtain at least one environmental feature;

[0127] Cluster analysis is performed on the structure features to form at least one structure feature set, and the coincidence rate of the structure features in the structure feature set is higher than 99%;

[0128] Cluster analysis is performed on the environmental features to form at least one environmental feature set, and the coincidence rate of the environmental features in the environmental feature set is higher than 99%, and the feature extraction is completed.

[0129] When matching the planning processing node for the water conservancy project, the features of the water conservancy project need to be analyzed, otherwise there is no basis for screening, and its features mainly manifest in two aspects, one is its own functional demand, and the other is the feature of the environment. The functional demand leads to the setting of the structure, and the feature of the environment limits the layout of the structure setting and the adaptive operation made for the environment, so the features of the two need to be extracted.

[0130] Referring to Figure 7 As shown in the figure, according to the features of the water conservancy project, the target planning processing node is generated, including the following steps:

[0131] The water conservancy project processed by the planning processing node in the actual planning process is regarded as a historical water conservancy project;

[0132] The implementation function and implementation location coordinates of the historical water conservancy project are extracted to obtain at least one historical structure feature and at least one historical environmental feature;

[0133] Cluster analysis is performed on the historical structure features to form at least one historical structure feature set, and the coincidence rate of the historical structure features in the historical structure feature set is higher than 99%;

[0134] The historical environment features are clustered to form at least one historical environment feature set, and the overlap ratio of the historical environment features in the historical environment feature set is higher than 99%;

[0135] When the overlap ratio of the historical structure features in the historical structure feature set and the structure features in the structure feature set is higher than 99%, the historical structure feature set and the structure feature set are paired, otherwise, they are not paired;

[0136] When the overlap ratio of the historical environment features in the historical environment feature set and the environment features in the environment feature set is higher than 99%, the historical environment feature set and the environment feature set are paired, otherwise, they are not paired;

[0137] If the historical environment feature set and the historical structure feature set of the planning processing node establish a one-to-one correspondence with the environment feature set and the structure feature set of the water conservancy project, the planning processing node is regarded as a feature planning processing node;

[0138] In the arrangement of the planning processing nodes, the feature planning processing node with the smallest number is selected as the target planning processing node.

[0139] In the matching, the features of the projects that have been processed by the planning processing node are compared with the features of the water conservancy project. When they all correspond to similar features, the planning processing node can plan them, but in order to ensure the effect of the planning, the earlier planning processing node in the arrangement of the planning processing nodes is selected, because the arrangement is sorted according to the planning effect, and the larger the periodic evaluation score is, the worse the effect is.

[0140] Referring to Figure 8 As shown in the figure, the optimization of the planning processing node according to the planning result of the water conservancy project includes the following steps:

[0141] When the overlap ratio of the historical environment features in the historical environment feature set of two planning processing nodes is higher than 99% and the overlap ratio of the historical structure features in the historical structure feature set is higher than 99%, the two planning processing nodes are in an approximate relationship;

[0142] The planning processing nodes with an approximate relationship are summarized as a planning processing node set;

[0143] The numerical value of the key indicator of the planning processing node in the planning processing node set is paired with the periodic evaluation score and fitted to obtain a key fitting function, wherein the numerical value of the key indicator is the independent variable and the periodic evaluation score is the dependent variable;

[0144] The value of the key indicator when the key fitting function takes the minimum value is obtained as the target value;

[0145] The value of the key index of the planning processing node in the planning processing node set is set to the target value.

[0146] Since there are multiple planning processing nodes for planning similar projects, the planning processing node set is set, and since there is a lot of data, the data can be used for function fitting, and here the optimization is performed for each key index in turn, and since the smaller the periodic evaluation score is, the better the planning effect is, therefore the value of the key index when the key fitting function takes the minimum value is obtained as the target value, and the target value can be used to optimize the key index.

[0147] Further, the present scheme also proposes a storage medium having a computer readable program stored thereon, and the computer readable program is run when called to run the water conservancy planning information platform construction method based on cloud data processing.

