Canal project line selection scheme recommendation method and device and electronic equipment

Abstract

The invention discloses a method and device for recommending a canal project line selection scheme and electronic equipment, and relates to the field of canal project data processing.The method comprises the steps that multi-source geographic information of a target area to be subjected to canal project site selection is fused, and a basic geographic information framework is constructed based on the multi-source fusion information; performing geological stability assessment on different to-be-assessed sub-regions by using a fuzzy logic rule, marking unfavorable geological sections based on geological stability assessment results, preliminarily drawing up N canal route schemes, identifying a matching relationship between each preliminarily drawn-up canal route scheme and a natural resource constraint condition set, and determining the matching relationship between each preliminarily drawn-up canal route scheme and the natural resource constraint condition set; adjusting constraint conditions in the canal line; and comparing and selecting the multiple adjusted canal route schemes by adopting a multi-objective optimization model, and determining a recommended canal route scheme. The technical problems that in the prior art, in the long-distance canal engineering planning line selection process, influences of topography and geology exist, the workload is large, and the cost is high are solved.

Description

Technical Field

[0001] This invention relates to the field of canal engineering data processing technology or other related fields. Specifically, it relates to a method, apparatus, and electronic equipment for recommending route selection schemes for canal engineering projects. Background Technology

[0002] Route selection is the primary step in canal construction, and its rationality directly affects construction costs, construction difficulty, navigation capacity, water resource utilization efficiency, ecological and environmental impact, and regional economic development potential. Traditional canal route selection often relies on detailed topographic surveys, geological investigations, and environmental assessments, which are time-consuming and costly, especially for long-distance, large-scale projects.

[0003] Canal projects typically span hundreds of kilometers, with complex terrain, diverse geological conditions, and involve various ecological environments and sensitive areas along the route. In the early stages of the project, the reserve of basic data is insufficient, the coverage and accuracy of topographic surveys are inadequate, and the distribution of geological survey points is sparse, failing to fully reflect the geological conditions along the route. As a result, it is difficult to obtain sufficient information for scientific and reasonable canal route selection during the project planning stage.

[0004] Currently, relevant engineering design standards such as the "Design Code for Waterway Engineering" (JTS181-2016) provide basic principles for waterway engineering route selection. These principles include consideration of factors such as overall planning, natural conditions, ship traffic density, environmental protection requirements, engineering volume, maintenance costs, and ship navigation safety. They also address requirements related to waterway siltation, strong winds and waves, the angle between the main current direction and the waterway axis, waterway axis smoothness, and the layout of the waterway axis in shallow sections. However, these standards have limitations in application under long-distance, information-scarce conditions, relying primarily on existing data and experience, making it difficult to cope with complex and ever-changing natural and social environments.

[0005] Furthermore, traditional methods for geological stability assessment require detailed geological data, including extensive borehole data and geological profile analysis. However, accurately assessing geological stability in situations of data scarcity poses a significant challenge for long-distance canal route selection. Existing technologies for geological stability assessment are relatively simplistic and lack effective handling of uncertainties and ambiguities, thus limiting the accuracy and reliability of the assessment results.

[0006] For long-distance, large-scale canal projects, the topographic surveying area is extensive, and the geological exploration workload is enormous. The costs of preliminary surveying and exploration are prohibitive, and the construction period is unacceptable. Conducting topographic surveying and exploration work later, which is not considered a recommended route, would be a waste of resources.

[0007] There is currently no effective solution to the above problems. Summary of the Invention

[0008] This invention provides a method, apparatus, and electronic device for recommending route selection schemes for canal projects, in order to at least solve the technical problems of high workload and high cost caused by topographic and geological influences in the planning and route selection of long-distance canal projects in related technologies.

