Water conservancy planning information platform construction method based on cloud data processing

Abstract

The invention discloses a water conservancy planning information platform construction method based on cloud data processing, and relates to the technical field of water conservancy information, and the method comprises the steps: forming at least one planning processing node, and summarizing the planning processing nodes into a water conservancy planning information platform; the planning processing nodes are divided into formal planning processing nodes and preparatory planning processing nodes, and the planning processing nodes serving as the formal planning processing nodes are reserved in the water conservancy planning information platform; obtaining a regular evaluation score; performing sorting optimization on the planning processing nodes; performing feature extraction on the water conservancy project; generating a target planning processing node, wherein the target planning processing node plans the water conservancy project; and according to the planning result of the water conservancy project, the planning processing node is optimized. By constructing a water conservancy planning information platform and setting a plurality of planning processing nodes, water conservancy planning with different emphasis can be carried out, and parameters of the planning processing nodes are adjusted according to planning results.

Description

Technical Field

[0001] The present invention relates to the field of water conservancy information technology, and more specifically to a method for constructing a water conservancy planning information platform based on cloud data processing. Background Art

[0002] Water conservancy planning is a general arrangement formulated according to the natural geography and current water situation for preventing and controlling floods and droughts and rationally developing and utilizing water and soil resources. It is an important preliminary work for water conservancy construction and an important branch of water conservancy science. Water conservancy planning mainly studies the current situation and characteristics of water conservancy, puts forward the direction of treatment and development, the main tasks and measures, and the phased implementation steps, arranges the overall and long-term plans for water conservancy construction, and guides the design and management of water conservancy projects.

[0003] However, the existing planning is usually carried out manually. Even if there is an automated system for planning, its planning intelligence is insufficient, and manual assistance is still required during the planning process, so the planning efficiency needs to be improved. Summary of the Invention

[0004] To solve the above technical problems, a method for constructing a water conservancy planning information platform based on cloud data processing is provided, and this technical solution solves the problems raised in the above background art.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

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

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

[0008] Dividing the planning processing nodes into formal planning processing nodes and preparatory planning processing nodes, and retaining the planning processing nodes as formal planning processing nodes in the water conservancy planning information platform;

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

[0010] Sorting and optimizing the planning processing nodes according to the regular evaluation scores of the planning processing nodes;

[0011] Extracting the characteristics of water conservancy projects;

[0012] Generating target planning processing nodes according to the characteristics of water conservancy projects, and the target planning processing nodes plan the water conservancy projects;

[0013] Optimizing the planning processing nodes according to the planning results of water conservancy projects;

[0014] Integrate the functions of feature extraction of water conservancy projects, generating target planning processing nodes, and optimizing the planning processing nodes into the water conservancy planning information platform.

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

[0016] Record all processes of the water conservancy planning process to obtain at least one planning process;

[0017] Conduct criticality identification on the planning processes to obtain at least one critical index;

[0018] Obtain the parameter range of the critical index, and evenly obtain at least one identification point within the parameter range;

[0019] Randomly select one from at least one identification point of the critical index and assign it to the critical index to form a parameter setting combination of the critical index;

[0020] Use the node with the parameter setting combination of the critical index as the planning parameter as the planning processing node.

[0021] Preferably, the conducting of criticality identification on the planning processes to obtain at least one critical index includes the following steps:

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

[0023] Summarize at least one planning process to obtain a planning process set;

[0024] Select one of the planning processes in the planning process set as the target planning process;

[0025] Use the planning process set after removing the target planning process as the target planning process set;

[0026] Use the planning processes in the target planning process set to plan the sample water conservancy project to obtain a first planning result;

[0027] Use the planning processes in the planning process set to plan the sample water conservancy project to obtain a second planning result;

[0028] Conduct a function comparison on the first planning result and the second planning result. When there is a function defect in the first planning result, the target planning process is the critical index, otherwise, no processing is done;

[0029] When the target planning process traverses the planning process set, obtain at least one critical index.

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

[0031] Use the planning processing node to plan the sample water conservancy project to obtain the actual planning result;

[0032] 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;

[0033] Take the average value of at least one coverage rate of the planning processing node to obtain the average coverage rate;

[0034] Use the maximum and minimum values of the average coverage rate as endpoints to form an identification interval, and take the value of the midpoint of the identification interval as the characteristic value;

[0035] Take the planning processing node with an average coverage rate greater than the characteristic value as the formal planning processing node, and take the planning processing node with an average coverage rate not exceeding the characteristic value as the preliminary planning processing node.

