Method and device for determining a scheme of re-greening measures for a wind farm

Abstract

The application provides a method and device for determining a scheme of a wind farm greening measure. The method comprises: in response to a design instruction, obtaining input information; wherein the input information comprises location parameters, terrain parameters, altitude parameters and a greening level of a wind farm project; based on a preset multidimensional database, performing associated matching on the input information as a query condition to determine matching information; wherein the preset multidimensional database is formed by association of a plurality of sub-databases, each sub-database is indexed by a multi-level parameter, the multi-level parameter represents at least one constraint dimension and a hierarchical progressive relationship between the constraint dimensions, and the matching information comprises measure configuration information, the measure configuration information represents a measure configuration and a corresponding plant configuration of an engineering area of the wind farm project; and determining a greening design scheme according to the matching information. The method is used to improve the accuracy and efficiency of determining the scheme of the wind farm greening measure.

Description

Technical Field

[0001] This application relates to the field of wind farm ecological restoration design technology, and in particular to a method and apparatus for determining wind farm revegetation measures. Background Technology

[0002] During the construction of wind farms, the construction of main projects such as wind turbine foundations, roads, and substations will disturb the ground surface, damage the original vegetation, and lead to problems such as soil erosion and ecological degradation. Therefore, vegetation restoration measures need to be planned simultaneously during the engineering design stage.

[0003] Traditional revegetation design requires manually selecting suitable plant species based on the project area, developing targeted restoration measures, and manually drawing the revegetation areas on engineering drawings, while also adhering to local regulations for cost control. This process relies heavily on the experience of designers and necessitates frequent consultation of multiple regulatory documents and historical data, resulting in long design cycles, low efficiency, high costs, and susceptibility to design quality issues due to human error. Furthermore, significant climate differences exist between regions, and different sub-projects within the same project have drastically different requirements for revegetation measures. Adopting a single design approach can easily lead to low plant survival rates and insufficient coverage, failing to meet ecological restoration goals.

[0004] Therefore, there is an urgent need for a solution that can accurately determine the revegetation measures for wind farms in order to meet the complexity and efficiency requirements of wind farm revegetation measure design. Summary of the Invention

[0005] The method and apparatus for determining wind farm revegetation measures provided in this application can improve the accuracy and efficiency of determining wind farm revegetation measures.

[0006] In a first aspect, embodiments of this application provide a method for determining a scheme for wind farm revegetation measures, including:

[0007] In response to design instructions, input information is acquired; this input information includes the location parameters, topographic parameters, altitude parameters, and revegetation level of the wind farm project.

[0008] Based on a pre-set multidimensional database, the input information is used as the query condition to perform association matching and determine the matching information. The pre-set multidimensional database is formed by the association of multiple sub-databases. Each sub-database is indexed with multi-level parameters. The multi-level parameters represent at least one constraint dimension and the hierarchical relationship between constraint dimensions. The matching information includes measure configuration information, which represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project.

[0009] Based on the matching information, a revegetation design scheme is determined; the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0010] Optionally, as described above, the multiple sub-databases include a climate type database, a suitable plant database, and a revegetation measures database; based on a pre-set multidimensional database, the input information is used as the query condition for association and matching to determine the matching information, including:

[0011] Using location parameters as query criteria, the climate type database is indexed and matched to determine the target climate zone; where the target climate zone represents the spatial distribution range of the climate type to which the wind farm project belongs.

[0012] Using target climate zone, altitude parameters, and revegetation level as query criteria, the suitable plant database is indexed and matched to determine the target plant configuration information;

[0013] Based on the target plant configuration information, the target plant configuration information is determined by indexing and matching the revegetation measures database using terrain parameters and revegetation level as query conditions, and the matching information is obtained.

[0014] Optionally, as described above, the multi-level parameters in the suitable plant database are indexed with climate zone as the first index level, altitude parameter as the second index level, and revegetation level as the third index level; the suitable plant database is indexed and matched using the target climate zone, altitude parameter, and revegetation level as query conditions to determine the target plant configuration information, including:

[0015] Using the target climate zone as the query condition, the suitable plant database is indexed and matched to obtain the first index result; using the altitude parameter as the query condition, the first index result is indexed and matched to obtain the second index result.

[0016] Using the revegetation level as the query condition, the results of the second index are matched to obtain the target plant configuration information.

[0017] Optionally, as described above, the revegetation measures database uses topographic parameters as the first index level, project area type as the second index level, and revegetation level as the third index level. Based on the target plant configuration information, the database is indexed and matched using topographic parameters and revegetation level as query conditions to determine the target measures configuration information, including:

[0018] Using terrain parameters as query criteria, the database of revegetation measures is indexed and matched to obtain the third index result;

[0019] Obtain a preset set of engineering area types. For each engineering area type in the set, perform index matching on the third index result to obtain the fourth sub-index result, and determine each fourth sub-index result as the fourth index result.

[0020] Using the re-greening level as the query condition, perform index matching on the fourth index result to obtain the fifth index result;

[0021] By associating the target plant configuration information with the fifth index result, the target measure configuration information is obtained.

[0022] Optionally, as described above, the multiple sub-databases also include a construction technology database; the method further includes:

[0023] Using the target measures configuration information as the query condition, the construction technology database is indexed and matched to determine the target technical document information, which represents the construction technology parameters of the project area;

[0024] The target technical document information and target measure configuration information are determined to obtain matching information.

[0025] Optionally, as described above, the input information also includes engineering drawings of the wind farm project, which represent the spatial distribution of the project area; and a revegetation design scheme is determined based on the matching information, including:

[0026] Element identification is performed on engineering drawings to determine slope line information; the slope line information represents the distribution and direction of topographic relief within the engineering area.

[0027] Based on the slope line information, the engineering drawings are divided to determine multiple engineering sub-regions and the corresponding engineering area type for each engineering sub-region.

[0028] For each engineering sub-region, based on the engineering sub-region type, extract the measure configuration information corresponding to the engineering sub-region type from the matching information, and configure the measure sub-region information.

[0029] Based on the configuration information of each measure section, the configuration information of each measure section is associated and bound with the corresponding engineering section area to obtain the greening design scheme.

[0030] Optionally, as described above, the engineering area type corresponding to each engineering sub-region is determined, including:

[0031] For each engineering section area, the slope line distribution data corresponding to the engineering section area is determined from the slope line information;

[0032] Based on the slope line distribution data, the density characteristics are determined; whereby the density characteristics characterize the number of slope lines distributed per unit area.

[0033] Based on density characteristics, the engineering sub-areas are determined as either slope areas or planar areas;

[0034] If the engineering section area is a slope area, the excavation slope type or the fill slope type is determined according to the direction of the slope line in the slope line section data, which is the corresponding engineering area type of the engineering section area.

[0035] If the project sub-region is a planar region, then the planar type is determined to be the project area type corresponding to the project sub-region.

[0036] Optionally, as described above, the multiple sub-databases include a revegetation cost database; the method also includes:

[0037] For each engineering sub-area, the greening cost database is indexed and matched using the sub-area measure configuration information as the query condition to determine the target greening cost; whereby the target greening cost represents the cost of implementing greening measures in the engineering sub-area.

[0038] The total revegetation cost is obtained based on the revegetation cost of each target.

[0039] If the total cost of revegetation exceeds a preset cost threshold, an alarm message will be triggered; the alarm message is used to instruct the user to adjust the revegetation design plan.

[0040] Optionally, the method described above further includes:

[0041] In response to user adjustment instructions, the system obtains adjustment information; the adjustment information represents the user's intention to change the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0042] Based on the adjustment information, the matching information is updated to obtain new matching information.

[0043] Secondly, embodiments of this application provide a device for determining a scheme for wind farm revegetation measures, comprising:

[0044] The response module is used to respond to design instructions and obtain input information, including the location parameters, terrain parameters, altitude parameters, and revegetation level of the wind farm project.

[0045] The matching module is used to perform association matching based on a preset multidimensional database and the input information as the query condition to determine the matching information. The preset multidimensional database is formed by the association of multiple sub-databases. Each sub-database is indexed with multi-level parameters. The multi-level parameters represent at least one constraint dimension and the hierarchical relationship between constraint dimensions. The matching information includes measure configuration information, which represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project.