[0009] According to one aspect of the present invention, a method for recommending canal engineering route selection schemes is provided, comprising: fusing multi-source geographic information of a target area for which a canal engineering site selection is to be carried out; constructing a basic geographic information framework based on the multi-source fused information, wherein the target area is divided into multiple sub-areas to be evaluated; performing geological stability assessments on different sub-areas to be evaluated using fuzzy logic rules, and marking unfavorable geological sections based on the geological stability assessment results; initially proposing N canal route schemes based on a pre-planned set of canal route selection rules, a historical case knowledge base, the basic geographic information framework, the river system transportation demand in the target area, and the geological stability assessment results, wherein N is a positive integer greater than 1; identifying the matching relationship between each initially proposed canal route scheme and a set of natural resource constraints, and adjusting the constraints in the canal route; and comparing the adjusted multiple canal route schemes using a multi-objective optimization model to determine a recommended canal route scheme.

[0010] Optionally, the step of fusing multi-source geographic information of the target area for the proposed canal project site selection and constructing a basic geographic information framework based on the multi-source fused information includes: preprocessing the multi-source geographic information of the target area for the proposed canal project site selection, wherein the preprocessing strategy includes at least one of the following: coordinate system unification, projection method unification, data format standardization, and data cleaning, wherein the data cleaning includes: removing redundant nodes in topographic maps, removing cloud mask areas in remote sensing images, and correcting coordinate anomalies in survey data; and obtaining the target area from multiple angles using optical stereo photogrammetry and radar interferometry strategies. The system utilizes remote sensing imagery and topographic mapping of the target area. A three-dimensional topographic model is constructed based on the remote sensing imagery of the target area. Transformation parameters are calculated using the least squares method. Based on pre-selected ground feature points, the remote sensing imagery and topographic mapping are registered using the transformation parameters. Geospatial analysis tools are used to identify the correlation between the registered remote sensing imagery and survey data. Based on the correlation, a geospatial database model is constructed. This model integrates the topographic features, remote sensing imagery interpretation results, and survey data of the target area to obtain a multi-dimensional dataset. The basic geographic information framework is then constructed based on this multi-dimensional dataset.

[0011] Optionally, the step of constructing the basic geographic information framework based on the multi-dimensional dataset includes: extracting geological boundaries from the remote sensing image interpretation results, geological exploration points from the exploration data, and profile lines from the topographic features; generating stratigraphic interfaces based on the profile lines and borehole data to construct a topographic surface model, and correcting the interface morphology of the topographic surface model by combining stratigraphic tonal differences in the remote sensing image; constructing a geological body model based on the geological boundaries and the geological exploration points; and constructing the basic geographic information framework including topographic relief and underground structure based on the topographic surface model and the geological body model.

[0012] Optionally, the construction of the historical case knowledge base includes: obtaining a set of completed historical canal engineering cases; extracting key information from the case documents and remote sensing images of each historical canal engineering case using text mining and image recognition strategies to obtain a set of key information, wherein the key information includes at least one of the following: terrain features, geological conditions, route selection scheme, engineering volume, construction difficulties, and environmental factors; and integrating the extracted set of key information into the knowledge base using a case reasoning framework to obtain the historical case knowledge base.

[0013] Optionally, the step of using fuzzy logic rules to assess the geological stability of different sub-regions to be evaluated includes: for each sub-region to be evaluated, determining a set of input variables related to geological stability, wherein the input variables include at least one of the following: rock type, seismic wave velocity, groundwater level, and soil moisture content; using membership functions to map the values ​​of the input variables to their respective fuzzy sets; based on a pre-defined fuzzy rule base and combined with the fuzzy sets of the input variables, calculating the fuzzy output of the geological stability of each sub-region to be evaluated; and using a defuzzification strategy to convert the fuzzy output into a geological stability level.

[0014] Optionally, the step of initially formulating N canal route schemes based on a pre-defined set of canal route selection rules, a historical case knowledge base, the basic geographic information framework, the river system transportation demand in the target area, and the geological stability assessment results includes: generating preliminary route selection guidelines based on the set of canal route selection rules, combined with the geographical conditions and environmental protection requirements of the target area; using the historical case knowledge base, identifying successful route selection patterns of historical canal projects under similar conditions to the target area through case reasoning; conducting multi-source data analysis based on the basic geographic information framework and the geological stability assessment results to identify potential risk points and adjustment space of the canal routes; extracting historical freight volume data, shipping demand, water resource allocation targets, and existing transportation network correlation information from the river system transportation demand to determine the transportation demand priority of the canal routes; and using a heuristic search algorithm to initially formulate N canal route schemes based on the route selection guidelines, the successful route selection patterns of historical canal projects, the potential risk points, adjustment space, and transportation demand priority of the canal routes.

