An airport large earthwork engineering intelligent deployment method, system and device thereof

Abstract

This application discloses an intelligent allocation method, system, and equipment for large-scale earthwork engineering projects at airports, relating to the field of earthwork construction technology. The method includes collecting and preprocessing earthwork engineering data for the airport to be built to obtain a standardized engineering dataset; constructing an intelligent earthwork allocation model based on linear programming; generating initial earthwork allocation schemes for each allocation zone of the airport to be built based on the standardized engineering dataset, preset allocation constraints, and allocation priorities in the intelligent earthwork allocation model; visualizing the initial earthwork allocation schemes based on different allocation zones; and dynamically updating the initial earthwork allocation schemes by acquiring real-time construction monitoring data for each allocation zone during construction to obtain the latest earthwork allocation scheme. This application improves the efficiency of earthwork allocation in large-scale earthwork engineering projects at airports.

Description

Technical Field

[0001] This application relates to the field of earthwork construction technology, and in particular to an intelligent allocation method, system and equipment for large-scale earthwork projects at airports. Background Technology

[0002] Earthwork engineering, as a fundamental process in airport construction, has the core task of achieving site leveling through the precise transportation and allocation of earth and stone, thus providing the necessary conditions for subsequent construction. In large-scale airport projects, the volume of earth excavation and filling is enormous, and the rationality of the allocation plan directly determines the project's construction progress, cost control, and quality.

[0003] Traditional earthwork allocation methods are usually formulated by designers based on allocation principles and past experience. However, they often only focus on the current needs and implementation of the project, while ignoring potential future land use changes. This leads to frequent earthwork allocation during construction and a lack of long-term planning. Consequently, there is a deficiency in the low allocation efficiency of large-scale earthwork projects such as airports, which needs to be improved. Summary of the Invention

[0004] To improve the efficiency of earthwork allocation in large-scale earthwork projects at airports, this application provides an intelligent allocation method, system, and equipment for large-scale earthwork projects at airports.

[0005] Firstly, the objective of this invention is achieved through the following technical solution:

[0006] A method for intelligent allocation of resources for large-scale earthwork projects at airports, comprising:

[0007] Collect and preprocess earthwork data for the airport to be built to obtain a standardized engineering dataset;

[0008] Construct an intelligent earthwork allocation model based on linear programming; in the intelligent earthwork allocation model, based on the standardized engineering dataset, preset allocation constraints and allocation priorities, generate initial earthwork allocation schemes for each allocation zone corresponding to the airport to be built.

[0009] The initial earthwork allocation plan is visualized based on different allocation zones;

[0010] During construction, real-time construction monitoring data of each allocation zone is acquired, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan.

[0011] By adopting the above-mentioned technical solutions, the digitalization and intelligentization of the allocation process in large-scale earthwork engineering at airports have been achieved. This not only improves the accuracy of decision-making and enhances planning efficiency, but also enables timely responses to changes at the construction site, ensuring the smooth implementation of earthwork engineering and providing efficient and intelligent allocation methods for airport construction. Specifically, the intelligent earthwork allocation model of this application transforms traditionally dependent qualitative decision-making into data-driven quantitative optimization. By pre-setting allocation constraints (such as restricting the transport of soil from areas whose excavated soil properties do not meet the backfill material requirements of a certain allocation zone to that zone, and restricting the transport of soil from areas lacking soil, etc.) and allocation priorities (such as prioritizing the use of excavated material from the same zone for backfilling roadbed areas, etc.), ineffective transportation volume is reduced, thereby achieving precise cost control throughout the entire airport construction cycle. During construction, by acquiring real-time construction monitoring data from each allocation zone, the initial earthwork allocation plan is dynamically updated, ensuring that the allocation plan can respond promptly to changes at the construction site, achieving optimal resource allocation and effective control of construction progress. Thus, this application can provide efficient and intelligent allocation methods in complex construction environments.

[0012] In a preferred embodiment, this application describes the construction of an intelligent earthwork allocation model based on linear programming. Within this model, based on the standardized engineering dataset, preset allocation constraints, and allocation priorities, initial earthwork allocation schemes are generated for each allocation zone corresponding to the airport to be constructed. Specifically, this includes:

[0013] Based on the soil properties and filling requirements, the allocation zones are subdivided into several sub-items, and a zone matrix with dimension m×m is established, where m = number of allocation zones × number of sub-items in each allocation zone + 1;

[0014] Based on the partition matrix, construct the transport distance matrix, material source matrix, fill-cut ratio matrix, fill matrix, and cut matrix;

[0015] Establish a constraint matrix based on the obtained allocation requirement information; establish a priority matrix based on the allocation priority.

[0016] The sum of rows in the material source matrix is ​​constrained by the excavation matrix; the sum of columns in the material source matrix is ​​constrained by the filling matrix and the fill-excavation ratio coefficient.

[0017] The optimal initial allocation scheme is obtained by minimizing the objective function, thus obtaining the initial earthwork allocation scheme for each allocation zone corresponding to the airport to be built.

[0018] By adopting the above technical solution, the allocation zone is subdivided into several sub-items based on the soil properties and filling requirements, accommodating external soil sources, supporting multi-zone scenarios in large airports, and improving the adaptability of the earthwork allocation scheme to complex environments. The compliance of soil materials is rigidly constrained by a constraint matrix (e.g., prohibiting the filling of organic soil in the roadbed area), while priority is softly guided by a priority matrix (e.g., allocation to nearby areas), reducing manual intervention. The material source matrix row constraints (excavation volume ≥ output volume) and column constraints (fill volume = input volume) used in this application avoid resource waste, ensuring a balance between excavation and filling earthwork volumes.