[0036] Preferably, the regular evaluation of the planning quality of the planning processing node includes the following steps:

[0037] Obtain at least one real planning result completed by the planning processing node during the actual planning process;

[0038] Obtain the feedback result of the water conservancy project unit implementing the real planning result;

[0039] Conduct statistics on the missing functions in the feedback result to obtain at least one missing function, and obtain the estimated service life reduction ratio of the project, the construction time overrun ratio of the project, and the cost overrun ratio of the project in the feedback result;

[0040] Use the analytic hierarchy process to form the key weights of the missing functions, and accumulate the key weights of the missing functions to obtain the missing coefficient;

[0041] Take the average value of the missing coefficients of all planning processing nodes to obtain the average missing coefficient;

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

[0043] Accumulate the missing ratio of the planning processing node, the estimated service life reduction ratio of the project, the construction time overrun ratio of the project, and the cost overrun ratio of the project as the regular evaluation score of the planning processing node.

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

[0045] Sort the planning processing nodes in ascending order according to the regular evaluation scores, and number them in the order of arrangement.

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

[0047] Obtain the implementation functions and implementation location coordinates of the water conservancy project;

[0048] Set the function implementation structure based on the implementation functions, perform feature extraction on the function implementation structure, and obtain at least one structural feature;

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

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

[0051] Perform cluster analysis on the environmental features to form at least one environmental feature set, and the coincidence ratio of the environmental features in the environmental feature set is higher than 99%, and the feature extraction is completed.

[0052] Preferably, the generation of the target planning processing node according to the characteristics of the water conservancy project includes the following steps:

[0053] Regard the water conservancy projects processed by the planning processing node in the actual planning process as historical water conservancy projects;

[0054] Perform feature extraction on the implementation functions and implementation location coordinates of the historical water conservancy projects to obtain at least one historical structural feature and at least one historical environmental feature respectively;

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

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

[0057] When the coincidence ratio of the historical structural features in the historical structural feature set and the structural features in the structural feature set is higher than 99%, then pair the historical structural feature set with the structural feature set, otherwise, do not pair;

[0058] When the coincidence ratio of the historical environmental features in the historical environmental feature set and the environmental features in the environmental feature set is higher than 99%, then pair the historical environmental feature set with the environmental feature set, otherwise, do not pair;

[0059] When 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 the structural feature set of the water conservancy project, the planning processing node is taken as the feature planning processing node;

[0060] Among the arrangements of the planning processing nodes, the feature planning processing node with the smallest number is selected as the target planning processing node.

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

[0062] When the coincidence ratio of the historical environmental features in the historical environmental feature set of two planning processing nodes is higher than 99% and the coincidence ratio of the historical structural features in the historical structural feature set is higher than 99%, the two planning processing nodes are in an approximate relationship;

[0063] The planning processing nodes with an approximate relationship are summarized into a planning processing node set;

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

[0065] Find the value of the key indicator when the key fitting function takes the minimum value as the target value;

[0066] Set the values of the key indicators of the planning processing nodes in the planning processing node set to the target values.

[0067] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0068] By constructing a 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, through the setting of multiple planning processing nodes, water conservancy planning with different focuses can be carried out. Thus, during the planning, more suitable planning processing nodes can be matched according to the characteristics of the water conservancy project for planning operations. At the same time, the parameters of the planning processing nodes are adjusted according to the planning results, thereby improving the planning effect of the water conservancy planning information platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a schematic flow chart of the method for constructing a water conservancy planning information platform based on cloud data processing of the present invention;

[0070] Figure 2 It is a schematic flow chart of forming at least one planning processing node of the present invention;

[0071] Figure 3 It is a schematic flow chart for the present invention to identify key points in the planning process and obtain at least one key index;

[0072] Figure 4 It is a schematic flow chart for the present invention to divide the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes;

[0073] Figure 5 It is a schematic flow chart for the present invention to regularly evaluate the planning quality of the planning processing nodes;

[0074] Figure 6 It is a schematic flow chart for the present invention to extract features of a water conservancy project;