[0015] Optionally, the step of identifying the matching relationship between each initially proposed canal route and the set of natural resource constraints, and adjusting the canal route, includes: digitizing each initially proposed canal route and storing it in a geographic information system (GIS) format; using the spatial analysis function of the GIS to identify conflict points between the canal route and the set of natural resource constraints; analyzing the identified conflict points, evaluating the impact of the conflict points on the canal engineering corresponding to the canal route, and obtaining an evaluation result; and adjusting the canal route based on the evaluation result.

[0016] Optionally, the step of comparing and selecting multiple adjusted canal route schemes using a multi-objective optimization model to determine the recommended canal route scheme includes: obtaining the objective index function of the multi-objective optimization model and defining the constraints in the multi-objective optimization model; inputting the parameters of each canal route scheme into the multi-objective optimization model, running a multi-objective optimization algorithm by the multi-objective optimization model to iteratively optimize the different canal route schemes, and selecting the canal route scheme with the highest comprehensive evaluation score as the recommended canal route scheme.

[0017] According to another aspect of the present invention, a device for recommending canal engineering route selection schemes is also provided, comprising: an information fusion unit, used to fuse multi-source geographic information of a target area for which a canal engineering site selection is to be carried out, and construct a basic geographic information framework based on the multi-source fused information, wherein the target area is divided into multiple sub-areas to be evaluated; a geological stability assessment unit, used to perform geological stability assessments on different sub-areas to be evaluated using fuzzy logic rules, and mark unfavorable geological sections based on the geological stability assessment results; a route formulation unit, used to initially formulate N canal route schemes based on a pre-formulated set of canal route selection rules, a historical case knowledge base, the basic geographic information framework, the river system transportation demand in the target area, and the geological stability assessment results, wherein N is a positive integer greater than 1; a constraint adjustment unit, used to identify the matching relationship between each initially formulated canal route scheme and a set of natural resource constraints, and adjust the constraints in the canal route; and a recommended route determination unit, used to compare the adjusted multiple canal route schemes using a multi-objective optimization model to determine a recommended canal route scheme.

[0018] Optionally, the information fusion unit includes: an information preprocessing module, used to preprocess the multi-source geographic information of the target area for the proposed canal project site selection, wherein the preprocessing strategy includes at least one of the following: coordinate system unification, projection method unification, data format standardization, and data cleaning, wherein the data cleaning includes: removing redundant nodes in the topographic map, removing cloud mask areas in the remote sensing image, and correcting coordinate anomalies in the survey data; and a remote sensing image acquisition module, used to obtain remote sensing images and topographic maps of the target area from multiple angles using optical stereo photogrammetry and radar interferometry strategies, based on the remote sensing images of the target area. The system comprises: a 3D terrain model; an image registration module for calculating transformation parameters using the least squares method; registration of the remote sensing image with the topographic map based on pre-selected feature points using the transformation parameters; an image data relationship analysis module for identifying the correlation between the registered remote sensing image and the survey data using geospatial analysis tools; and an information integration module for constructing a geospatial database model based on the correlation, integrating the terrain features, remote sensing image interpretation results, and survey data of the target area using the geospatial database model to obtain a multi-dimensional dataset, and constructing the basic geographic information framework based on the multi-dimensional dataset.