[0148] It can be understood that the storage medium can be a magnetic medium, for example, a floppy disk, a hard disk, a magnetic tape, an optical medium such as a DVD, or a semiconductor medium such as a solid state disk (SSD).

[0149] In summary, the advantages of the present application are that by constructing the water conservancy planning information platform and deploying functions such as feature extraction of water conservancy projects, generation of target planning processing nodes, and optimization of planning processing nodes for the water conservancy planning information platform, different focused water conservancy planning can be performed through the setting of multiple planning processing nodes, so that more suitable planning processing nodes can be matched according to the characteristics of the water conservancy project during planning, and the parameters of the planning processing nodes can be adjusted according to the planning results, thereby improving the planning effect of the water conservancy planning information platform.

[0150] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection claimed by the present application is defined by the appended claims and their equivalents.

Claims

1. A method for constructing a water conservancy planning information platform based on cloud data processing, characterized in that, include: At least one planning processing node is formed, and the planning processing nodes are aggregated into a water conservancy planning information platform; The planning processing nodes are divided into formal planning processing nodes and preliminary planning processing nodes. The planning processing nodes that are to be formal planning processing nodes are retained in the water conservancy planning information platform. The planning quality of the planning processing nodes is evaluated periodically to obtain periodic evaluation scores; Based on the periodic evaluation scores of the planning and processing nodes, the planning and processing nodes are sorted and optimized. Feature extraction for water conservancy projects; Based on the characteristics of water conservancy projects, target planning processing nodes are generated, and these nodes are used to plan water conservancy projects. Based on the planning results of water conservancy projects, the planning processing nodes are optimized; The functions of feature extraction for water conservancy projects, generation of target planning processing nodes, and optimization of planning processing nodes will be integrated into the water conservancy planning information platform. The process of dividing the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes includes the following steps: The planning processing nodes are used to plan the sample water conservancy projects to obtain the actual planning results; The actual planning results are compared with the sample planning results to obtain the coverage rate of the actual planning results to the sample planning results; The average coverage rate is obtained by taking the average of the coverage rates of at least one of the planned processing nodes. The maximum and minimum values ​​of the average coverage are used as endpoints to form the recognition interval, and the value of the midpoint of the recognition interval is used as the feature value. Planning nodes with an average coverage rate greater than the characteristic value are designated as formal planning nodes, while planning nodes with an average coverage rate less than the characteristic value are designated as preliminary planning nodes. The process of ranking and optimizing the planning processing nodes based on their periodic evaluation scores includes the following steps: The planning and processing nodes are sorted from smallest to largest according to their periodic evaluation scores, and then numbered in the order of their arrangement. The feature extraction of water conservancy projects includes the following steps: Obtain the functionalities and location coordinates of the water conservancy project; Based on the functional implementation structure, feature extraction is performed on the functional implementation structure to obtain at least one structural feature; Perform feature recognition on the environment at the location coordinates to obtain at least one environmental feature; Cluster analysis is performed on the structural features to form at least one set of structural features, with the overlap rate of structural features in the set exceeding 99%. Cluster analysis is performed on environmental features to form at least one set of environmental features. The overlap rate of environmental features in the set is higher than 99%, thus completing feature extraction. The process of generating target planning processing nodes based on the characteristics of water conservancy projects includes the following steps: Water conservancy projects that were processed during the actual planning process are considered historical water conservancy projects. Feature extraction is performed on the realized functions and location coordinates of historical water conservancy projects to obtain at least one historical structural feature and at least one historical environmental feature, respectively. Cluster analysis is performed on historical structural features to form at least one set of historical structural features, with the overlap rate of historical structural features in the set exceeding 99%. Cluster analysis was performed on historical environmental features to form at least one set of historical environmental features, with the overlap rate of historical environmental features in the set exceeding 99%. If the overlap ratio between the historical structural features in the historical structural feature set and the structural features in the structural feature set is higher than 99%, then the historical structural feature set and the structural feature set are paired; otherwise, they are not paired. If the overlap rate between the historical environmental features in the historical environmental feature set and the environmental features in the environmental feature set is higher than 99%, then the historical environmental feature set and the environmental feature set are paired; otherwise, they are not paired. If a one-to-one correspondence is established between the historical environmental feature set and the historical structural feature set of the planning processing node and the environmental feature set and structural feature set of the water conservancy project, then the planning processing node will be regarded as the feature planning processing node. In the arrangement of planning processing nodes, the feature planning processing node with the smallest number is selected as the target planning processing node.