[0019] In a preferred embodiment of this application: the material source matrix includes a material source matrix P for the roadbed area, a material source matrix Q for the soil surface area, a material source matrix R for the working area, and a material source matrix S for the reconstruction and expansion project area; the cut-fill ratio matrix includes a cut-fill ratio matrix for the roadbed area. Matrix of fill-cut ratio in soil surface area Work area cut-fill ratio matrix and the cut-fill ratio matrix of the expansion and renovation area ;

[0020] The minimization objective function for:

[0021] in, and To adjust the partition identifier; This is the transport distance matrix, referring to the distance from the allocation zone. To allocate partitions Earthwork transportation distance; This is the constraint matrix; This is the priority matrix.

[0022] By adopting the above technical solution, the distance matrix and rule weights are combined. and With the same dimension as the effective volume, it is easy to achieve precise minimization of transportation costs through comprehensive cost quantification calculation. This application further refines the allocation strategy by defining specific matrices (material source matrix, fill-cut ratio matrix) for different areas (roadbed area, soil surface area, working area, reconstruction and expansion project area) and minimizing the objective function expression. The material source matrix is ​​also optimized by zone collaboration to adapt to different filling standards (such as roadbed compaction degree > 95%).

[0023] In a preferred embodiment of this application: the collection and preprocessing of earthwork engineering data for the airport to be constructed to obtain a standardized engineering dataset includes:

[0024] Based on the actual construction area and engineering requirements of the airport to be built, the airport to be built is divided into multiple allocation zones;

[0025] Obtain relevant engineering data on earthwork allocation through engineering construction drawings, including excavation and filling volume, soil properties, cut-fill ratio coefficient, and earthwork transportation distance;

[0026] Based on the construction data of the airport to be built, relevant information on project implementation is obtained, including construction plan and schedule, construction method, and land acquisition status.

[0027] Acquire on-site measurement data, and perform data correction and preprocessing on the earthwork allocation-related engineering data;

[0028] The pre-processed earthwork allocation-related engineering data and the engineering implementation-related information are classified and integrated according to allocation zones and soil properties to obtain a standardized engineering dataset.

[0029] By adopting the above technical solutions, the importance of data acquisition and preprocessing is demonstrated, including the classification and integration of relevant engineering data on earthwork allocation and engineering implementation information to form a standardized engineering dataset, thus ensuring the quality of input data.

[0030] In a preferred embodiment of this application: during the construction process, acquiring real-time construction monitoring data for each allocation zone and dynamically updating the initial earthwork allocation plan to obtain the latest earthwork allocation plan specifically includes:

[0031] During construction, elevation data is transmitted daily through sensors on excavators and compactors, and the daily excavation and filling volumes are calculated based on this elevation data.

[0032] The remaining work volume is updated based on the daily completed excavation and filling volumes.

[0033] In the intelligent earthwork allocation model, calculations are performed based on the remaining work volume to obtain the latest earthwork allocation plan after updating the work volume.

[0034] Obtain the updated data of the earthwork allocation plan before and after the update, and visualize the updated content based on the updated data and the partition identifiers of each allocation zone.

[0035] By adopting the above technical solution, during the construction process, the daily excavation and filling volume is updated by transmitting elevation data from sensors, and the remaining work volume is dynamically adjusted accordingly. This allows the allocation plan to reflect the actual situation on site in real time, greatly improving the flexibility and adaptability of the construction plan.

[0036] In a preferred embodiment of this application, the plurality of sub-items include site excavation, special excavation, trench backfilling, and surface backfilling; the method further includes:

[0037] The allocation zones are established based on the different soil properties and cut-fill ratios within the engineering site, creating fill matrices, cut-fill ratio matrices, and material source matrices for the roadbed zone, surface zone, working zone, and reconstruction / expansion project zone:

[0038] Roadway / channel area: Fill matrix (F), fill-cut ratio coefficient matrix (F) ), Material source matrix (P)

[0039] Soil surface area: Fill matrix (D), fill-cut ratio coefficient matrix ( ), Material source matrix (Q)

[0040] Work area: Fill matrix (G), Fill-cut ratio coefficient matrix (G) ), Source Matrix (R)

[0041] Reconstruction and Expansion Project Area: Fill Matrix (K), Fill-Cut Ratio Coefficient Matrix ( ), Material source matrix (S);

[0042] The allocation requirements information includes:

[0043] Based on the obtained information on fill material requirements and soil properties for each allocation zone, soil transportation to the corresponding allocation zone whose soil properties do not meet the fill material requirements is restricted.

[0044] Obtain the shortage and surplus status of each allocation zone, restrict the outward transport of soil from allocation zones in the shortage status, and restrict the transport of soil into allocation zones in the surplus status.

[0045] The constraint matrix is ​​filled with 1s and 0s, where 1 indicates that soil transportation to the allocation zone is allowed, and 0 indicates that soil transportation to the allocation zone is not allowed.

[0046] By adopting the above technical solutions, based on the subdivided allocation zones and their internal sub-items (site excavation, special excavation, etc.), and establishing corresponding filling matrices, filling-excavation ratio matrices, and material source matrices, the material flow within each allocation zone can be managed more precisely, ensuring that the properties of the fill material meet the requirements, avoiding unnecessary transportation losses, and improving overall construction efficiency.

[0047] In a preferred embodiment of this application: the allocation priority is set based on the allocation priority principle, which includes: prioritizing allocation within the same allocation zone and prioritizing the use of excavated material from the site for backfilling the roadway area;

[0048] The priority matrix is ​​filled with 0.5 and 1, where 0.5 represents a higher allocation priority and 1 represents a lower allocation priority;

[0049] The constraint of the row sum of the material source matrix by the excavation matrix and the constraint of the column sum of the material source matrix by the filling matrix and the fill-excavation ratio coefficient include:

[0050] The material source matrices P, Q, R, and S are horizontally spliced ​​together. The rows of the spliced ​​material source matrix are constrained according to the excavation matrix so that the sum of each row of the material source matrix is ​​less than or equal to the excavation volume of the partition represented by the current row.

[0051] Constrain the material source matrix columns corresponding to different soil properties based on the fill matrix and fill-cut ratio coefficient matrix, so that the sum of each column of the material source matrix for different soil properties is equal to the fill volume of the corresponding soil material required for the partition represented by the current column.