[0019] Optionally, the information integration module includes: a geological information extraction module, used to extract geological boundaries from the remote sensing image interpretation results, geological exploration points from the exploration data, and profile lines from the topographic elements; a topographic surface model construction module, used to generate stratigraphic interfaces based on the profile lines and borehole data to construct a topographic surface model, and to correct the interface morphology of the topographic surface model by combining stratigraphic tonal differences in the remote sensing image; a geological body model construction module, used to construct a geological body model based on the geological boundaries and the geological exploration points; and a basic geographic information framework construction module, used to construct the basic geographic information framework including topographic relief and underground structure based on the topographic surface model and the geological body model.

[0020] Optionally, when constructing the historical case knowledge base, the device for recommending canal engineering route selection schemes includes: a historical canal engineering case set acquisition unit, used to acquire a set of completed historical canal engineering cases; a historical canal engineering case information extraction unit, used to extract key information from the case documents and remote sensing images of each historical canal engineering case through text mining and image recognition strategies to obtain a key information set, wherein the key information includes at least one of the following: terrain features, geological conditions, route selection scheme, engineering volume, construction difficulties, and environmental factors; and a historical case knowledge base determination unit, used to integrate the extracted key information set into the knowledge base using a case reasoning framework to obtain the historical case knowledge base.

[0021] Optionally, the geological stability assessment unit includes: an input variable determination module, used to determine a set of input variables related to geological stability for each of the sub-regions to be assessed, wherein the input variables include at least one of the following: rock type, seismic wave velocity, groundwater level, and soil moisture content; an input variable mapping module, used to map the values ​​of the input variables to their respective fuzzy sets using membership functions; a fuzzy output calculation module, used to calculate the fuzzy output of the geological stability of each sub-region to be assessed based on a pre-set fuzzy rule base and in combination with the fuzzy sets of the input variables; and a geological stability level conversion module, used to convert the fuzzy output into a geological stability level using a defuzzification strategy.

[0022] Optionally, the route planning unit includes: a route selection guidance principle generation module, used to generate preliminary route selection guidance principles based on the canal route selection rule set, combined with the geographical conditions and environmental protection requirements of the target area; a route selection success module identification module, used to utilize the historical case knowledge base to identify historical canal project route selection success patterns under similar conditions to the target area through case reasoning; a multi-source data analysis module, used to combine the basic geographic information framework and the geological stability assessment results to perform multi-source data analysis and identify potential risk points and adjustment space of the canal route; a transportation demand extraction module, used to extract historical freight volume data, shipping demand, water resource allocation targets, and existing transportation network correlation information from the river system transportation demand to determine the transportation demand priority of the canal route; and a canal route planning module, used to preliminarily plan N canal route schemes based on the route selection guidance principles, the historical canal project route selection success patterns, the potential risk points, adjustment space, and transportation demand priority of the canal route using a heuristic search algorithm.

[0023] Optionally, the constraint adjustment unit includes: a route plan storage module, used to digitize each initially proposed canal route plan and store it in a geographic information system (GIS) format; a conflict point identification module, used to use the spatial analysis function of the GIS to identify conflict points between the canal route plan and the set of natural resource constraints; an impact assessment module, used to analyze the identified conflict points, assess the impact of the conflict points on the canal project corresponding to the canal route plan, and obtain an assessment result; and a route adjustment module, used to adjust the canal route plan based on the assessment result.

[0024] Optionally, the recommended route determination unit includes: an index function acquisition module, used to acquire the objective index function of the multi-objective optimization model and define the constraints in the multi-objective optimization model; and a recommended route determination module, used to input the parameters of each canal route scheme into the multi-objective optimization model, and run a multi-objective optimization algorithm to iteratively optimize the different canal route schemes, and select the canal route scheme with the highest comprehensive evaluation score as the recommended canal route scheme.

[0025] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the recommended method of canal engineering route selection scheme of any one of the above-mentioned methods.

[0026] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the recommended method for canal engineering route selection schemes as described above.

[0027] According to another aspect of the present invention, a computer program product is also provided, comprising a computer program that, when executed by a processor, implements the steps of the method for recommending a canal engineering route selection scheme as described in any of the preceding embodiments.