[0046] The design module is used to determine the revegetation design scheme based on the matching information; the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0047] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0048] The memory stores the instructions that the computer executes;

[0049] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0050] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0051] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0052] The wind farm revegetation measure scheme determination method and apparatus provided in this application embodiment, in response to design instructions, acquires input information, and further, based on a preset multidimensional database, performs association matching with the input information as query conditions to determine matching information, and further determines a revegetation design scheme based on the matching information; wherein, the input information includes the location parameters, topographic parameters, altitude parameters, and revegetation level of the wind farm project, the preset multidimensional database is formed by the association of multiple sub-databases, each sub-database is indexed with multi-level parameters, the multi-level parameters represent at least one constraint dimension and the hierarchical progression relationship between constraint dimensions, the matching information includes measure configuration information, the measure configuration information represents the measure configuration and corresponding plant configuration of the engineering area of ​​the wind farm project, and the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project. The method for determining wind farm revegetation measures in this application utilizes a pre-defined multidimensional database indexed by multiple sub-databases and linked together. This database uses input information including location, topography, altitude, and revegetation level as query conditions for correlation and matching, replacing the manual method of searching multiple standard documents and historical data for experience-based judgment. This significantly improves the efficiency of determining revegetation measures. Furthermore, the pre-defined multidimensional database is indexed based on the hierarchical relationships between the constraint dimensions represented by the multi-level parameters, reducing operational errors in manually selecting suitable plant species and developing targeted restoration measures, and improving the accuracy of matching revegetation measures with project environmental conditions and engineering requirements. Therefore, this method improves the accuracy and efficiency of determining wind farm revegetation measures. Attached Figure Description

[0053] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0054] Figure 1 A flowchart illustrating a method for determining a wind farm revegetation measure provided in this application. Figure 1 ;

[0055] Figure 2 A flowchart illustrating a method for determining a wind farm revegetation measure provided in this application. Figure 2 ;

[0056] Figure 3 A flowchart illustrating a method for determining a wind farm revegetation measure provided in this application. Figure 3 ;

[0057] Figure 4 A flowchart illustrating a matching information adjustment method provided in this application;

[0058] Figure 5 A schematic diagram of a device for determining a wind farm revegetation measure scheme provided in this application;

[0059] Figure 6 This is a schematic diagram of the structure of an electronic device provided in this application.

[0060] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0062] It should be noted that the data involved in this application (including but not limited to data used for analysis, data stored, data displayed, etc.) are all information and data that have been fully authorized by all parties, and the collection, use, processing, transmission, provision, disclosure and application of the relevant data shall comply with relevant laws, regulations and standards.

[0063] It should be noted that the method and apparatus for determining the scheme of wind farm revegetation measures in this application can be used in the field of wind farm ecological restoration design technology, or in any field other than the field of wind farm ecological restoration design technology. The application field of the method and apparatus for determining the scheme of wind farm revegetation measures in this application is not limited.

[0064] Traditional revegetation design requires manually selecting suitable plant species based on the project area, developing targeted restoration measures, and manually drawing the revegetation areas on engineering drawings, while also adhering to local regulations for cost control. This process relies heavily on the experience of designers and necessitates frequent consultation of multiple regulatory documents and historical data, resulting in long design cycles, low efficiency, high costs, and susceptibility to design quality issues due to human error. Furthermore, significant climate differences exist between regions, and different sub-projects within the same project have drastically different requirements for revegetation measures. Adopting a single design approach can easily lead to low plant survival rates and insufficient coverage, failing to meet ecological restoration goals.

[0065] Specifically, in the plant variety selection stage, designers need to manually consult floras, local vegetation restoration guidelines, and historical engineering data based on the climate characteristics of the project area to select suitable plant species and determine planting density and configuration ratios. Because the hydrothermal conditions vary significantly between different climate zones and at different altitudes within the same climate zone, manual selection is not only time-consuming and labor-intensive, but also prone to inappropriate variety selection due to incomplete data or insufficient experience, resulting in low survival rates and poor restoration effects. In the restoration measure development stage, differentiated revegetation measures need to be formulated for different terrains and different sub-projects. Without systematic database support, relying solely on individual experience for a single design makes it difficult to consider the differences in underlying surface conditions across different sub-projects, leading to a disconnect between measures and actual needs, resulting in insufficient coverage and substandard soil and water conservation effects.

[0066] Therefore, there is an urgent need for a solution that can accurately determine the revegetation measures for wind farms in order to meet the complexity and efficiency requirements of wind farm revegetation measure design.

[0067] The method for determining wind farm revegetation measures in this application utilizes a pre-defined multidimensional database indexed by multiple sub-databases and linked together. This database uses input information including location, topography, altitude, and revegetation level as query conditions for correlation and matching, replacing the manual method of searching multiple standard documents and historical data for experience-based judgment. This significantly improves the efficiency of determining revegetation measures. Furthermore, the pre-defined multidimensional database is indexed based on the hierarchical relationships between the constraint dimensions represented by the multi-level parameters, reducing operational errors in manually selecting suitable plant species and developing targeted restoration measures, and improving the accuracy of matching revegetation measures with project environmental conditions and engineering requirements. Therefore, this method improves the accuracy and efficiency of determining wind farm revegetation measures.

[0068] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0069] Figure 1 A flowchart illustrating a method for determining a wind farm revegetation measure provided in this application. Figure 1 The execution subject of this method can be a server, computer terminal, or other device, such as... Figure 1 As shown, the method includes:

[0070] S101. Responding to design instructions, obtain input information; the input information includes the location parameters, topographic parameters, altitude parameters, and revegetation level of the wind farm project;

[0071] S102. Based on a preset multidimensional database, perform association matching with the input information as the query condition to determine the matching information; wherein, the preset multidimensional database is formed by association of multiple sub-databases, each sub-database is indexed with multi-level parameters, the multi-level parameters represent at least one constraint dimension and the hierarchical progression relationship between constraint dimensions, and the matching information includes measure configuration information, which represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project.

[0072] S103. Based on the matching information, determine the revegetation design scheme; wherein, the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0073] In step S101, the implementing entity of this application receives user operations through a human-computer interaction interface and initiates the process of determining the wind farm revegetation measures scheme in response to design instructions.

[0074] Design instructions can refer to instructions issued by users to initiate the wind farm revegetation design process by clicking interface buttons, selecting menu options, or entering specific trigger characters.

[0075] Wind farm projects can refer to new energy power generation engineering construction projects that include main engineering facilities such as wind turbine generators, on-site roads, substations, and power collection lines. Their construction process will disturb the ground surface and damage the original vegetation, requiring vegetation restoration design.

[0076] Input information refers to a set of data characterizing the basic conditions and design objectives of a wind farm project, serving as the basis for subsequent correlation and matching queries. Input information may include data such as the wind farm project's location parameters, terrain parameters, altitude parameters, and revegetation level.

[0077] Location parameters characterize the geographical spatial location of a wind farm project. These parameters may include, but are not limited to, administrative division information (e.g., province, city, county) or latitude and longitude coordinates. It should be understood that different location parameters will result in different climate zones for the project, thus affecting the selection range of suitable plant species and the climate adaptability requirements of revegetation measures. For example, projects located in subtropical monsoon climate zones and those located in temperate continental climate zones have significantly different hydrothermal conditions. The former is suitable for warm- and humid plant species (e.g., Bermuda grass, rhododendron), while the latter is suitable for cold- and drought-resistant plant species (e.g., crested wheatgrass, sea buckthorn). Incorrect identification of location parameters will lead to low plant survival rates.

[0078] Topographic parameters characterize the topographic features of the area where a wind farm project is located. These parameters can include, but are not limited to, terrain categories such as plains, hills, and mountains. It should be understood that different topographic parameters will lead to variations in the specific configuration and construction difficulty of revegetation measures. For example, plains are primarily open spaces, suitable for simple measures such as hydroseeding and turfing; mountainous areas, however, have numerous excavated and filled slopes, requiring slope stabilization measures such as reinforced netting hydroseeding and vegetation mat installation. Incorrect identification of topographic parameters can lead to slope instability or insufficient vegetation cover.

[0079] Altitude parameters characterize the elevation of the area where a wind farm project is located. These parameters can be the average elevation or a range of elevations within the project area. It should be understood that different altitude parameters lead to variations in climatic elements such as temperature, precipitation, and air pressure, as well as the vertical distribution of vegetation zones in the wind farm project area. This, in turn, affects the altitude adaptability of suitable plant species and the adjustment of planting density. For example, within the same climatic zone, low-altitude areas (plains to low mountains) have higher temperatures and more abundant precipitation, making it suitable to select warm- and humid, widely adaptable plant species. High-altitude areas (high mountains) have lower temperatures and stronger ultraviolet radiation, requiring the selection of cold-resistant and UV-resistant special adaptable species, and the planting density needs to be appropriately increased to compensate for the loss of survival rate under harsh conditions. Incorrect altitude parameter identification will result in low plant survival rates and poor revegetation effects.