[0052] By adopting the above technical solutions, setting priority principles for allocation, and reflecting priorities in a matrix format, it is ensured that the allocation process follows established rules, prioritizing the needs of key areas. At the same time, by constraining the rows and columns of the material source matrix, the effective allocation and rational use of resources are guaranteed, reducing resource waste.

[0053] Secondly, the objective of this invention is achieved through the following technical solution:

[0054] An intelligent dispatching system for large-scale earthwork projects at airports, the system comprising:

[0055] The data acquisition and preprocessing module is used to collect earthwork engineering data of the airport to be built and preprocess it to obtain a standardized engineering dataset.

[0056] The model building and scheme generation module is used to build an intelligent earthwork allocation model based on linear programming. In the intelligent earthwork allocation model, based on the standardized engineering dataset, preset allocation constraints and allocation priorities, an initial earthwork allocation scheme corresponding to each allocation zone of the airport to be built is generated.

[0057] The scheme visualization module is used to visualize the initial earthwork allocation scheme based on different allocation zones;

[0058] The dynamic update module is used to acquire real-time construction monitoring data of each allocation zone during the construction process, and to dynamically update the initial earthwork allocation plan to obtain the latest earthwork allocation plan.

[0059] By adopting the above technical solutions, a complete closed-loop process is formed, covering multiple functional modules such as data acquisition and preprocessing, model building and solution generation, solution visualization and dynamic updates. This supports full lifecycle management from data collection to solution execution, improving the intelligence and management level of the entire earthwork project.

[0060] Thirdly, the objective of this invention is achieved through the following technical solution:

[0061] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described intelligent allocation method for large-scale earthwork engineering at an airport.

[0062] Fourthly, the objective of this invention is achieved through the following technical solution:

[0063] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described intelligent allocation method for large-scale earthwork engineering at an airport.

[0064] In summary, this application includes at least one of the following beneficial technical effects:

[0065] 1. This application constructs an intelligent allocation model based on linear programming, which generates an initial allocation scheme using preset constraints and priorities, effectively improving the efficiency of earthwork allocation and resource utilization. The dynamic update mechanism of real-time construction monitoring data enables the allocation scheme to be flexibly adjusted according to the actual situation, improving the adaptability and construction quality during the construction process;

[0066] 2. The earthwork allocation zones were refined, and multiple matrices were established for haul distance, material source, cut-fill ratio, etc., which helps to accurately calculate the demand and supply of each allocation zone and ensures the scientific and rational nature of the allocation plan. Attached Figure Description

[0067] Figure 1 This is a flowchart of an intelligent allocation method for large-scale earthwork engineering at an airport, according to one embodiment of this application.

[0068] Figure 2 This is a flowchart of step S2 in an embodiment of an intelligent allocation method for large-scale earthwork engineering at an airport.

[0069] Figure 3 This is a schematic diagram of a device according to one embodiment of this application. Detailed Implementation

[0070] The present application will be further described in detail below with reference to the accompanying drawings.

[0071] In one embodiment, such as Figure 1 As shown, this application discloses an intelligent allocation method for large-scale earthwork engineering at airports, which specifically includes the following steps:

[0072] S1: Collect and preprocess the earthwork data of the airport to be built to obtain a standardized engineering dataset.

[0073] In this embodiment, the earthwork engineering data for the airport to be constructed includes site zoning information, soil properties, excavation and filling volumes, cut-fill-fill ratio coefficient, haulage distance between zones, construction progress and plan, land acquisition status, and engineering requirements. The standardized engineering dataset refers to structured data categorized and integrated according to allocation zones and soil properties. It includes key parameters such as excavation and filling volumes, soil properties, cut-fill-fill ratio coefficient, haulage distance, and construction progress. Data preprocessing includes data cleaning (removing outliers and filling missing values), data deduplication, data correction (combined with on-site measurement calibration), and classification and integration. The cut-fill-fill ratio coefficient is the ratio of the compacted volume of earthwork to its natural volume (e.g., 1.2 means that 1 m³ of natural soil occupies 0.83 m³ of space after compaction).

[0074] Specifically, step S1 includes:

[0075] S11: Based on the actual construction area and engineering requirements of the airport to be built, the airport to be built will be divided into multiple allocation zones.

[0076] Specifically, allocation zones refer to independent earthwork operation areas divided according to airport functional areas (runways, aprons, work areas, etc.) and construction units. Each zone has a unique zone identifier and engineering attributes. The actual construction area is constrained by the engineering construction location, such as land acquisition boundaries and equipment operating radii. Engineering requirements include high-density fill material for the runway core area in the runway trench area, and ordinary fill material for the green belt in the soil surface area. The building foundation in the work area requires medium density.

[0077] For example, the airport to be built is divided into:

[0078] Track and runway areas: P1 (runway section), P2 (taxiway section)

[0079] Soil surface area: P3 (East Green Belt), P4 (West Green Belt)

[0080] Work area: P5 (terminal foundation)

[0081] Renovation and expansion area: P6 (old runway renovation).

[0082] S12: Obtain relevant engineering data on earthwork allocation through engineering construction drawings, including excavation and filling volume, soil properties, cut-fill ratio coefficient, and earthwork transportation distance.

[0083] In this embodiment, the engineering construction drawings are CAD construction drawings or BIM drawing models; the excavation volume (natural volume), fill volume (compacted volume), and soil properties (sand, clay, gravel) of each allocation zone are extracted. The earthwork transportation distance is based on the centroid coordinates of the zone, and the shortest transportation distance between zones is calculated using GIS route planning tools, with the unit being km.

[0084] S13: Based on the construction data of the airport to be built, obtain relevant information on project implementation, including construction plan and schedule, construction method, and land acquisition status.

[0085] Specifically, the construction plan includes phased schedules, such as the P1 excavation needing to be completed by September 1, 2025. Construction methods are determined through equipment configuration; for example, dynamic compaction will be used in area P5, with a cut-fill ratio calculated at 1.35. Land acquisition status will be marked based on the actual land handover status, requiring the marking of unhandled areas, such as area P6, whose status is "not yet handed over" and will not be included in the allocation at this time.