[0028] In this disclosure, multi-source geographic information of the target area for the proposed canal project is fused, and a basic geographic information framework is constructed based on the fused information. The target area is divided into multiple sub-areas to be evaluated. Fuzzy logic rules are used to conduct geological stability assessments on different sub-areas to be evaluated, and unfavorable geological sections are marked based on the geological stability assessment results. According to the pre-planned set of canal route selection rules, historical case knowledge base, basic geographic information framework, river system transportation demand in the target area, and geological stability assessment results, N preliminary canal route schemes are proposed, where N is a positive integer greater than 1. The matching relationship between each preliminary proposed canal route scheme and the set of natural resource constraints is identified, and the constraints in the canal route are adjusted. A multi-objective optimization model is used to compare and select the adjusted multiple canal route schemes to determine the recommended canal route scheme.

[0029] In this disclosure, by integrating multi-source geographic information to construct a basic geographic information framework, the limitations of a single data source can be overcome, providing more comprehensive and accurate topographic and geological information. This reduces the workload and cost of field surveys. In the geological condition assessment stage, a fuzzy inference system is used to handle uncertainties and incomplete information, assessing the geological stability of different regions and shifting the assessment of geological conditions from qualitative to quantitative, thereby reducing the intensity and cost of geological surveys. The canal route utilizes intelligent algorithms to establish a multi-objective optimization model, automatically adjusting the route plan to find the canal path with the best cost-effectiveness ratio. Based on historical data feedback, parameter adjustments and model optimizations are performed to improve accuracy and reliability, reducing errors and costs in planning. This solves the technical problems of high workload and high cost in the planning and route selection of long-distance canal projects due to the influence of topography and geology. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0031] Figure 1 This is a flowchart of a recommended method for an optional canal engineering route selection scheme according to an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of a recommended device for an optional canal engineering route selection scheme according to an embodiment of the present invention;

[0033] Figure 3 This is a hardware structure block diagram of an electronic device (or mobile device) for implementing a recommended method for canal engineering route selection according to an embodiment of the present invention. Detailed Implementation

[0034] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0036] To facilitate understanding of the present invention by those skilled in the art, some terms or nouns involved in the various embodiments of the present invention are explained below:

[0037] Geographic Information System (GIS) is a system used to collect, store, analyze, and display geographic information about the Earth's surface. It can process various forms of geographic data, including maps, aerial photographs, satellite imagery, and topographic data. In the canal engineering route selection of this invention, GIS is used to integrate and analyze multi-source data such as topography, geology, and ecology to achieve visualization and optimization of the route plan.

[0038] A hydrodynamic model is a mathematical model used to simulate the movement and mass transport of water in bodies of water such as rivers, lakes, and oceans. In the canal route selection of this invention, this model is used to predict hydrological changes and assess the impact of canal construction on water flow, water level, and sediment deposition, thereby ensuring the rationality and safety of the waterway design.

[0039] Soil and water conservation models are comprehensive hydrological, water quality, and agricultural models used to predict processes such as soil erosion, nutrient migration, and pesticide flow within watersheds under different land management practices. In the canal project of this invention, the model can be used to assess the impact of civil engineering on the surrounding environment, particularly soil erosion and water pollution.

[0040] Remote sensing technology uses sensors to collect and analyze electromagnetic wave information reflected or emitted from the Earth's surface, acquiring information about the characteristics and state of ground objects in a non-contact manner. In the canal engineering route selection of this invention, remote sensing technology is used to obtain large-scale information on topography, vegetation cover, and water distribution, providing basic data for GIS analysis and route planning.

[0041] Three-dimensional geological modeling is a technique for constructing three-dimensional models of underground structures based on geological data. It can reveal complex geological structures and stratigraphic distributions, which is of great significance for engineering site selection, design, and construction. In the canal route selection of this invention, three-dimensional geological modeling is used to predict geological conditions and potential risks, helping engineers make more informed decisions.

[0042] Multi-objective optimization methods seek the optimal solution among multiple conflicting objective functions. They can simultaneously consider objectives such as cost, efficiency, and environmental impact in canal engineering, using intelligent algorithms to find the solution that best satisfies various constraints. In this invention, the multi-objective optimization method is used to select the best recommended solution from numerous route options.