[0075] Figure 7 It is a schematic flow chart for the present invention to generate target planning processing nodes according to the features of the water conservancy project;

[0076] Figure 8 It is a schematic flow chart for the present invention to optimize the planning processing nodes according to the planning result of the water conservancy project. Detailed implementation manners

[0077] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0078] Refer to Figure 1 As shown, a method for constructing a water conservancy planning information platform based on cloud data processing includes:

[0079] Form at least one planning processing node and summarize the planning processing nodes into a water conservancy planning information platform;

[0080] Divide the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes, and retain the planning processing nodes as formal planning processing nodes in the water conservancy planning information platform;

[0081] Regularly evaluate the planning quality of the planning processing nodes to obtain a regular evaluation score;

[0082] Sort and optimize the planning processing nodes according to the regular evaluation score of the planning processing nodes;

[0083] Extract features of the water conservancy project;

[0084] Generate target planning processing nodes according to the features of the water conservancy project, and the target planning processing nodes plan the water conservancy project;

[0085] Optimize the planning processing nodes according to the planning result of the water conservancy project;

[0086] Integrate the functions of feature extraction of water conservancy projects, generating target planning processing nodes, and optimizing the planning processing nodes into the water conservancy planning information platform.

[0087] When constructing the water conservancy planning information platform, since water conservancy planning involves many factors, if a simple construction is carried out, although the obtained platform can perform planning, the matching degree of its planning results is likely to be insufficient. In this solution, multiple planning processing nodes are set, and different parameters are set for each planning processing node. Therefore, differential planning can be carried out, and sorting and matching with water conservancy projects are carried out according to the planning results, so that the target planning processing node can be used to plan water conservancy projects, and its planning effect is relatively good among all nodes. Moreover, the parameters of the planning processing nodes are optimized, thereby improving the reliability of the planning results of the water conservancy planning information platform.

[0088] Refer to Figure 2 As shown, forming at least one planning processing node includes the following steps:

[0089] Record all processes of the water conservancy planning process to obtain at least one planning process;

[0090] Conduct critical identification on the planning processes to obtain at least one key index;

[0091] Obtain the parameter range of the key index, and evenly obtain at least one identification point within the parameter range;

[0092] Randomly select one from at least one identification point of the key index and assign it to the key index to form a parameter setting combination of the key index;

[0093] Use the node with the parameter setting combination of the key index as the planning parameter as the planning processing node.

[0094] During planning, each process has corresponding parameter settings. Different parameter settings will lead to different planning effects. Therefore, in order to carry out different focused planning according to the needs of water conservancy projects, multiple parameter setting combinations are formed, and thus planning processing nodes are generated. However, these are preliminary planning processing nodes and need further deletion and optimization.

[0095] Refer to Figure 3 As shown, conducting critical identification on the planning processes to obtain at least one key index includes the following steps:

[0096] Obtain at least one sample water conservancy project and its corresponding sample planning result;

[0097] Summarize at least one planning process to obtain a planning process set;

[0098] Select one of the planning processes in the set of planning processes as the target planning process;

[0099] Take the set of planning processes obtained by removing the target planning process as the target set of planning processes;

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

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

[0102] Compare the functions of the first planning result and the second planning result. When there is a functional defect in the first planning result, the target planning process is the key indicator, otherwise, no processing is performed;

[0103] When the target planning process traverses the set of planning processes, at least one key indicator is obtained.

[0104] Among all the planned processes, some are unnecessary. Therefore, in order to reduce the generation of unnecessary steps during planning, it is necessary to identify key indicators. When identifying, it is mainly based on the comparison of the planning effects. When it is an unnecessary step, the result of the planning will be defective, so it can be discarded because it will not have a substantial impact on the result. Thus, the planning process can be reduced.

[0105] Refer to Figure 4 As shown, dividing the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes includes 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 for the sample planning result;

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

[0109] Use the maximum and minimum values of the average coverage rate as endpoints to form an identification interval, and take the value of the midpoint of the identification interval as the characteristic value;

[0110] Take the planning processing nodes with an average coverage rate greater than the characteristic value as formal planning processing nodes, and take the planning processing nodes with an average coverage rate not exceeding the characteristic value as 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, parameters with too poor effects will prolong the optimization time of the planning processing nodes. Therefore, a preliminary judgment is made on the planning processing nodes here, and the planning processing nodes with obviously poor planning effects are hidden.