[0086] S14: Obtain on-site measurement data and perform data correction and preprocessing on earthwork allocation-related engineering data.

[0087] Specifically, data correction involves calibrating data based on actual on-site measurements. For example, if the drawing indicates an excavation volume of 60,000 m³ for P1, but the on-site measurement is 55,000 m³, the measured value will be used, and the reason for the correction will be noted. For missing values, if there is no cut-fill ratio coefficient, the average value of the zone with the same soil properties will be used. Alternatively, if the data type is missing, a prompt for manual correction can be used.

[0088] S15: The pre-processed earthwork allocation-related engineering data and engineering implementation-related information are classified and integrated according to allocation zones and soil properties to obtain a standardized engineering dataset.

[0089] Specifically, the standardized engineering dataset includes the main table structure of each allocation zone's basic attributes, zone ID, soil type, excavation volume, fill volume, cut-fill ratio, and construction status, as well as the relational table structure of the inter-zone transport distance matrix.

[0090] S2: Construct an intelligent earthwork allocation model based on linear programming; in the intelligent earthwork allocation model, based on standardized engineering datasets, preset allocation constraints and allocation priorities, generate initial earthwork allocation schemes for each allocation zone of the airport to be built.

[0091] In this embodiment, the intelligent earthwork allocation model is a mathematical optimization model that uses minimizing transportation costs as the objective function to solve for the optimal allocation path under the constraints of excavation volume ≤ supply and fill volume = demand. Allocation priority is set based on allocation priority principles. These principles include: prioritizing allocation within the same zone and prioritizing the use of excavated material for backfilling trench areas.

[0092] Specifically, such as Figure 2 As shown, step S2 includes:

[0093] S21: Based on the soil properties and filling requirements, the allocation zone is subdivided into several sub-items, and a partition matrix with dimension m×m is established, where m = number of allocation zones × number of sub-items in each allocation zone + 1.

[0094] In this embodiment, dimension m plus 1 represents the external soil source. Several sub-items include site excavation (general soil material), special excavation (special excavation other than general excavation, such as stone or special soil), trench backfilling, and surface backfilling. The external soil source is treated as an independent sub-item, numbered m. For example, if four zones are established, and each allocation zone has four sub-items, then m = 4 × 4 + 1 = 17.

[0095] S22: Construct the haul distance matrix, material source matrix, fill-cut ratio matrix, fill matrix, and cut matrix based on the partition matrix.

[0096] In this embodiment, based on the partition matrix established in step S201, a transport distance matrix (L) with dimension m×m, a material source matrix classified by soil properties, a fill-cut ratio matrix, a fill matrix of partitioned allocation according to soil properties with dimension m×1, and a cut matrix (N) are established respectively.

[0097] Specifically, elements To allocate partitions (Sub-item) ) to allocation zone (Sub-item) The earthwork transportation distance is [not specified]. The material source matrix is ​​classified according to the soil properties into the material source matrix P for the roadbed area, the material source matrix Q for the surface area, the material source matrix R for the work area, and the material source matrix S for the reconstruction and expansion project area (all m×m dimensions); for example, the elements are from the allocation zone. (Sub-item) ) to allocation zone (Sub-item) The earthwork volume of the roadbed area.

[0098] The square matrix N is an m×1 dimension vector. To allocate partitions (Sub-item) Excavation volume (natural volume); Fill matrix It is an m×1 dimensional vector. To allocate partitions (Sub-item) The filling requirements (compacted volume) of ).

[0099] In this embodiment, based on the partition matrix in step S21, and considering the different soil properties and cut-fill ratios within the engineering site, the following matrices are established: fill matrix, cut-fill ratio matrix, and material source matrix for the roadbed area, surface area, working area, and reconstruction / expansion engineering area.

[0100] Roadway / channel area: Fill matrix (F), fill-cut ratio coefficient matrix (F) ), Material source matrix (P)

[0101] Soil surface area: Fill matrix (D), fill-cut ratio coefficient matrix ( ), Material source matrix (Q)

[0102] Work area: Fill matrix (G), Fill-cut ratio coefficient matrix (G) ), Source Matrix (R)

[0103] Reconstruction and Expansion Project Area: Fill Matrix (K), Fill-Cut Ratio Coefficient Matrix ( ), material source matrix (S).

[0104] S23: Establish a constraint matrix based on allocation requirements; establish a priority matrix based on allocation priority principles.

[0105] In this embodiment, the elements of the constraint matrix are 0 or 1, indicating whether soil transportation is permitted or prohibited; that is, 1 indicates that soil transportation to the allocation zone is permitted, and 0 indicates that soil transportation to the allocation zone is not permitted. Priority Matrix The matrix elements are 0.5 or 1, indicating allocation priority, where 0.5 represents higher allocation priority and 1 represents lower allocation priority. Allocation priority principles include: prioritizing allocation within the same allocation zone and prioritizing the use of excavated material for backfilling trench areas; in the priority matrix... In the middle, allocation within the same zone is... =0.5; when allocating resources across zones, then =1. A special rule is that excavated material from the site is prioritized for backfilling roadbeds; if... Excavation for the site, For backfilling the roadbed, then =0.5.

[0106] S24: Constrain the row sum of the material source matrix by the excavation matrix; constrain the column sum of the material source matrix by the filling matrix and the fill-excavation ratio coefficient.

[0107] In this embodiment, the material source matrices P, Q, R, and S are horizontally spliced ​​together. The rows of the spliced ​​material source matrices are constrained according to the excavation matrix, so that the sum of each row of the material source matrix is ​​less than or equal to the excavation volume of the partition represented by the current row.

[0108] In this embodiment, the row constraint of the material source matrix is ​​the upper limit constraint of excavation supply, and the inequality constrained by the excavation volume is:

[0109] For each sub-item From sub-items The total volume of earthwork transported out is less than or equal to the volume of earthwork excavated.