2. The method for constructing a water conservancy planning information platform based on cloud data processing according to claim 1, characterized in that, The process of forming at least one planning processing node includes the following steps: Record all steps in the water conservancy planning process to obtain at least one planning step; Identify the key processes in the planning process and obtain at least one key indicator; Obtain the parameter range of key indicators, and uniformly acquire at least one identification point within the parameter range; Randomly select one of the key indicator from at least one identification point and assign it to the key indicator to form a combination of key indicator parameter settings; The nodes that use the combination of key indicator parameter settings as planning parameters are used as planning processing nodes.

3. The method for constructing a water conservancy planning information platform based on cloud data processing according to claim 2, characterized in that, The process of identifying key planning procedures and obtaining at least one key indicator includes the following steps: Obtain at least one sample water conservancy project and its corresponding sample planning results; By summarizing at least one planning process, a set of planning processes is obtained; Select one of the planning processes from the set of planning processes as the target planning process; The set of planned processes after removing the target planning process is taken as the target planning process set; The sample water conservancy project is planned using the planning procedures of the target planning procedure set to obtain the first planning result; The planning process of the planning process set is used to plan the sample water conservancy project to obtain the second planning result; A functional comparison is made between the first and second planning results. If the first planning result has functional defects, the target planning process is the key indicator; otherwise, no action is taken. When the target planning process traverses the set of planning processes, at least one key indicator is obtained.

4. The method for constructing a water conservancy planning information platform based on cloud data processing according to claim 3, characterized in that, The periodic evaluation of the planning quality of the planning processing nodes includes the following steps: Obtain at least one actual planning result completed by the planning processing node during the actual planning process; Obtain feedback from water conservancy engineering units that have implemented the actual planning results; The feedback results are used to count the missing functions, and at least one missing function is obtained. The feedback results are also used to obtain the percentage reduction in the estimated service life of the project, the percentage of construction time exceeding the budget, and the percentage of cost exceeding the budget. Using the analytic hierarchy process (AHP), key weights for missing functions are determined, and the key weights for missing functions are summed to obtain the missing coefficient. The average missing coefficient is obtained by taking the mean of the missing coefficients for all planning and processing nodes. If the missing coefficient does not exceed the mean missing coefficient, the missing proportion is 0; otherwise, the missing proportion is equal to the portion of the missing coefficient that exceeds the mean missing coefficient divided by the mean missing coefficient. The percentage of missing planned processing nodes, the percentage of reduced estimated service life of the project, the percentage of construction time exceeding the budget, and the percentage of cost exceeding the budget are added together to form the periodic evaluation score for the planned processing nodes.

5. The method for constructing a water conservancy planning information platform based on cloud data processing according to claim 4, characterized in that, The optimization of planning nodes based on the planning results of water conservancy projects includes the following steps: When the overlap ratio of historical environmental features in the historical environmental feature sets of two planning processing nodes is higher than 99% and the overlap ratio of historical structural features in the historical structural feature sets is higher than 99%, then the two planning processing nodes are approximately related. Planning processing nodes with similar relationships are grouped into a planning processing node set; The values ​​of key indicators of planning processing nodes in the planning processing node set are paired and fitted with periodic evaluation scores to obtain a key fitting function, where the values ​​of key indicators are independent variables and periodic evaluation scores are dependent variables. Find the value of the key indicator when the key fitting function reaches its minimum value, and use it as the target value; Set the values ​​of the key indicators of the planning processing nodes in the planning processing node set to the target values.

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