[0080] The revegetation level can be a parameter that characterizes the design target level of revegetation. It is used to distinguish the configuration standards of revegetation measures under different ecological restoration standards, landscape effect requirements and cost budget constraints. The revegetation level can be preset, such as basic, upgraded or landscape type.

[0081] In one possible implementation, the aforementioned location parameters, terrain parameters, altitude parameters, and revegetation level can be obtained through drop-down menu selection, text box input, map point selection, or file import. The obtained input information can be formatted and validated to ensure that the values ​​of each parameter are within the preset valid range. After the validation is passed, the subsequent steps can be performed.

[0082] It should be understood that the parameters in the input information can be expanded or refined according to actual design requirements. For example, the location parameter can further include watershed information or ecological functional zone information where the project is located, and the terrain parameter can further include slope information or aspect information. This application does not limit this.

[0083] It should also be understood that the classification criteria for revegetation levels can be adjusted according to the technical specifications of different regions and industries. For example, in some regions, it can be divided into three levels: basic, standard, and enhanced. The essence is to differentiate design objectives through the classification of levels. This application does not limit the specific names and number of revegetation levels.

[0084] In step S102, the executing entity of this application calls a preset multidimensional database, uses the input information as a query condition, performs hierarchical progressive association matching between the sub-databases, and outputs matching information containing measure configuration information.

[0085] A pre-built multidimensional database can refer to a structured data set that is pre-built and stored in relevant storage media to support the automated determination of greening measures. The pre-built multidimensional database is formed by the association of multiple sub-databases. Data connections are established between the sub-databases through pre-built association fields to realize cross-database data flow and integration.

[0086] The use of multi-level parameters to index each sub-database refers to organizing and arranging the data records of each sub-database according to multiple parameter levels, forming a tree-like or hierarchical index structure, so as to facilitate step-by-step query matching according to the priority of constraints. For example, each sub-database may include a climate type database, a suitable plant database, and a revegetation measure database; wherein, the climate type database is used to match climate zones, the suitable plant database is used to match plant configurations of suitable plants, and the revegetation measure database is used to match the configurations of revegetation measures.

[0087] In one possible implementation, the pre-defined multidimensional database can be constructed through the following steps: First, collect and organize basic data sources such as climate natural zoning data, existing phytoremediation technology data, standard specification documents, and historical wind farm revegetation project data; then, perform data cleaning, standardization, and classification coding on the basic data sources to form a structured basic dataset; next, determine the constraint dimensions and hierarchical relationships of each sub-database according to its functional positioning, and design a multi-level parameter index structure; finally, establish data connection relationships between the sub-databases through pre-defined association fields (such as climate zone codes representing climate types, revegetation level codes, etc.) to form an interconnected multidimensional database.

[0088] The multi-level parameter representation of at least one constraint dimension and the hierarchical progression between constraint dimensions can be understood as follows: multi-level parameters are used to represent various constraints (i.e., constraint dimensions) that affect the selection of revegetation measures, and there is a priority order or logical sequence relationship between each constraint dimension (i.e., hierarchical progression relationship). The constraint dimensions of the preceding level are used to determine the basic adaptation conditions, and the constraint dimensions of the subsequent level are used to further refine the matching results under the basic adaptation conditions. The constraint dimension can refer to the natural condition dimension or design target dimension of the revegetation design scheme that affects the configuration of revegetation measures, such as climate zone, altitude, topography, revegetation level, etc. The hierarchical progression relationship can refer to the step-by-step screening logic from macro to micro, from basic adaptation to target refinement. For example, in the suitable plant database, the climate zone is used as the first-level constraint dimension (representing macro natural conditions), the altitude parameter is used as the second-level constraint dimension (representing micro natural conditions), and the revegetation level is used as the third-level constraint dimension (representing design target), forming a hierarchical progression relationship from the first level to the second level to the third level.

[0089] Using input information as query conditions for correlation matching can refer to mapping the parameter values ​​in the input information to the query key values ​​of the corresponding level index in the sub-database, retrieving and filtering data step by step according to the hierarchical relationship, and passing intermediate matching results between multiple sub-databases through correlation fields, and finally integrating them to form complete matching information.

[0090] Matching information can refer to the collection of various data information required to characterize the revegetation measure configuration scheme, obtained after association and matching. For example, matching information may include, but is not limited to, measure configuration information, plant configuration information, etc.

[0091] The measure configuration information refers to the types and combinations of revegetation measures applicable to each engineering area of ​​the wind farm project, as well as the plant configuration information selected for the revegetation measures, used to guide the selection of measures for specific revegetation projects. For example, when the terrain parameter in the input information is "mountainous" and the revegetation level is "upgraded", the revegetation measure database is matched according to the hierarchical progression of terrain category, engineering type, and revegetation level, and the specific content of the measure configuration information can be determined, which may include: reinforced netting and hydroseeding measures are applicable to excavated slope areas, and the plant varieties are bermudagrass, carpet grass, bahiagrass, and pigeon pea; strip seeding and afforestation measures are applicable to filled slope areas, and the plant varieties are rhododendron and Chinese fir; a combination of turf and dense shrub hedges is applicable to the booster station area, and the plant variety is rhododendron.

[0092] The engineering area of ​​a wind farm project can refer to the area where the wind farm project is located that needs to be revegetated. For example, the engineering area of ​​a wind farm project may include, but is not limited to, excavated slope areas, filled slope areas, wind turbine platform areas, substation areas, and on-site road areas.

[0093] The configuration of measures can refer to the type of revegetation measures selected for a specific project area, which may include, but is not limited to, single measures or combinations of multiple measures such as hydroseeding, reinforced netting hydroseeding, seedling planting, vegetation carpet laying, flower beds and borders, ecological permeable hardening, turf laying, and dense shrub hedges.

[0094] Plant configuration can refer to information such as suitable plant varieties, planting density, configuration ratio and mixed sowing ratio selected for specific greening measures, and may include, but is not limited to, herbaceous plant varieties and sowing quantity, shrub varieties and spacing, tree varieties and spacing.

[0095] It should be understood that the number and type of sub-databases can be expanded according to actual design requirements, and this application does not limit the specific number and name of the sub-databases.

[0096] It should also be understood that the specific number of hierarchical relationships and the constraint dimensions of each level can be adjusted according to the data organization needs. For example, a two-level hierarchical structure can be used in some sub-databases, while a four-level hierarchical structure can be used in other sub-databases. The essence is to achieve the step-by-step filtering of constraints through hierarchical indexing. This application does not limit the specific number of levels.

[0097] In step S103, the implementing entity of this application will structurally integrate and format the matching information obtained by association matching to generate a greening design scheme.

[0098] A revegetation design scheme can refer to a structured set of information that represents a complete scheme for the configuration of revegetation measures in a wind farm project, and is used to guide the specific implementation of the revegetation project.

[0099] The revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​wind farm projects. It can be understood that the revegetation design scheme provides technical basis and data support for the construction preparation, material procurement, plant selection, implementation of measures, and quality acceptance of the revegetation project. This ensures that the configuration of revegetation measures in each engineering area is based on evidence, and that the revegetation measures are matched with the project's environmental conditions and engineering needs to achieve the expected ecological restoration goals.

[0100] In one possible implementation, the revegetation design scheme is stored in a structured data format on a relevant storage medium and can be output as a document file according to a preset template format, such as a wind farm revegetation design specification, a revegetation measure configuration table, a plant type configuration table, etc., so that designers can review, approve and deliver it for use.

[0101] It should be understood that the output format and carrier of the greening design scheme can be adjusted according to actual needs. For example, it can be output as a PDF document, Word document, Excel spreadsheet or structured data file (such as XML or JSON format) to facilitate data exchange and system integration in different application scenarios. This application does not limit the output format.

[0102] It should also be understood that the content of the revegetation design scheme can be expanded according to the complexity of the project and the requirements of the design depth. For example, information such as investment budget, construction schedule, maintenance and management requirements, and monitoring and evaluation indicators can be added. The essence is to form a complete technical solution that can guide the implementation of the project by structurally integrating and matching the data information. This application does not limit the specific content of the revegetation design scheme.

[0103] This embodiment provides a method for determining wind farm revegetation measures. It utilizes a pre-defined multi-dimensional database indexed by multiple sub-databases and linked by multi-level parameters. Input information including location, topography, altitude, and revegetation level is used as query conditions for correlation and matching, replacing the manual method of searching multiple standard documents and historical data one by one, thus improving the efficiency of determining revegetation measures. Simultaneously, the pre-defined multi-dimensional database is indexed through the hierarchical relationship between the constraint dimensions represented by the multi-level parameters, reducing operational errors in manually selecting suitable plant species and formulating targeted restoration measures, and improving the accuracy of matching revegetation measures with project environmental conditions and engineering requirements. The method of this application improves the accuracy and efficiency of determining wind farm revegetation measures.