[0043] Fuzzy inference systems are reasoning methods based on fuzzy logic theory, allowing logical reasoning even with incomplete or uncertain data. In this invention, a fuzzy inference system is used to assess geological stability, enabling fuzzy evaluation even with scarce borehole data, and helping to identify unfavorable geological sections.

[0044] A case-based reasoning knowledge base is a method of learning and reasoning from past experience cases. It stores data and solutions from similar historical projects, providing a reference for new projects. In the canal route selection of this invention, the case-based reasoning knowledge base draws on the experience of historical cases to guide the formulation of route principles and avoid repeating past mistakes.

[0045] Least squares is a mathematical optimization technique used to estimate the parameters of unknown data so as to minimize the sum of squared residuals between the observed data and the prediction model.

[0046] The Analytic Hierarchy Process (AHP) is a decision analysis method used to handle complex multi-criteria decision problems. In this invention, AHP is used to determine the weights of different ecological factors, thereby treating all considerations fairly in a multi-objective optimization model.

[0047] Kriging interpolation (KI) is a geostatistical method used for spatial prediction and estimation, particularly well-suited for handling spatially heterogeneous data. In 3D geological modeling, KI is used to construct more accurate stratigraphic interface models.

[0048] A Triangulated Irregular Network (TIN) is a 3D model representing a terrain surface. It connects points on the terrain through a series of triangles, forming an irregular triangular mesh. In the 3D geological modeling of this invention, TIN is used to integrate the terrain surface model and subsurface structure to create a 3D geographic information framework.

[0049] It should be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, and displayed data) collected in this public disclosure are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with the relevant laws, regulations, and standards of the relevant regions, and necessary confidentiality measures have been taken. This does not violate public order and good morals, and corresponding operation entry points are provided for users to choose to authorize or refuse. For example, this system has interfaces with relevant users or organizations. Before obtaining relevant information, a request to obtain the information needs to be sent to the aforementioned user or organization through the interface, and the relevant information is obtained only after receiving consent from the aforementioned user or organization.

[0050] It should be noted that in this disclosure, customer information is collected and analyzed, and users are provided with corresponding operation entry points to choose whether to agree to or reject the automated decision results; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0051] The following embodiments of the present invention can be applied to systems / applications / equipment that recommend route selection schemes for various canal projects. The present invention can be applied to waterway engineering, particularly the route selection stage of long-distance canal construction projects, such as the preliminary route selection and optimization of new long-distance canal projects. In situations where basic data is scarce or difficult to obtain quickly, the present invention can rapidly generate multiple candidate routes and conduct comprehensive evaluations, helping decision-makers to screen the most promising route selection schemes in the early stages. For projects requiring waterway modifications, the present invention can, based on the existing waterway's geographical and geological information, combined with intelligent analysis, propose optimized suggestions for the modification route, aiming to improve the waterway's navigation capacity and safety.

[0052] The present invention will now be described in detail with reference to various embodiments.

[0053] Example 1

[0054] According to an embodiment of the present invention, an embodiment of a method for recommending a route selection scheme for a canal project is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0055] Figure 1 This is a flowchart of a recommended method for an optional canal engineering route selection scheme according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps S101 to S105, and each step is described in detail below.

[0056] Step S101: Multi-source geographic information of the target area for the proposed canal project site selection is fused, and a basic geographic information framework is constructed based on the multi-source fused information. The target area is divided into multiple sub-areas to be evaluated.