[0110] In this embodiment, the material source matrix columns corresponding to different soil properties are constrained according to the fill matrix and the fill-cut ratio coefficient matrix, so that the sum of each column of the material source matrix for different soil properties is equal to the fill volume of the corresponding soil material required for the partition represented by the current column.

[0111] Specifically, the equation constrained by the fill volume is:

[0112] The material source matrix is ​​the fill demand equation, i.e., the material transported to the sub-items. After compaction, the earthwork in the roadbed area just met the filling requirements.

[0113] S25: Solve for the optimal initial allocation scheme by minimizing the objective function to obtain the initial earthwork allocation scheme for each allocation zone of the airport to be built.

[0114] Minimize objective function for:

[0115] in, and To adjust the partition identifier; This is the transport distance matrix, referring to the distance from the allocation zone. To allocate partitions Earthwork transportation distance; This is the constraint matrix; This is the priority matrix.

[0116] This application, through the minimum weighted comprehensive transportation volume, can be applied in practice using an objective function. Using the linear constraints from step S24 as input, the optimal material allocation matrix P, Q, R, S is obtained by solving the problem using the Python SciPy library or the commercial solver CPLEX.

[0117] Furthermore, when adding new allocation partitions, only the matrix dimension needs to be expanded, without reconstructing the model; that is, the value of m can be automatically adjusted as needed.

[0118] S3: Visualize the initial earthwork allocation plan based on different allocation zones.

[0119] In this embodiment, visualization refers to converting the allocation plan into spatial graphics based on a GIS (Geographic Information System) platform.

[0120] Specifically, based on the allocation plan and different fill compaction degrees, each earthwork area is divided on the Geographic Information System (GIS) base map using a grid as the unit, and different patterns and colors are used to distinguish different fill and cut types. One-way arrows are used to display the direction, transport distance, and volume of earthwork allocation for each allocation zone. When a specific allocation zone is clicked, the system will display the currently completed fill and cut volumes, as well as the remaining uncompleted volumes for that zone.

[0121] Furthermore, the zone boundaries and earthwork volume data are overlaid onto the airport GIS base map. The rendering rule is to use red grids for cut areas and green grids for fill areas to distinguish between cut and fill types. When displaying the flow direction, arrows are used to indicate the direction from the cut zone to the fill zone, and the thickness of the arrows is positively correlated with the volume of earthwork transported (e.g., 1 mm width for every 1,000 m³). When labeling, the transport distance (km) and volume (m³) can also be displayed next to the arrows.

[0122] S4: During construction, real-time construction monitoring data of each allocation zone is obtained, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan.

[0123] In this embodiment, the real-time construction monitoring data is the elevation change data collected by IoT sensors, which is then calculated and converted into the daily completion amount.

[0124] Specifically, excavation volume monitoring uses daily elevation data transmitted by the excavator's GNSS sensors to calculate changes in excavation volume. For example, if the elevation drops by 0.5m × an area of ​​1000m², the calculated excavation volume is 500m³. Fill volume monitoring uses the compaction roller's vibration sensors to detect the number of compaction passes, combined with the elevation rise, to calculate the effective fill volume, deducting for compaction settlement.

[0125] In this embodiment, step S4 includes:

[0126] S41: During construction, elevation data is transmitted daily through sensors on excavators and compactors, and the daily excavation and filling volumes are calculated based on the elevation data.

[0127] In this embodiment, the calculation formula is as follows: Daily excavation volume = (Average elevation of the previous day - Average elevation of the current day) × Zone area, where the zone area is ㎡. Daily filling volume = [(Average elevation of the previous day - Average elevation of the current day) - Compaction settlement coefficient] × Zone area. The compaction settlement coefficient is 0.15 for clay and 0.08 for sand.

[0128] S42: Update the remaining work volume based on the daily completed excavation and filling volumes.

[0129] S43: In the intelligent earthwork allocation model, calculations are performed based on the remaining engineering quantities to obtain the latest earthwork allocation plan after updating the engineering quantities.

[0130] Specifically, the remaining work volume is the total excavation volume minus the completed excavation volume, which is calculated and summed based on the number of construction days and the actual excavation volume completed each day.

[0131] S44: Obtain the updated data of the earthwork allocation plan before and after the update, and visualize the updated content based on the updated data and the partition identifier of each allocation partition.

[0132] In this embodiment, if the progress of a certain allocation zone is delayed (e.g., P2 completion rate <80%), other zones are prohibited from transporting soil to it in the restriction matrix H to avoid resource congestion. The updated data content of the soil allocation plan before and after the update is visualized to help staff quickly understand the updated allocation zones and specific update content.

[0133] Specifically, repeat steps S41 and S44 until the earthwork construction is completed.

[0134] In one embodiment, a method for intelligent allocation of resources for large-scale earthwork projects at airports further includes:

[0135] S401: During construction, real-time monitoring data on compaction degree, elevation change, and haul distance of each allocation zone are acquired, and an actual construction feedback model is generated.

[0136] In this embodiment, the traditional method uses a fixed cut-fill ratio and haul distance, which cannot adapt to fluctuations in soil compaction and changes in haul distance caused by temporary traffic control during construction, resulting in large deviations between model predictions and actual conditions. Furthermore, it is difficult for humans to quickly identify changes in critical paths, such as changes in the source of fill material in the roadbed area, which can easily lead to construction delays. Therefore, it is necessary to track and calculate the construction situation in real time to improve the anomaly response speed of the intelligent allocation scheme and adapt to complex construction environments.

[0137] Specifically, step S401 includes:

[0138] S4011: Based on compaction monitoring data, calculate the real-time fill-cut ratio correction coefficient using the compaction-compression ratio curve calibrated in the laboratory.

[0139] In this embodiment, the compaction monitoring data is the number of compaction passes and frequency data collected by the vibration sensor of the roller compactor, which is converted into compaction density values ​​in g / cm³ through a calibration curve. The compaction density value is obtained by interpolating the vibration frequency through the calibration curve. The elevation change data is the daily variation value of the regional surface elevation transmitted back by a GNSS positioning device (such as Trimble R12). The transport distance dynamic data is the real-time path distance calculated based on the GPS trajectory of the transport vehicle.