[0104] Figure 2 A flowchart illustrating a method for determining a wind farm revegetation measure provided in this application. Figure 2 In this embodiment Figure 1Based on the examples, the method for determining the revegetation measures for wind farms is described in detail, such as... Figure 2 As shown, the method includes:

[0105] S201. Responding to design instructions, obtain input information; the input information includes the location parameters, topographic parameters, altitude parameters, and revegetation level of the wind farm project.

[0106] S202. Using location parameters as query conditions, index and match the climate type database to determine the target climate zone; whereby the target climate zone represents the spatial distribution range of the climate type to which the wind farm project belongs.

[0107] Among them, several sub-databases include a climate type database, which stores mapping data between location parameters and climate zones that characterize climate types.

[0108] In one possible implementation, constructing a climate type database may include:

[0109] This process involves acquiring national administrative division vector map data, latitude and longitude grid vector map data, and climate zone distribution map data. Using relevant geographic information system software or technology, these three types of vector map data are overlaid to establish spatial correspondences between administrative division boundaries, latitude and longitude grids, and climate zone boundaries. Attribute associations are then applied to the overlaid layers, assigning a corresponding climate zone code to each administrative division unit or latitude and longitude grid unit. The processed spatial data is then structured and stored, creating a data table with administrative division codes or latitude and longitude grid codes as index keys and climate zone codes as index values, resulting in a climate type database. By inputting location parameters (administrative division information or latitude and longitude coordinates) into this database, users can locate and query the corresponding climate zone.

[0110] Furthermore, the specific steps for determining the target climate zone by indexing and matching the climate type database using location parameters as query conditions can be as follows: First, identify the parameter type of the location parameter. If the location parameter is administrative division information (e.g., provincial, municipal, county, etc.), extract the administrative division code corresponding to this information. Use this administrative division code as the query key and perform an exact match in the administrative division index table of the climate type database to obtain the climate zone code corresponding to the administrative division code. Then, determine this climate zone code as the target climate zone. Second, if the location parameter is latitude and longitude coordinate information (e.g., a coordinate pair composed of longitude and latitude values), map the latitude and longitude coordinates to the corresponding latitude and longitude grid code according to the preset latitude and longitude grid division rules. Use this latitude and longitude grid code as the query key and perform a match in the latitude and longitude grid index table of the climate type database to obtain the climate zone code corresponding to the latitude and longitude grid code. Then, determine this climate zone code as the target climate zone.

[0111] It should be understood that the data sources for the climate type database may include climate zoning data released by relevant regional meteorological bureaus, vegetation climate zoning data compiled by relevant scientific research institutions, etc. The data update cycle can be set according to actual needs. This application does not limit the specific data sources and update mechanisms of the climate type database.

[0112] It is understandable that a pre-built climate type database can enable rapid and automatic identification of project climate conditions, replacing manual review of climate zoning maps and experience-based judgments. This improves the efficiency and accuracy of determining climate zones that characterize climate types and provides a precise data foundation for subsequent steps.

[0113] S203. Using the target climate zone, altitude parameters, and revegetation level as query conditions, index and match the suitable plant database to determine the target plant configuration information.

[0114] Among them, several sub-databases include a suitable plant database, which stores plant species configuration data applicable under different climatic conditions, altitude conditions and revegetation levels, i.e. target plant configuration information. This plant configuration information may include, for example, the names of herbaceous, shrub, and tree plant species and planting density data.

[0115] In one alternative implementation, the multi-level parameters in the suitable plant database are indexed with climate zone as the first index level, altitude parameter as the second index level, and revegetation level as the third index level.

[0116] In this step, the first index level is used to filter the range of suitable plant varieties from the perspective of macro-climatic conditions; the second index level is used to further refine the suitable plant varieties from the perspective of vertical zonation conditions; and the third index level is used to determine the final plant configuration scheme from the perspective of design goals, i.e., to obtain the target plant configuration information. The various index levels achieve progressive filtering through a hierarchical relationship, with the matching results of the preceding levels serving as query constraints for subsequent levels, forming a three-level progressive index structure from climate zone to altitude to revegetation level.

[0117] Based on this, step S203 may include:

[0118] S2031. Using the target climate zone as the query condition, perform index matching on the suitable plant database to obtain the first index result; using the altitude parameter as the query condition, perform index matching on the first index result to obtain the second index result.

[0119] S2032. Using the revegetation level as the query condition, perform index matching on the second index results to obtain the target plant configuration information.

[0120] Specifically, using the target climate zone (which can be represented by an encoding) as the query key, a matching process is performed at the first index level of the suitable plant database to retrieve the set of all plant species records corresponding to the target climate zone, forming the first index result. The first index result represents the range of plant species that are ecologically adaptable under the hydrothermal conditions of the target climate zone. Furthermore, the altitude parameters of the input information are processed by altitude classification, for example, mapping the altitude parameters to altitude levels such as plains (e.g., below 200 meters), low mountains (e.g., 200 to 1500 meters), or high mountains (e.g., above 1500 meters) according to preset altitude classification rules. Using the grade code as the query key, a second-level filtering and matching process is performed based on the first index result to retrieve a subset of plant variety records suitable for the altitude conditions, forming the second index result. The second index result represents the range of plant varieties with ecological adaptability under the comprehensive constraints of the target climate zone and the altitude parameter. Further, using the revegetation level of the input information as the query key, a third-level filtering and matching process is performed based on the second index result to retrieve plant variety configuration records that meet the design goals of the revegetation level, which are identified as the target plant configuration information. The target plant configuration information includes parameters such as the specific plant variety name, planting density, configuration ratio, and mixed sowing ratio.

[0121] For example, when the target climate zone is "subtropical monsoon climate zone", the altitude parameter is "800 meters" (corresponding to the altitude level code "low mountain"), and the revegetation level is "upgraded", the implementing entity of this application uses "subtropical monsoon climate zone" as the query key value to match at the first index level and obtains the first index result; then uses "low mountain" as the query key value to match at the second index level in the first index result and obtains the second index result; then uses "upgraded" as the query key value to match at the third index level in the second index result and determines the target plant configuration information as "herbaceous varieties: Bermuda grass, carpet grass, Bahia grass, pigeon pea (corresponding planting density and mixed sowing ratio: 60 kg per hectare and 4:2:2:2); shrub varieties: rhododendron (corresponding plant spacing: 0.5 m × 0.5 m); tree varieties: Chinese fir (corresponding plant spacing: 5 m × 5 m)".

[0122] It should be understood that the altitude classification rules can be adjusted according to the actual conditions of different regions and climate zones. For example, in some high-altitude areas, the upper limit of the low mountain altitude classification can be adjusted to 2000m. This application does not limit the specific threshold of altitude classification. At the same time, parameters such as planting density and mixed sowing ratio in the plant configuration information can be optimized and adjusted according to actual engineering experience and local specifications. This application does not limit the specific parameter values ​​of the target plant configuration information.

[0123] It is understandable that by using the target climate zone, altitude parameters, and revegetation level as constraints, and following a hierarchical progression from macro-climate conditions to micro-altitude conditions and then to design goals, a step-by-step indexing and matching process is performed in the suitable plant database. This process sequentially determines the first index result, the second index result, and the target plant configuration information, thereby obtaining the target plant configuration information. This ensures that the plant variety selection matches the climate conditions, altitude conditions, and revegetation design goals of the project area, thereby improving the accuracy of plant configuration and the reliability of the later survival rate. It also avoids the problem of inappropriate variety selection due to incomplete data or insufficient experience during manual screening.

[0124] S204. Based on the target plant configuration information, using terrain parameters and revegetation level as query conditions, index and match the revegetation measures database to determine the target measures configuration information and obtain matching information.

[0125] The database includes several sub-databases, including a revegetation measures database. This database stores applicable revegetation measures for different terrain conditions, project area types, and revegetation levels. These measures can include, for example, hydroseeding, reinforced netting hydroseeding, seedling planting, vegetation mats, flower beds and borders, and permeable ecological hardening. Based on the target plant configuration information and the revegetation measure type, the database can then determine the target measure configuration information and obtain matching information.

[0126] In one alternative implementation, the revegetation measures database uses terrain parameters as the first index level, project area type as the second index level, and revegetation level as the third index level.

[0127] The index consists of three levels: the first level filters applicable revegetation measures based on basic terrain conditions; the second level refines the measures based on specific engineering needs; and the third level determines the final measure configuration based on design objectives. Each index level is progressively selected through a hierarchical relationship, with the matching results of the preceding levels serving as constraints for subsequent levels, forming a three-tiered progressive index structure from terrain parameters to engineering area type and then to revegetation level.