[0112] Refer to Figure 5 As shown, the regular evaluation of the planning quality of the planning processing nodes includes the following steps:

[0113] Obtain at least one real planning result completed by the planning processing node during the actual planning process;

[0114] Obtain the feedback results of the water conservancy project unit implementing the real planning result;

[0115] Conduct a statistics of the missing functions in the feedback results to obtain at least one missing function, and obtain 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 in the feedback results;

[0116] Use the analytic hierarchy process to form the key weights of the missing functions, and accumulate the key weights of the missing functions to obtain the missing coefficient;

[0117] Take the average value of the missing coefficients of all planning processing nodes to obtain the average missing coefficient;

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

[0119] Accumulate 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 as the regular evaluation score of the planning processing node.

[0120] Here, the planning processing nodes are sorted. When selecting the planning processing nodes later, it is necessary to rely on the sorting results for screening. The sorting basis is a comprehensive evaluation according to the actual application situation of the planning. It should be noted here that different missing functions need to be treated differently because the impacts caused by different missing functions are different. Therefore, it is necessary to form the key weights of the missing functions and obtain the missing coefficient from this, so as to treat the missing functions differently. In addition, the relevance of 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 construction period. When the planning is unreasonable, the life of the project cannot reach the expectation, and both the cost and the construction period will exceed to a certain extent.

[0121] According to the periodic evaluation scores of the planned processing nodes, the sorting optimization of the planned processing nodes includes the following steps:

[0122] The planning processing nodes are sorted from small to large according to the periodic evaluation scores, and are numbered in the order of arrangement.

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

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

[0125] Setting a function realization structure based on the realization function, extracting features of the function realization structure, and obtaining at least one structural feature;

[0126] Performing feature recognition on the environment at the realization location coordinates to obtain at least one environmental feature;

[0127] Performing cluster analysis on the structural features to form at least one structural feature set, wherein the overlap ratio of the structural features in the structural 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 overlap ratio of the environmental features in the environmental feature set is higher than 99%, thereby completing feature extraction.

[0129] When matching planning processing nodes for water conservancy projects, it is necessary to analyze the characteristics of the water conservancy projects, otherwise, there is no basis for screening. Its characteristics are mainly manifested in two aspects: one is its own functional requirements, and the other is the characteristics of the environment. Functional requirements lead to the setting of its structure, and the characteristics of the environment limit the layout of the structure setting and the strain operations made for the environment. Therefore, it is necessary to extract features from both.

[0130] Reference Figure 7 As shown, according to the characteristics of the water conservancy project, generating the target planning processing node includes the following steps:

[0131] The water conservancy projects processed by the planning processing nodes in the actual planning process are regarded as historical water conservancy projects;

[0132] Extracting features of the realized functions and realized location coordinates of the historical water conservancy projects, and obtaining at least one historical structural feature and at least one historical environmental feature respectively;

[0133] Performing cluster analysis on the historical structural features to form at least one historical structural feature set, wherein the overlap ratio of the historical structural features in the historical structural feature set is higher than 99%;

[0134] Perform a clustering analysis on the historical environmental features to form at least one set of historical environmental features, and the coincidence ratio of the historical environmental features in the set of historical environmental features is higher than 99%;

[0135] When the coincidence ratio of all historical structural features in the set of historical structural features and the structural features in the set of structural features is higher than 99%, then pair the set of historical structural features with the set of structural features, otherwise, do not pair;

[0136] When the coincidence ratio of all historical environmental features in the set of historical environmental features and the environmental features in the set of environmental features is higher than 99%, then pair the set of historical environmental features with the set of environmental features, otherwise, do not pair;

[0137] If a one-to-one correspondence is established between the set of historical environmental features and the set of historical structural features of the planning processing node and the set of environmental features and the set of structural features of the water conservancy project, then take the planning processing node as the feature planning processing node;

[0138] Among the arrangements of the planning processing nodes, select the feature planning processing node with the smallest number as the target planning processing node.