[0140] For example, a triaxial vibration sensor (PCB 356A32) is installed on the roller in zone P1, with a sampling frequency of 100Hz, to transmit vibration data in real time. Compaction-compression ratio curves are pre-generated using laboratory data, such as 15Hz corresponding to 90%, 25Hz to 95%, and 35Hz to 98%. The real-time compaction degree is calculated, such as 28Hz corresponding to 96%.

[0141] Real-time cut-fill ratio correction factor ,in, To design the compaction degree, such as 95%; This refers to the real-time compaction degree, such as 96%.

[0142] S4012: Calculate the dynamic adjustment value of the actual transport distance between sections based on elevation change data.

[0143] In this embodiment, the actual dynamic adjustment value of the transport distance refers to the deviation (unit: km) between the length of the transport path between sections and the original design value caused by changes in the construction terrain (such as surface uplift in the fill area and subsidence during excavation in the cut area) or temporary traffic control. The actual dynamic adjustment value of the transport distance is the difference between the straight-line distance between the centroids initially calculated by GIS and the path length after dynamic adjustment.

[0144] S4013: Based on dynamic haul distance data, generate an actual construction feedback model that includes a cut-fill ratio correction coefficient and a haul distance adjustment value.

[0145] In this embodiment, the dynamic haulage distance data refers to the data showing changes in haulage distances within the allocation zones. The actual construction feedback model integrates a dynamic linear programming model of the real-time cut-fill ratio coefficient and haulage distance to predict the current optimal allocation scheme. For example, if temporary traffic control measures cause the actual haulage distance between allocation zones P1 and P3 to increase to 1.5 km, the dynamic haulage distance adjustment will be 0 if there is no change.

[0146] S402: Compare the initial allocation plan with the prediction results of the actual construction feedback model, and trigger the model correction command.

[0147] Specifically, step S402 includes:

[0148] S4021: Extract the key parameters of the initial allocation plan. The key parameters include the objective function value, the amount of soil transported in each zone, and the transportation cost.

[0149] Specifically, the objective function value refers to the initial optimal solution value of the intelligent earthwork allocation model, and the earthwork volume transported by each zone is the planned earthwork allocation volume between zones, in m³. The transportation cost is the weighted cost per unit earthwork volume × transport distance, in yuan / m³·km.

[0150] S4022: Extract the prediction parameters of the actual construction feedback model. The prediction parameters include the actual amount of soil transported, real-time transportation costs, and remaining work volume.

[0151] Specifically, the actual completed soil transport volume refers to the real-time soil transport volume (unit: m³) obtained through GNSS trajectory inversion. The actual completed soil transport volume = GNSS trajectory length of the transport vehicle × on-board soil density, calibrated by a weight sensor; the real-time transportation cost is a dynamic cost calculated based on the actual path length.

[0152] S4023: Calculate the deviation rate of key parameters. If the deviation rate of any key parameter exceeds the preset threshold, trigger the model correction command.

[0153] In this embodiment, the deviation rate of the key parameter is the absolute value of (key parameter value - predicted parameter value) / key parameter value. The preset threshold is taken as an engineering experience value, such as 10%. The trigger condition for the distance adjustment value is that it exceeds 10% of the original planned path length.

[0154] S403: Update the constraints or objective function of the initial allocation model according to the model correction command, and generate a dynamic optimization allocation scheme.

[0155] In this embodiment, if the fill-cut ratio correction coefficient triggers a correction command, the fill-cut ratio matrix in the initial allocation model is adjusted. If the transport distance adjustment value triggers a correction command, the transport distance matrix in the initial allocation model is updated. If the transport cost deviation rate is too high, a schedule constraint or a resource balance objective function is added.

[0156] Specifically, an excessively high transportation cost deviation rate is defined as the actual transportation cost exceeding the originally designed transportation cost by 10%. The resource balance objective function is to add a resource fluctuation penalty term to the original transportation cost objective function.

[0157] ,in To balance the weights, the default value is 0.1, and the configurable range is 0-0.5; These are the elements of the distance matrix; For material source matrix elements; These are the initial material source matrix elements; Basic transportation costs; This is a penalty for resource fluctuations.

[0158] S404: Compare the differences between the initial allocation plan and the dynamically optimized allocation plan, and provide visual early warnings based on zoning identifiers and changes in soil transport routes.

[0159] In this embodiment, the differences refer to the quantitative differences between the initial plan and the dynamically optimized plan in terms of earthmoving routes, volumes, and costs. Detection elements include route additions or cancellations, earthmoving volume changes exceeding 10%, and cost fluctuations exceeding 10%.

[0160] Specifically, the visual early warning system uses dynamic graphic symbols to mark differences on a GIS map and pushes them to the construction terminal in conjunction with a hierarchical alarm mechanism.

[0161] For example, when the difference type is a decrease in traffic volume > 10%, the graphic symbol is a thick red arrow + a ↓ percentage label; the dynamic effect is a flashing arrow. When the difference type is an increase in traffic volume > 10%, the graphic symbol is a thick blue arrow + an ↑ percentage label; the dynamic effect is a continuously highlighted arrow. When the difference type is adding a path, the graphic symbol is a green dashed arrow; the dynamic effect is a progressive drawing from the source to the target. When the difference type is canceling a path, the graphic symbol is a gray cross covering the original arrow.

[0162] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0163] In one embodiment, an intelligent allocation system for large-scale earthwork projects at airports is provided, which corresponds to an intelligent allocation method for large-scale earthwork projects at airports as described in the above embodiment.

[0164] An intelligent dispatching system for large-scale earthwork projects at airports includes a data acquisition and preprocessing module, a model building and scheme generation module, a scheme visualization module, and a dynamic update module. Detailed descriptions of each functional module are as follows:

[0165] The data acquisition and preprocessing module is used to collect earthwork engineering data of the airport to be built and preprocess it to obtain a standardized engineering dataset.