[0128] Based on this, step S204 may include:

[0129] S2041. Using terrain parameters as query conditions, perform index matching on the revegetation measures database to obtain the third index result.

[0130] Specifically, using the terrain parameters of the input information as the query key, a match is made in the first index level of the revegetation measures database to retrieve a set of records of all revegetation measures applicable to the terrain conditions, forming a third index result. The third index result represents the range of revegetation measures applicable to the basic engineering conditions under the terrain conditions.

[0131] S2042. Obtain a preset set of engineering area types. For each engineering area type in the set of engineering area types, perform index matching on the third index result to obtain the fourth sub-index result, and determine each fourth sub-index result as the fourth index result.

[0132] The pre-defined set of engineering area types refers to a pre-defined classification set of various engineering area types that require revegetation measures in a wind farm project. This set can be determined based on the composition and construction disturbance characteristics of the main wind farm project. For example, the engineering area type can be an excavation slope type, an embankment slope type, or a planar type. It should be understood that the pre-defined set of engineering area types can be determined, expanded, or adjusted according to the scale of the wind farm project, topographical conditions, and the composition of the main project. This application does not limit the specific composition of the engineering area type set.

[0133] Specifically, for each engineering area type in the set of engineering area types, the engineering area type is used as the query key value. Based on the third index result, the second index level is used for filtering and matching to retrieve a subset of records of revegetation measures applicable to the engineering area type, forming the fourth sub-index result corresponding to the engineering area type. The fourth sub-index results of each engineering area type are summarized to form the fourth index result. The fourth index result represents the range of revegetation measures types that are applicable under the comprehensive constraints of the terrain conditions and each engineering area type.

[0134] S2043. Using the greening level as the query condition, perform index matching on the fourth index result to obtain the fifth index result.

[0135] Specifically, using the revegetation level of the input information as the query key, the third index level is used for filtering and matching based on the fourth index result to retrieve the revegetation measure type configuration records that meet the design goals of the revegetation level, forming the fifth index result. The fifth index result represents the final revegetation measure type configuration determined under the comprehensive constraints of the terrain conditions, the types of engineering areas, and the revegetation level.

[0136] S2044. Associate the target plant configuration information with the fifth index result to obtain the target measure configuration information.

[0137] Specifically, the target plant configuration information obtained is linked and integrated with the fifth index result through preset association fields, so that the plant variety and planting density parameters in the target plant configuration information are automatically filled into the technical indicator fields corresponding to each measure configuration in the fifth index result, forming complete target measure configuration information containing measure configuration and corresponding plant configuration.

[0138] For example, when the terrain parameter is "mountainous" and the revegetation level is "upgraded", the implementing entity of this application uses "mountainous" as the query key to match at the first index level, obtaining the third index result; then, it obtains a set of engineering area types (e.g., including cut slope type, fill slope type, and planar type), and performs a second index level match on each engineering area type in the third index result, obtaining the fourth index result (e.g., the revegetation measure type corresponding to the cut slope type: reinforced netting and hydroseeding; the revegetation measure type corresponding to the fill slope type: strip seeding and afforestation; the revegetation measure type corresponding to the planar type: ecological grass planting brick tree); then, it uses "upgraded" as the query key to match at the third index level in the fourth index result, obtaining the fifth index result; finally, it associates and fills the target plant configuration information (herbs: Bermuda grass, carpet grass, Bahia grass, pigeon pea, 60 kg / ha, 4:2:2:2; shrubs: rhododendron, 0.5m×0.5m; trees: Chinese fir, 5m×5m) into the fifth index result to form the target measure configuration information.

[0139] It is understandable that by using topographic parameters, project area type, and revegetation level as constraints, and following a hierarchical progression from topographic conditions to project requirements to design goals, the revegetation measures database is indexed and matched level by level. The third, fourth, and fifth index results are determined sequentially, and the target plant configuration information is linked and integrated with the fifth index result to obtain the target measure configuration information. This ensures that the type of revegetation measures matches the project's topographic conditions and the actual needs of each sub-project, thereby improving the pertinence and effectiveness of the revegetation measures and avoiding the problem of measures being out of touch with project conditions due to a single design.

[0140] It is understandable that by sequentially calling the climate type database, suitable plant database, and revegetation measure database, and using the input information as the query condition for hierarchical and progressive association matching, the entire process from climate condition identification to plant variety selection to measure type configuration can be automated, thereby automating the determination of revegetation measure schemes and improving the efficiency and accuracy of revegetation measure scheme determination.

[0141] S205. Using the target measure configuration information as the query condition, the construction technology database is indexed and matched to determine the target technical document information, which represents the construction technology parameters of the project area.

[0142] Among them, several sub-databases include a construction process database, which stores standardized construction process data for various types of revegetation measures, including technical documents such as construction preparation requirements, process flow, technical indicators, and quality standards. The plant variety and planting density fields in the technical indicators are dynamically linked fields that are automatically filled in by the target plant configuration information.

[0143] Specifically, using the revegetation measure type (which can be represented by a code) in the target measure configuration information as the query key, an index matching is performed in the construction process database to retrieve the standardized construction process record corresponding to that revegetation measure type. Then, the plant configuration information (plant variety, planting density, configuration ratio, etc.) in the target measure configuration information is automatically filled into the dynamic association field of the technical indicators in the construction process record, forming complete target technical document information. Target technical document information can include construction preparation requirements (e.g., slope clearing, material preparation, equipment debugging, etc.), process flow (e.g., substrate preparation, spraying, maintenance management, etc.), technical indicators (e.g., substrate thickness, spraying pressure, plant variety and sowing quantity, etc., dynamically entered parameters), and quality standards (e.g., coverage rate, survival rate, erosion resistance, etc., acceptance indicators).

[0144] S206. Determine the target technical document information and target measure configuration information to obtain matching information.

[0145] Specifically, the target technical document information and target measure configuration information can be directly used as matching information, or they can be integrated to form matching information that includes measure configuration information, plant configuration information, and construction technology information, serving as the data basis for subsequently determining the revegetation design scheme. The matching information can be stored in a structured data format, including data fields such as area type identifiers for each project area, measure type codes, plant variety configuration parameters, construction technology parameters, and quality standard parameters.

[0146] It is understandable that by indexing and matching the construction process database with the target measure configuration information as the query condition, and automatically filling the target plant configuration information into the technical indicator field of the construction process, the standardized generation of the greening measure construction process and the automatic association of plant configuration parameters can be realized. This achieves the automated integration of greening measure configuration and construction process technical documents, thereby improving the completeness and feasibility of the greening design scheme and avoiding parameter mismatch or omission problems when manually writing construction process documents.

[0147] S207. Based on the matching information, determine the revegetation design scheme; wherein, the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0148] In this embodiment, based on the aforementioned embodiments, on the one hand, a hierarchical progressive association matching mechanism with multi-level parameters is used to replace the experience-based judgment method of manually querying multiple standard documents and historical data one by one, thereby solving the problems of traditional revegetation measure design relying on manual experience, long design cycle, and low efficiency; on the other hand, through the hierarchical association matching of climate type database, suitable plant database, revegetation measure database, and construction technology database, the entire process from climate condition identification to plant variety selection to measure type configuration and construction technology determination is further automated; thus, the efficiency of determining revegetation measure schemes is improved, while the matching accuracy of revegetation measures with project environmental conditions and engineering requirements is improved.

[0149] Figure 3 A flowchart illustrating a method for determining a wind farm revegetation measure provided in this application. Figure 3 The method for determining the revegetation measures for wind farms is explained in detail, such as... Figure 4 As shown, the method includes:

[0150] S301. Responding to design instructions, obtain input information; wherein, the input information includes the location parameters, topographic parameters, altitude parameters, and revegetation level of the wind farm project.

[0151] S302. Based on a preset multidimensional database, perform association matching using the input information as the query condition to determine the matching information; wherein, the preset multidimensional database is formed by association of multiple sub-databases, and each sub-database is indexed with multi-level parameters. The multi-level parameters represent at least one constraint dimension and the hierarchical progression relationship between constraint dimensions. The matching information includes measure configuration information, which represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project.

[0152] S303. Perform element identification on the engineering drawings to determine the slope line information; wherein, the slope line information represents the distribution and direction of topographic undulation within the engineering area.

[0153] The input information also includes engineering drawings of the wind farm project, which represent the spatial distribution of the engineering area of ​​the wind farm project.

[0154] In one possible implementation, the engineering drawings can be obtained by standardizing computer-aided design (CAD) format drawings or geographic information system (GIS) format drawings, such as the site road plan, wind turbine platform plan, and substation plan provided by the main design unit of the wind farm.