[0139] During matching, compare the features of the projects that the planning processing node has processed with the features of the water conservancy project. When they all correspond and are similar, the planning processing node can perform planning on it. However, to ensure the planning effect, thus select the planning processing node that is more forward in the arrangement of the planning processing nodes, because this arrangement is sorted according to the planning effect, and the larger the regular evaluation score, the worse the effect.

[0140] Refer to Figure 8 As shown, optimizing the planning processing node according to the planning result of the water conservancy project includes the following steps:

[0141] When the coincidence ratio of the historical environmental features in the set of historical environmental features of two planning processing nodes is higher than 99% and the coincidence ratio of the historical structural features in the set of historical structural features is higher than 99%, then the two planning processing nodes are in an approximate relationship;

[0142] Summarize the planning processing nodes with an approximate relationship into a set of planning processing nodes;

[0143] Pair and fit the numerical values of the key indicators of the planning processing nodes in the set of planning processing nodes with the regular evaluation scores to obtain a key fitting function, where the numerical values of the key indicators are independent variables and the regular evaluation scores are dependent variables;

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

[0145] Set the values of the key indicators of the planning processing nodes in the set of planning processing nodes to the target values.

[0146] Since there are multiple planning processing nodes for planning similar projects, a set of planning processing nodes is set up. Since there is a lot of data here, these data can be used for function fitting. Here, each key indicator is optimized sequentially. Since the smaller the regular evaluation score, the better the planning effect, the values of the key indicators when the key fitting function takes the minimum value are obtained as the target values. Furthermore, the target values can be used to optimize the key indicators.

[0147] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is called, it runs the above-mentioned method for constructing a water conservancy planning information platform based on cloud data processing.

[0148] It can be understood that the storage medium can be a magnetic medium, such as a floppy disk, a hard disk, or 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 invention are as follows: By constructing a 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, through the setting of multiple planning processing nodes, water conservancy planning with different focuses can be carried out. Thus, during planning, more suitable planning processing nodes can be matched for the water conservancy project according to its characteristics for planning operations. At the same time, the parameters of the planning processing nodes are adjusted according to the results of the planning, thereby improving the planning effect of the water conservancy planning information platform.

[0150] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention 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, Including: Form at least one planning processing node and summarize the planning processing nodes into a water conservancy planning information platform; Divide the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes, and retain the planning processing nodes that are formal planning processing nodes in the water conservancy planning information platform; Regularly evaluate the planning quality of the planning processing nodes to obtain a regular evaluation score; Sort and optimize the planning processing nodes according to the regular evaluation scores of the planning processing nodes; Extract features of water conservancy projects; Generate target planning processing nodes according to the features of water conservancy projects, and the target planning processing nodes plan water conservancy projects; Optimize the planning processing nodes according to the planning results of water conservancy projects; Integrate the functions of extracting features of water conservancy projects, generating target planning processing nodes, and optimizing the planning processing nodes into the water conservancy planning information platform.

2. The method for constructing a water conservancy planning information platform based on cloud data processing according to claim 1, wherein, The forming of at least one planning processing node includes the following steps: Record all processes of the water conservancy planning process to obtain at least one planning process; Identify the key points of the planning process to obtain at least one key indicator; Obtain the parameter range of the key indicator, and evenly obtain at least one identification point within the parameter range; Randomly select one from at least one identification point of the key indicator and assign it to the key indicator to form a parameter setting combination of the key indicator; Use the node with the parameter setting combination of the key indicator as the planning parameter as the planning processing node.

3. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 2, characterized in that, The identifying the key points of the planning process to obtain at least one key indicator includes the following steps: Obtain at least one sample water conservancy project and its corresponding sample planning result; Summarize at least one planning process to obtain a planning process set; Select one planning process from the planning process set as the target planning process; Use the planning process set after removing the target planning process as the target planning process set; Use the planning processes of the target planning process set to plan the sample water conservancy project to obtain a first planning result; Use the planning processes of the planning process set to plan the sample water conservancy project to obtain a second planning result; Compare the functions of the first planning result and the second planning result. When there are functional defects in the first planning result, the target planning process is the key indicator, otherwise, no treatment is performed; When the target planning process traverses the planning process set, obtain at least one key indicator.

4. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 3, characterized in that, The dividing the planning processing nodes into formal planning processing nodes and preliminary planning processing nodes includes the following steps: Use the planning processing nodes to plan the sample water conservancy project to obtain an actual planning result; 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; Take the average value of at least one coverage rate of the planning processing nodes to obtain an average coverage rate; Use the maximum and minimum values of the average coverage rate as endpoints to form an identification interval, and use the value of the midpoint of the identification interval as the characteristic value; Use the planning processing nodes with an average coverage rate greater than the characteristic value as formal planning processing nodes, and use the planning processing nodes with an average coverage rate not exceeding the characteristic value as preliminary planning processing nodes.

5. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 4, characterized in that, The regular evaluation of the planning quality of the planning processing node includes the following steps: Obtain at least one real planning result completed by the planning processing node during the actual planning process; Obtain the feedback result of the water conservancy project unit implementing the real planning result; Conduct a statistics of the missing functions in the feedback result to obtain at least one missing function, and obtain 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 in the feedback result; Use the analytic hierarchy process to form the key weights of the missing functions, and accumulate the key weights of the missing functions to obtain the missing coefficient; Take the average value of the missing coefficients of all planning processing nodes to obtain the average missing coefficient; If the missing coefficient does not exceed the average missing coefficient, the missing ratio is 0, otherwise, the missing ratio is equal to the part where the missing coefficient exceeds the average missing coefficient divided by the average missing coefficient; Accumulate 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 as the regular evaluation score of the planning processing node.

6. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 5, characterized in that, The sorting optimization of the planning processing node according to the regular evaluation score of the planning processing node includes the following steps: Sort the planning processing nodes from small to large according to the regular evaluation score, and number them according to the sorting order.

7. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 6, characterized in that, The feature extraction of the water conservancy project includes the following steps: Obtain the implemented functions and the implemented position coordinates of the water conservancy project; Set the function implementation structure based on the implemented functions, and extract features from the function implementation structure to obtain at least one structural feature; Conduct feature recognition on the environment at the implemented position coordinates to obtain at least one environmental feature; Conduct cluster analysis on the structural features to form at least one structural feature set, and the coincidence ratio of the structural features in the structural feature set is higher than 99%; Conduct cluster analysis on the environmental features to form at least one environmental feature set, and the coincidence ratio of the environmental features in the environmental feature set is higher than 99%, and the feature extraction is completed.

8. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 7, characterized in that, The generation of the target planning processing node according to the features of the water conservancy project includes the following steps: Regard the water conservancy project processed by the planning processing node during the actual planning process as the historical water conservancy project; Extract features from the implemented functions and the implemented position coordinates of the historical water conservancy project to obtain at least one historical structural feature and at least one historical environmental feature respectively; Conduct cluster analysis on the historical structural features to form at least one historical structural feature set, and the coincidence ratio of the historical structural features in the historical structural feature set is higher than 99%; Conduct cluster analysis on the historical environmental features to form at least one historical environmental feature set, and the coincidence ratio of the historical environmental features in the historical environmental feature set is higher than 99%; When the coincidence ratio of the historical structural features in the historical structural feature set is higher than 99% with the structural features in the structural feature set, then pair the historical structural feature set with the structural feature set, otherwise, do not pair; When the coincidence ratio of the historical environmental features in the historical environmental feature set is higher than 99% with the environmental features in the environmental feature set, then pair the historical environmental feature set with the environmental feature set, otherwise, do not pair; When 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 the structural feature set of the water conservancy project, the planning processing node is regarded as a feature planning processing node; Among the arrangements of the planning processing nodes, select the feature planning processing node with the smallest number as the target planning processing node.

9. A method for constructing a water conservancy planning information platform based on cloud data processing according to claim 8, characterized in that, The optimization of the planning processing node according to the planning result of the water conservancy project includes the following steps: When the coincidence ratio of the historical environmental features in the historical environmental feature set of two planning processing nodes is higher than 99% and the coincidence ratio of the historical structural features in the historical structural feature set is higher than 99%, the two planning processing nodes are in an approximate relationship; Summarize the planning processing nodes with an approximate relationship into a planning processing node set; Match and fit the numerical values of the key indicators of the planning processing nodes in the planning processing node set with the scores obtained from regular evaluations, and obtain a key fitting function, where the numerical values of the key indicators are independent variables and the scores obtained from regular evaluations are dependent variables; Find the value of the key indicator when the key fitting function takes the minimum value 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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