[0166] The model building and scheme generation module is used to build an intelligent earthwork allocation model based on linear programming. In the intelligent earthwork allocation model, based on standardized engineering datasets, preset allocation constraints and allocation priorities, the initial earthwork allocation schemes for each allocation zone of the airport to be built are generated.

[0167] The scheme visualization module is used to visualize the initial earthwork allocation scheme based on different allocation zones;

[0168] The dynamic update module is used to acquire real-time construction monitoring data of each allocation zone during construction, dynamically update the initial earthwork allocation plan, and obtain the latest earthwork allocation plan.

[0169] For specific limitations regarding the intelligent allocation system for large-scale earthwork engineering at airports, please refer to the limitations of the intelligent allocation method for large-scale earthwork engineering at airports mentioned above, which will not be repeated here. Each module in the aforementioned intelligent allocation system for large-scale earthwork engineering at airports can be implemented entirely or partially through software, hardware, or a combination thereof. Each module can be embedded in or independent of the processor in a computer device in hardware form, or it can be stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0170] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores standardized engineering datasets and earthwork allocation schemes, etc. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an intelligent allocation method for large-scale earthwork engineering at an airport.

[0171] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0172] S1: Collect earthwork data for the airport to be built and preprocess it to obtain a standardized engineering dataset;

[0173] S2: Construct an intelligent earthwork allocation model based on linear programming; In the intelligent earthwork allocation model, based on standardized engineering datasets, preset allocation constraints and allocation priorities, generate initial earthwork allocation schemes for each allocation zone of the airport to be built.

[0174] S3: Visualize the initial earthwork allocation plan based on different allocation zones;

[0175] S4: During construction, real-time construction monitoring data of each allocation zone is obtained, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan.

[0176] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0177] S1: Collect earthwork data for the airport to be built and preprocess it to obtain a standardized engineering dataset;

[0178] S2: Construct an intelligent earthwork allocation model based on linear programming; In the intelligent earthwork allocation model, based on standardized engineering datasets, preset allocation constraints and allocation priorities, generate initial earthwork allocation schemes for each allocation zone of the airport to be built.

[0179] S3: Visualize the initial earthwork allocation plan based on different allocation zones;

[0180] S4: During construction, real-time construction monitoring data of each allocation zone is obtained, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan.

[0181] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0182] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0183] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for intelligent allocation of resources for large-scale earthwork projects at airports, characterized in that, include: Collect and preprocess earthwork data for the airport to be built to obtain a standardized engineering dataset; Construct an intelligent earthwork allocation model based on linear programming; In the intelligent earthwork allocation model, based on the standardized engineering dataset, preset allocation constraints and allocation priorities, an initial earthwork allocation plan is generated for each allocation zone of the airport to be built. The initial earthwork allocation plan is visualized based on different allocation zones; During construction, real-time construction monitoring data of each allocation zone is acquired, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan. The construction of an intelligent earthwork allocation model based on linear programming; in the intelligent earthwork allocation model, based on the standardized engineering dataset, preset allocation constraints, and allocation priorities, an initial earthwork allocation scheme corresponding to each allocation zone of the airport to be built is generated, specifically including: Based on the soil properties and filling requirements, the allocation zones are subdivided into several sub-items, and a zone matrix with dimension m×m is established, where m = number of allocation zones × number of sub-items in each allocation zone + 1; Based on the partition matrix, construct the transport distance matrix, material source matrix, fill-cut ratio matrix, fill matrix, and cut matrix; Establish a constraint matrix based on the obtained allocation requirement information; establish a priority matrix based on the allocation priority. The sum of rows in the material source matrix is ​​constrained by the excavation matrix; the sum of columns in the material source matrix is ​​constrained by the filling matrix and the fill-excavation ratio coefficient. The optimal initial allocation scheme is solved by minimizing the objective function, thereby obtaining the initial earthwork allocation scheme for each allocation zone of the airport to be built. The material source matrix includes the material source matrix P for the roadbed area, the material source matrix Q for the soil surface area, the material source matrix R for the working area, and the material source matrix S for the reconstruction and expansion project area; the cut-fill ratio matrix includes the cut-fill ratio matrix for the roadbed area. The cut-fill ratio matrix θ of the soil surface area, the cut-fill ratio matrix σ of the working area, and the cut-fill ratio matrix ω of the reconstruction and expansion project area; The minimization objective function f is: Where f is the transportation cost; i and j are the allocation zone identifiers; L ij Here, H represents the transport distance matrix, indicating the earthwork transport distance from allocation zone i to allocation zone j. ij H′ is the constraint matrix; ij This is the priority matrix; During the construction process, real-time construction monitoring data of each allocation zone is acquired, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan, specifically including: During construction, elevation data is transmitted daily through sensors on excavators and compactors, and the daily excavation and filling volumes are calculated based on this elevation data. The remaining work volume is updated based on the daily completed excavation and filling volumes. In the intelligent earthwork allocation model, calculations are performed based on the remaining work volume to obtain the latest earthwork allocation plan after updating the work volume. Obtain the updated data of the earthwork allocation plan before and after the update, and visualize the updated content based on the updated data and the partition identifiers of each allocation zone.

2. The intelligent allocation method for large-scale earthwork engineering at airports according to claim 1, characterized in that, The process of collecting and preprocessing earthwork data for the proposed airport to obtain a standardized engineering dataset includes: Based on the actual construction area and engineering requirements of the airport to be built, the airport to be built is divided into multiple allocation zones; Obtain relevant engineering data on earthwork allocation through engineering construction drawings, including excavation and filling volume, soil properties, cut-fill ratio coefficient, and earthwork transportation distance; Based on the construction data of the airport to be built, relevant information on project implementation is obtained, including construction plan and schedule, construction method, and land acquisition status. Acquire on-site measurement data, and perform data correction and preprocessing on the earthwork allocation-related engineering data; The pre-processed earthwork allocation-related engineering data and the engineering implementation-related information are classified and integrated according to allocation zones and soil properties to obtain a standardized engineering dataset.