[0155] Slope lines can refer to graphic elements in engineering drawings used to represent the direction of terrain slope and slope change. For example, slope lines are drawn as short line segments perpendicular to contour lines, and the direction of the short line segments indicates the direction of slope decrease.

[0156] In one possible implementation, the slope line information can be determined based on graphic feature extraction techniques using image recognition algorithms (such as edge detection algorithms, Hough transform algorithms, or semantic segmentation algorithms based on deep learning).

[0157] For example, the implementing entity of this application identifies the contour of the slope line in the engineering drawing through the edge detection algorithm in the computer vision library (such as OpenCV), extracts the spatial distribution coordinates, line segment direction and distribution quantity per unit area of ​​the slope line, and forms a slope line information dataset; or, through a trained image recognition model, it identifies the elements of the drawing, automatically annotates and extracts the spatial position and orientation attributes of the slope line graphic elements.

[0158] It should be understood that engineering drawings can be in common vector graphics formats or raster image formats. The entity implementing this application can process them uniformly through format conversion or image parsing technology. This application does not limit the specific format of engineering drawings.

[0159] It is understandable that by identifying slope line elements on engineering drawings, the distribution and direction information of terrain undulations can be automatically obtained, providing a data foundation for the automatic division and type determination of subsequent engineering areas, replacing manual map reading and interpretation, and improving the efficiency and accuracy of terrain information extraction.

[0160] S304. Based on the slope line information, divide the engineering drawings to determine multiple engineering sub-regions and determine the engineering area type corresponding to each engineering sub-region.

[0161] Among them, the engineering sub-area can refer to a local area unit with relatively uniform terrain features and the need for revegetation measures, obtained after dividing the overall engineering area of ​​the wind farm project according to the slope line information.

[0162] In one possible implementation, the engineering drawings are divided based on the slope line information to determine multiple engineering sub-regions. This can include: performing spatial cluster analysis on the slope line information to merge adjacent areas with similar slope line distribution characteristics into the same engineering sub-region; or, based on preset engineering area division rules (such as according to main engineering design elements such as road stationing segments and platform boundary lines), the engineering area is divided into segments in combination with the slope line information to obtain multiple engineering sub-regions.

[0163] In one optional implementation, determining the engineering area type corresponding to each engineering sub-area may include:

[0164] S3041. For each engineering sub-region, determine the slope distribution data corresponding to the engineering sub-region from the slope line information;

[0165] S3042. Determine the density characteristics based on the slope line distribution data; whereby the density characteristics characterize the number of slope lines distributed per unit area.

[0166] S3043. Based on density characteristics, the engineering sub-area is determined as either a slope area or a planar area;

[0167] S3044. If the engineering sub-region is a slope region, the type of excavation slope or fill slope shall be determined according to the direction of the slope line in the sub-region data. This shall be the engineering region type corresponding to the engineering sub-region.

[0168] S3045. If the engineering sub-region is a planar region, then the planar type is determined to be the engineering region type corresponding to the engineering sub-region.

[0169] Specifically, density characteristics are positively correlated with terrain slope. A preset density threshold is used to distinguish between slope areas and flat areas: when the number of slope indicator lines per unit area exceeds the preset density threshold, the area is determined to be a slope area, indicating significant terrain undulation and slope variation; when the number of slope indicator lines per unit area does not exceed the preset density threshold, it is determined to be a flat area, indicating relatively flat terrain. The direction in which the slope indicator lines point is used to determine the slope type: when the slope indicator lines point in a decreasing elevation direction, it is determined to be a cut slope type, indicating that the area is a slope formed by excavation; when the slope indicator lines point in a increasing elevation direction, it is determined to be a fill slope type, indicating that the area is a slope formed by filling.

[0170] For example, the implementing entity of this application performs the following processing on each engineering sub-region by traversing each engineering sub-region: First, extract the distribution data of the slope indicator lines within the engineering sub-region from the slope indicator line information, including the number of slope indicator lines, total length, spatial distribution range, and set of pointing directions; Second, calculate the density feature, which represents the ratio of the number of slope indicator lines within the engineering sub-region to the area of ​​the engineering sub-region; Third, compare the density feature with a preset density threshold. If the density feature is greater than the preset density threshold, it is marked as a slope region and enters the slope type judgment process; otherwise, it is marked as a planar region, and the engineering region type is determined to be a planar type; For slope regions, count the pointing directions of the slope indicator lines. If the proportion of slope indicator lines pointing in the direction of decreasing elevation exceeds a preset proportion threshold (e.g., 50%), the engineering region type is determined to be an excavation slope type; if the proportion of slope indicator lines pointing in the direction of increasing elevation exceeds a preset proportion threshold, the engineering region type is determined to be an embankment slope type.

[0171] It should be understood that the preset density threshold and preset ratio threshold can be set and adjusted according to different terrain conditions, engineering drawings of different scales and different engineering accuracy requirements. This application does not limit the specific values ​​of the preset density threshold and preset ratio threshold.

[0172] It is understandable that by identifying slope line elements on engineering drawings and automatically dividing engineering sub-regions based on the distribution density and direction of the slope lines, the engineering sub-regions can be determined as excavation slope type, fill slope type, or planar type. This achieves automated identification and classification of engineering sub-region types, which can replace manual drawing and zoning, thereby improving the efficiency and accuracy of engineering sub-region division and providing a spatial basis for the precise configuration of subsequent revegetation measures.

[0173] S305. For each engineering sub-region, based on the engineering region type of the engineering sub-region, extract the measure configuration information corresponding to the engineering region type from the matching information, and configure the measure sub-region information.

[0174] For example, for a project sub-area of ​​type "cut slope", the corresponding measure configuration information "reinforced netting and hydroseeding" is extracted from the matching information, and the plant configuration information (such as varieties and sowing amount of bermudagrass, carpet grass, etc.) corresponding to the measure is obtained to form the measure sub-area configuration information for the cut slope area; for a project sub-area of ​​type "planar", the corresponding measure configuration information "hydroseeding" or "laying turf" is extracted to form the measure sub-area configuration information for the planar area.

[0175] In one optional implementation, the multiple sub-databases include a revegetation cost database; the method may further include:

[0176] For each engineering sub-area, the revegetation cost database is indexed and matched using the sub-area's measure configuration information as the query condition to determine the target revegetation cost. The target revegetation cost represents the cost of implementing revegetation measures in the engineering sub-area. Based on each target revegetation cost, the total revegetation cost is obtained. If the total revegetation cost exceeds a preset cost threshold, an alarm is triggered. The alarm is used to instruct the user to adjust the revegetation design plan.

[0177] The greening cost database is used to store data such as cost indicators for various types of greening measures.

[0178] Specifically, the implementing entity of this application uses the measure type (which can be represented by a code) in the measure division configuration information as the query key value, matches and determines the comprehensive cost index cost of the measure type in the greening cost database, and calculates the target greening cost of the project division area by combining the area data of the project division area; further, the target greening costs of each project division area are summarized to obtain the total greening cost; the total greening cost is compared with the preset cost threshold, and if the cost threshold is exceeded, an alarm message is output through the human-computer interaction interface to prompt the designer to adjust and optimize the greening design scheme, such as reducing the greening level or adjusting the measure configuration.

[0179] It is understandable that by indexing and matching the greening cost database with the configuration information of the measures as the query conditions, the target greening cost and total greening cost of each engineering section area can be automatically calculated, and over-budget warnings can be issued. This can realize the automated accounting and dynamic monitoring of greening costs, improve the timeliness and accuracy of cost control, and thus avoid rework of the plan and extension of the design cycle due to cost overruns.

[0180] S306. Based on the configuration information of each measure section, associate and bind the configuration information of each measure section with the corresponding engineering section area to obtain the greening design scheme.

[0181] Specifically, the implementing entity of this application associates and binds the configuration information of the measures in each engineering sub-area with the engineering sub-area to form a spatialized greening measure configuration scheme, which is a greening design scheme.

[0182] For example, the associated and bound revegetation design scheme includes the spatial boundary coordinates of each engineering sub-area, engineering area type, measure configuration information, plant configuration information and construction technology information, stored in the form of structured data, and can be output as a revegetation measure layout map and supporting design documents according to a preset format.

[0183] In one possible implementation, a greening measure layout map can be obtained by filling each engineering sub-area with a preset filling pattern from a preset greening measure pattern database.

[0184] For example, the revegetation measure pattern database pre-stores filling patterns corresponding to each type of revegetation measure, such as diagonal filling patterns for hydroseeding, grid filling patterns for reinforced netting hydroseeding, and tree-shaped filling patterns for seedling afforestation. The implementing entity of this application can extract the corresponding filling patterns from the revegetation measure pattern database based on the measure type in the measure configuration information of each engineering sub-area, and automatically fill them according to the spatial boundary coordinates of the engineering sub-area to generate a visualized revegetation measure layout map.

[0185] For example, during the generation of the revegetation measure layout map, the implementing entity of this application can also collect area data for each engineering sub-area, and store the area data in association with the sub-area configuration information for subsequent engineering quantity statistics and resource allocation. The revegetation measure layout map is output in vector graphics or raster image form, including map elements such as legend, scale bar, and north arrow, and conforms to the requirements of engineering drawing specifications.

[0186] It is understandable that by automatically dividing the engineering sections into sub-regions through slope line element recognition on engineering drawings, and spatially associating and binding the sub-regional configuration information of the measures with the sub-regions of the engineering, a revegetation design scheme containing spatial location information can be obtained. This can achieve a precise correspondence between the configuration of revegetation measures and the spatial location of the project, thereby improving the spatial accuracy and feasibility of the revegetation design scheme, and providing precise guidance for the subsequent construction layout and material allocation of the revegetation project.

[0187] In this embodiment, based on the aforementioned embodiments, on the one hand, by identifying slope line elements in the engineering drawings and automatically dividing the engineering sub-areas, the problem of low efficiency and easy omission in traditional manual drawing identification and zoning is solved; on the other hand, by spatially associating and binding the configuration information of the measures sub-areas with the engineering sub-areas, the spatial positioning of the greening measures configuration is further realized; thereby improving the spatial accuracy and feasibility of the greening design scheme, and at the same time improving the efficiency of determining the greening measures scheme.

[0188] Figure 4 This is a flowchart illustrating a matching information adjustment method provided in this application. Based on the aforementioned embodiments, this embodiment considers the user's personalized adjustment needs for the automatically generated revegetation measure configuration and explains the corresponding adjustment steps, such as... Figure 5 As shown, the method includes:

[0189] S401. In response to the user's adjustment instruction, obtain adjustment information; wherein, the adjustment information represents the user's intention to change the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0190] Among them, the adjustment command can refer to the operation command issued by the user through the human-computer interaction interface to trigger the greening measure configuration adjustment process. It can be a response signal triggered by means of clicking the adjustment button, selecting the adjustment menu, dragging and dropping to modify the configuration item, or entering the adjustment parameter.

[0191] Adjustment information can represent the user's intention to change the configuration of revegetation measures in a specific project area. For example, adjustment information includes data fields such as the input information to be changed, the original configuration information, the desired configuration information, and optional explanations of the reasons for adjustment.

[0192] For example, after viewing the automatically generated revegetation design scheme in the human-computer interaction interface, if the user believes that the current "basic" revegetation level cannot meet the ecological restoration goals, or receives an alarm message that the total revegetation cost exceeds the preset cost threshold, the user can adjust the revegetation level from "basic" to "upgraded" by adjusting the interface, so as to update the matching information and obtain new matching information.

[0193] It should be understood that the proposed changes to the input information in the adjustment information may include changes to any input information such as location parameters, terrain parameters, altitude parameters, and revegetation level, or may include redefinition of the engineering area type or re-division of the engineering sub-area. This application does not limit the specific type of the proposed changes to the input information.

[0194] It is understandable that by obtaining adjustment information containing proposed changes to the input, designers can optimize and adjust the revegetation design scheme from the source of input, rather than being limited to partial modifications to the output results, thus improving the flexibility of the adjustment operation and the systematic nature of the adjustment effect.

[0195] S402. Based on the adjustment information, update the matching information to obtain new matching information.

[0196] Specifically, the implementing entity of this application replaces the corresponding parameters in the original input information with the proposed change input information in the adjustment information, uses the updated complete input information as the query condition, and sequentially performs hierarchical progressive association matching on the preset multidimensional database to redetermine the new matching information.

[0197] In one possible implementation, if the adjustment information only involves adjusting the matching information and not the input information, the implementing entity of this application may only update the specific content of the matching information. For example, if the adjustment information includes the code of the engineering sub-area, the original measure configuration information is "reinforced netting and spraying," and the desired measure configuration information is "vegetation mat laying and anchor frame beams," then the implementing entity of this application locates the corresponding measure configuration record in the matching information based on the code of the engineering sub-area, replaces the original measure configuration information "reinforced netting and spraying" with the desired measure configuration information "vegetation mat laying and anchor frame beams," and obtains new matching information. This new matching information is used to regenerate the content of the revegetation design scheme for that engineering sub-area, so as to achieve local adjustment without affecting the configuration scheme of other engineering sub-areas, improve the efficiency of adjustment processing, and ensure data consistency.

[0198] In one possible implementation, the above steps may include validating the adjustment information, checking whether the desired measure configuration information exists in the revegetation measure database, and whether the compatibility of the measure configuration information with the engineering area type of the project sub-region conforms to preset rules. If the verification passes, an update process is executed; if the verification fails, an error message is output through the human-computer interaction interface, guiding the user to re-enter the adjustment information.

[0199] In this embodiment, based on the aforementioned embodiments, the matching information is updated in response to user adjustment commands to address the problem that automatically generated revegetation design schemes may not fully meet special engineering conditions or personalized design needs, thereby achieving the effect of improving the flexibility and reliability of revegetation design schemes.

[0200] Figure 5 A schematic diagram of a device for determining a wind farm revegetation measure scheme provided in this application is shown below. Figure 6 As shown, the wind farm revegetation scheme determination device 50 includes: a response module 501, a matching module 502, and a design module 503.

[0201] The response module 501 is used to respond to design instructions and obtain input information, including the location parameters, terrain parameters, altitude parameters, and revegetation level of the wind farm project.

[0202] The matching module 502 is used to perform association matching based on a preset multidimensional database and the input information as the query condition to determine the matching information. The preset multidimensional database is formed by the association of multiple sub-databases. Each sub-database is indexed by multi-level parameters. The multi-level parameters represent at least one constraint dimension and the hierarchical relationship between the constraint dimensions. The matching information includes measure configuration information, which represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project.

[0203] Design module 503 is used to determine the revegetation design scheme based on the matching information; wherein, the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

[0204] In an optional example, multiple sub-databases include a climate type database, a suitable plant database, and a revegetation measures database; the matching module 502 is further configured to: perform index matching on the climate type database using location parameters as query conditions to determine the target climate zone; wherein, the target climate zone represents the spatial distribution range of the climate type to which the wind farm project belongs; perform index matching on the suitable plant database using the target climate zone, altitude parameters, and revegetation level as query conditions to determine the target plant configuration information; and, based on the target plant configuration information, perform index matching on the revegetation measures database using terrain parameters and revegetation level as query conditions to determine the target measures configuration information, thereby obtaining matching information.

[0205] In an optional example, the multi-level parameters in the suitable plant database are indexed with climate zone as the first index level, altitude parameter as the second index level, and revegetation level as the third index level. The matching module 502 is also used to: perform index matching on the suitable plant database with the target climate zone as the query condition to obtain the first index result; perform index matching on the first index result with the altitude parameter as the query condition to obtain the second index result; and perform index matching on the second index result with the revegetation level as the query condition to obtain the target plant configuration information.

[0206] In an optional example, the revegetation measures database uses terrain parameters as the first index level, project area type as the second index level, and revegetation level as the third index level. The matching module 502 is further configured to: use terrain parameters as query conditions to perform index matching on the revegetation measures database to obtain the third index result; obtain a preset set of project area types, and for each project area type in the set, perform index matching on the third index result to obtain the fourth sub-index result, and determine each fourth sub-index result as the fourth index result; use the revegetation level as query conditions to perform index matching on the fourth index result to obtain the fifth index result; and associate the target plant configuration information with the fifth index result to obtain the target measure configuration information.

[0207] In an optional example, the multiple sub-databases also include a construction technology database; the matching module 502 is further configured to: use the target measure configuration information as a query condition to perform index matching on the construction technology database, determine the target technical document information, the target technical document information representing the construction technology parameters of the engineering area; determine the target technical document information and the target measure configuration information to obtain matching information.

[0208] In an optional example, the input information also includes engineering drawings of the wind farm project, which represent the spatial distribution of the project area. The design module 503 is further used to: identify elements in the engineering drawings and determine slope line information; wherein, the slope line information represents the distribution and direction of topographic relief within the project area; divide the engineering drawings according to the slope line information to determine multiple engineering sub-regions and determine the engineering area type corresponding to each engineering sub-region; for each engineering sub-region, extract the measure configuration information corresponding to the engineering area type from the matching information according to the engineering area type of the engineering sub-region, and set it as measure sub-region configuration information; and associate and bind each measure sub-region configuration information with the corresponding engineering sub-region according to the measure sub-region configuration information to obtain the revegetation design scheme.