3. The intelligent allocation method for large-scale earthwork engineering at airports according to claim 1, characterized in that, The aforementioned sub-items include site excavation, special excavation, trench backfilling, and surface backfilling; the methods also include: The allocation zones are established based on the different soil properties and cut-fill ratios within the engineering site, creating fill matrices, cut-fill ratio matrices, and material source matrices for the roadbed zone, surface zone, working zone, and reconstruction / expansion project zone: Roadway / channel area: Roadway / channel fill matrix F, Roadway / channel fill-cut ratio matrix Material source matrix P in the channel area Soil surface area: Soil surface area fill matrix D, soil surface area fill-cut ratio matrix θ, soil surface area material source matrix Q Working area: Working area fill matrix G, working area fill-cut ratio matrix σ, working area material source matrix R Reconstruction and expansion project area: Fill matrix K, fill-excavation ratio matrix ω, material source matrix S of the reconstruction and expansion project area; The allocation requirements information includes: Based on the obtained information on fill material requirements and soil properties for each allocation zone, soil transportation to the corresponding allocation zone whose soil properties do not meet the fill material requirements is restricted. Obtain the shortage and surplus status of each allocation zone, restrict the outward transport of soil from allocation zones in the shortage status, and restrict the transport of soil into allocation zones in the surplus status. The constraint matrix is ​​filled with 1s and 0s, where 1 indicates that soil transportation to the allocation zone is allowed, and 0 indicates that soil transportation to the allocation zone is not allowed.

4. The intelligent allocation method for large-scale earthwork engineering at airports according to claim 3, characterized in that, The allocation priority is set based on the allocation priority principle, which includes: prioritizing allocation within the same allocation zone and prioritizing the use of excavated material for backfilling roadbed areas. The priority matrix is ​​filled with 0.5 and 1, where 0.5 represents a higher allocation priority and 1 represents a lower allocation priority; the constraint of the material source matrix row sum through the excavation matrix; and the constraint of the material source matrix column sum through the filling matrix and the fill-excavation ratio coefficient, including: The material source matrices P, Q, R, and S are horizontally spliced ​​together. The rows of the spliced ​​material source matrix are constrained according to the excavation matrix so that the sum of each row of the material source matrix is ​​less than or equal to the excavation volume of the partition represented by the current row. Constrain the material source matrix columns corresponding to different soil properties based on the fill matrix and fill-cut ratio matrix, so that the sum of each column of the material source matrix for different soil properties is equal to the fill volume of the corresponding soil material required for the partition represented by the current column.

5. An intelligent dispatching system for large-scale earthwork projects at airports, characterized in that, The system includes: The data acquisition and preprocessing module is used to collect earthwork engineering data of the airport to be built and preprocess it to obtain a standardized engineering dataset. The model building and scheme generation module is used to build an intelligent earthwork allocation model based on linear programming. In the intelligent earthwork allocation model, based on the standardized engineering dataset, preset allocation constraints and allocation priorities, an initial earthwork allocation scheme corresponding to each allocation zone of the airport to be built is generated. The scheme visualization module is used to visualize the initial earthwork allocation scheme based on different allocation zones; The dynamic update module is used to acquire real-time construction monitoring data of each allocation zone during the construction process, and to dynamically update the initial earthwork allocation plan to obtain the latest earthwork allocation plan. The construction of an intelligent earthwork allocation model based on linear programming; in the intelligent earthwork allocation model, based on the standardized engineering dataset, preset allocation constraints, and allocation priorities, an initial earthwork allocation scheme corresponding to each allocation zone of the airport to be built is generated, specifically including: Based on the soil properties and filling requirements, the allocation zones are subdivided into several sub-items, and a zone matrix with dimension m×m is established, where m = number of allocation zones × number of sub-items in each allocation zone + 1; Based on the partition matrix, construct the transport distance matrix, material source matrix, fill-cut ratio matrix, fill matrix, and cut matrix; Establish a constraint matrix based on the obtained allocation requirement information; establish a priority matrix based on the allocation priority. The sum of rows in the material source matrix is ​​constrained by the excavation matrix; the sum of columns in the material source matrix is ​​constrained by the filling matrix and the fill-excavation ratio coefficient. The optimal initial allocation scheme is solved by minimizing the objective function, thereby obtaining the initial earthwork allocation scheme for each allocation zone of the airport to be built. The material source matrix includes the material source matrix P for the roadbed area, the material source matrix Q for the soil surface area, the material source matrix R for the working area, and the material source matrix S for the reconstruction and expansion project area; the cut-fill ratio matrix includes the cut-fill ratio matrix φ for the roadbed area, the cut-fill ratio matrix θ for the soil surface area, the cut-fill ratio matrix σ for the working area, and the cut-fill ratio matrix ω for the reconstruction and expansion project area; The minimization objective function f is: Where f is the transportation cost; i and j are the allocation zone identifiers; L ij Here, H represents the transport distance matrix, indicating the earthwork transport distance from allocation zone i to allocation zone j. ij H′ is the constraint matrix; ij This is the priority matrix; During the construction process, real-time construction monitoring data of each allocation zone is acquired, and the initial earthwork allocation plan is dynamically updated to obtain the latest earthwork allocation plan, specifically including: During construction, elevation data is transmitted daily through sensors on excavators and compactors, and the daily excavation and filling volumes are calculated based on this elevation data. The remaining work volume is updated based on the daily completed excavation and filling volumes. In the intelligent earthwork allocation model, calculations are performed based on the remaining work volume to obtain the latest earthwork allocation plan after updating the work volume. Obtain the updated data of the earthwork allocation plan before and after the update, and visualize the updated content based on the updated data and the partition identifiers of each allocation zone.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent allocation method for large-scale earthwork engineering at airports as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent allocation method for large-scale earthwork engineering at airports as described in any one of claims 1 to 4.

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