[0209] In an optional example, design module 503 is further configured to: for each engineering sub-region, determine the distribution data of the slope line corresponding to the engineering sub-region from the slope line information; determine the density characteristics based on the slope line distribution data; wherein the density characteristics characterize the number of slope lines distributed per unit area; determine the engineering sub-region as a slope region or a planar region based on the density characteristics; if the engineering sub-region is a slope region, determine the excavation slope type or the fill slope type as the engineering region type corresponding to the engineering sub-region based on the direction of the slope line in the slope line sub-region data; if the engineering sub-region is a planar region, determine the planar type as the engineering region type corresponding to the engineering sub-region.

[0210] In an optional example, multiple sub-databases include a greening cost database; design module 503 is further configured to: for each engineering sub-area, use the sub-area measure configuration information as query conditions to index and match the greening cost database to determine the target greening cost; wherein, the target greening cost represents the cost of implementing greening measures in the engineering sub-area; obtain the total greening cost based on each target greening cost; if the total greening cost is greater than a preset cost threshold, trigger an alarm message; wherein, the alarm message is used to instruct the user to adjust the greening design scheme.

[0211] In an optional example, the wind farm revegetation measure scheme determination device 50 further includes an adjustment module, which is used to: obtain adjustment information in response to the user's adjustment instruction; wherein the adjustment information represents the user's intention to change the configuration of revegetation measures in the engineering area of ​​the wind farm project; and update the matching information according to the adjustment information to obtain new matching information.

[0212] The wind farm revegetation measure scheme determination device in this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principle are the same, and will not be repeated here.

[0213] Figure 6 A schematic diagram of the structure of an electronic device provided in this application, such as... ​ As shown, the electronic device 60 provided in this embodiment includes at least one processor 601 and a memory 602. Optionally, the electronic device 60 further includes a communication component 603. The processor 601, memory 602, and communication component 603 are connected via a bus 604.

[0214] In a specific implementation, at least one processor 601 executes computer execution instructions stored in memory 602, causing at least one processor 601 to perform the above-described method.

[0215] The specific implementation process of processor 601 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0216] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0217] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0218] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0219] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0220] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0221] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as magnetic disks or optical disks.

[0222] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for determining a scheme for revegetation measures in a wind farm, characterized in that, include: In response to design instructions, input information is acquired; wherein, the input information includes the location parameters, terrain parameters, altitude parameters, and revegetation level of the wind farm project; Based on a preset multidimensional database, the input information is used as a query condition to perform association matching and determine matching information; wherein, the preset multidimensional database is formed by association of multiple sub-databases, each sub-database is indexed with multi-level parameters, the multi-level parameters represent at least one constraint dimension and the hierarchical progression relationship between the constraint dimensions, and the matching information includes measure configuration information, the measure configuration information represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project; Based on the matching information, a revegetation design scheme is determined; wherein, the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

2. The method according to claim 1, characterized in that, The multiple sub-databases include a climate type database, a suitable plant database, and a revegetation measures database; the multidimensional database based on the preset information uses the input information as query conditions to perform association matching to determine the matching information, including: Using the location parameters as query conditions, the climate type database is indexed and matched to determine the target climate zone; wherein, the target climate zone represents the spatial distribution range of the climate type to which the wind farm project belongs; Using the target climate zone, the altitude parameter, and the revegetation level as query conditions, the suitable plant database is indexed and matched to determine the target plant configuration information; Based on the target plant configuration information, using the terrain parameters and the revegetation level as query conditions, the revegetation measures database is indexed and matched to determine the target measures configuration information and obtain the matching information.

3. The method according to claim 2, characterized in that, The multi-level parameters in the suitable plant database are indexed with climate zone as the first index level, altitude parameter as the second index level, and revegetation level as the third index level. The process of using the target climate zone, altitude parameter, and revegetation level as query conditions to perform index matching on the suitable plant database and determine target plant configuration information includes: Using the target climate zone as the query condition, the suitable plant database is indexed and matched to obtain a first index result; using the altitude parameter as the query condition, the first index result is indexed and matched to obtain a second index result. Using the revegetation level as the query condition, the second index result is matched to obtain the target plant configuration information.

4. The method according to claim 2, characterized in that, The revegetation measures database uses terrain parameters as the first index level, project area type as the second index level, and revegetation level as the third index level. The process of indexing and matching the revegetation measures database based on the target plant configuration information, using the terrain parameters and the revegetation level as query conditions, to determine the target measures configuration information includes: Using the terrain parameters as query conditions, the database of revegetation measures is indexed and matched to obtain a third index result; Obtain a preset set of engineering area types. For each engineering area type in the set of engineering area types, perform index matching on the third index result to obtain a fourth sub-index result, and determine each of the fourth sub-index results as the fourth index result. Using the regreening level as the query condition, the fourth index result is matched to obtain the fifth index result; The target plant configuration information and the fifth index result are associated to obtain the target measure configuration information.

5. The method according to claim 2, characterized in that, The plurality of sub-databases also includes a construction technology database; the method further includes: Using the target measure configuration information as the query condition, the construction process database is indexed and matched to determine the target technical document information, which represents the construction process parameters of the project area; The matching information is obtained by determining the target technical document information and the target measure configuration information.

6. The method according to claim 1, characterized in that, The input information also includes engineering drawings of the wind farm project, which represent the spatial distribution of the wind farm project's engineering area; determining the revegetation design scheme based on the matching information includes: The engineering drawings are subjected to element identification to determine slope line information; wherein, the slope line information represents the distribution and direction of topographic undulation within the engineering area; Based on the slope line information, the engineering drawings are divided to determine multiple engineering sub-regions, and the engineering region type corresponding to each engineering sub-region is determined. For each of the aforementioned engineering sub-regions, based on the engineering sub-region type, measure configuration information corresponding to the engineering sub-region type is extracted from the matching information to form measure sub-region configuration information; Based on the configuration information of each of the aforementioned measures, the configuration information of each of the aforementioned measures is associated and bound with the corresponding engineering sub-area to obtain the revegetation design scheme.

7. The method according to claim 6, characterized in that, Determining the engineering area type corresponding to each of the aforementioned engineering sub-areas includes: For each engineering sub-region, the slope line distribution data corresponding to the engineering sub-region is determined from the slope line information; Based on the slope line distribution data, density characteristics are determined; wherein, the density characteristics represent the number of slope lines distributed per unit area; Based on the density characteristics, the engineering sub-region is determined to be a slope region or a planar region; If the engineering sub-region is the slope region, then the excavation slope type or the fill slope type is determined as the engineering region type corresponding to the engineering sub-region based on the direction of the slope line in the slope line sub-region data. If the engineering sub-region is the planar region, then the planar type is determined to be the engineering region type corresponding to the engineering sub-region.

8. The method according to claim 6, characterized in that, The plurality of sub-databases includes a revegetation cost database; the method further includes: For each of the aforementioned engineering sub-regions, the greening cost database is indexed and matched using the sub-regional measure configuration information as the query condition to determine the target greening cost; wherein, the target greening cost represents the cost of implementing greening measures in the engineering sub-region. Based on the stated target revegetation costs, the total revegetation cost is obtained; If the total cost of revegetation exceeds a preset cost threshold, an alarm message is triggered; wherein, the alarm message is used to instruct the user to adjust the revegetation design scheme.

9. The method according to any one of claims 1-8, characterized in that, Also includes: In response to the user's adjustment command, the system obtains adjustment information; wherein, the adjustment information represents the user's intention to change the configuration of revegetation measures in the engineering area of ​​the wind farm project; Based on the adjustment information, the matching information is updated to obtain new matching information.

10. A device for determining a scheme for wind farm revegetation measures, characterized in that, include: The response module is used to respond to design instructions and obtain input information; wherein, the input information includes the location parameters, terrain parameters, altitude parameters, and revegetation level of the wind farm project; The matching module is used to perform association matching based on a preset multidimensional database and the input information as query conditions to determine matching information; wherein, the preset multidimensional database is formed by association of multiple sub-databases, each sub-database is indexed by multi-level parameters, the multi-level parameters represent at least one constraint dimension and the hierarchical progression relationship between the constraint dimensions, and the matching information includes measure configuration information, which represents the measure configuration and corresponding vegetation configuration of the engineering area of ​​the wind farm project; The design module is used to determine the revegetation design scheme based on the matching information; wherein the revegetation design scheme is used to guide the configuration of revegetation measures in the engineering area of ​​the wind farm project.

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