[0057] Optionally, step S101 includes: preprocessing the multi-source geographic information of the target area for the proposed canal project site selection, wherein the preprocessing strategy includes at least one of the following: coordinate system unification, projection method unification, data format standardization, and data cleaning. Data cleaning includes: removing redundant nodes in the topographic map, removing cloud mask areas in the remote sensing image, and correcting coordinate anomalies in the survey data; using optical stereo photogrammetry and radar interferometry strategies to obtain remote sensing images and topographic maps of the target area from multiple angles, and constructing a three-dimensional topographic model based on the remote sensing images of the target area; calculating transformation parameters using the least squares method; registering the remote sensing images and topographic maps using the transformation parameters based on pre-selected ground feature points; identifying the correlation between the registered remote sensing images and survey data using geospatial analysis tools; constructing a geospatial database model based on the correlation; integrating the topographic features of the target area, remote sensing image interpretation results, and survey data using the geospatial database model to obtain a multi-dimensional dataset; and constructing a basic geographic information framework based on the multi-dimensional dataset.

[0058] In step S101, the target area for the proposed canal project site selection is divided into multiple sub-areas to be evaluated to ensure the local accuracy and overall consistency of geographic information. Considering the diverse sources of geographic information and their differences in format, coordinate system, projection method, and data quality, preprocessing strategies become a prerequisite for multi-source information fusion. The preprocessing strategies in this embodiment cover at least one of the following: Coordinate System 1: Unifying all data sources into a consistent coordinate system to eliminate spatial benchmark differences and improve the accuracy of data overlay; Unified Projection Method: Ensuring the accuracy of data after projection conversion; Data Format Standardization: Unifying the storage and retrieval formats of data to facilitate data exchange and processing between different GIS software; Data Cleaning: Removing redundant nodes from topographic maps to reduce data redundancy and improve processing efficiency; Removing cloud mask areas from remote sensing images to avoid the influence of clouds on topographic measurements; Correcting coordinate outliers in survey data to ensure the accuracy of geographic positioning of the data.

[0059] Subsequently, this embodiment employs optical stereo photogrammetry and radar interferometry strategies to acquire remote sensing images and topographic maps of the target area from multiple angles, constructing a three-dimensional terrain model. The optical stereo photogrammetry strategy utilizes stereo images captured by satellite-borne optical cameras, calculating the three-dimensional coordinates of the ground based on the parallax principle. It is suitable for areas with significant terrain variations. Optical stereo photogrammetry technology uses satellite-borne optical cameras to capture multiple images of the same area from different angles (e.g., forward-looking, front-looking, and back-looking), calculating the three-dimensional coordinates of ground points through the parallax principle, similar to how the human eye perceives depth through binocular parallax. The "stereo image pairs" of satellite images can construct a three-dimensional terrain model. The baseline-to-height ratio (baseline length / satellite height) is considered; the larger the ratio, the higher the elevation accuracy. The radar interferometry strategy calculates surface elevation or deformation through the phase difference of microwave signals, acquiring terrain information even under vegetation cover or cloud cover conditions, with accuracy down to the centimeter level.

[0060] This embodiment further employs the Least Squares Method (LSM) to calculate transformation parameters, which ensure geometric consistency between the remote sensing image and the topographic map. Based on pre-selected feature points (such as road intersections and building corners), the transformation parameters calculated using LSM are used for precise registration of the remote sensing image and the topographic map, with the error controlled within 1 to 2 pixels, thereby establishing a direct spatial association between the remote sensing image and the topographic map.

[0061] Next, geospatial analysis tools are used to identify the relationships between the registered remote sensing images and exploration data, including attribute linking and profile and 3D terrain integration. Attribute linking associates exploration attributes such as borehole depth and lithology with spatial points through the ID field, forming a spatial dataset with attributes. Profile and 3D terrain integration uses borehole data to generate stratigraphic interfaces and combines the tonal differences of strata in remote sensing images to correct the interface morphology, ultimately forming a 3D geographic information framework that includes topographic relief and underground structure.

[0062] In the process of building a geospatial database model, this embodiment integrates the topographic features of the target area, remote sensing image interpretation results, and survey data to form a multi-dimensional dataset. It not only supports SQL queries and spatial statistics, but also stores and manages multi-source spatial data, enabling efficient data retrieval and application.

[0063] Optionally, the steps for constructing a basic geographic information framework based on a multi-dimensional dataset include: extracting geological boundaries from remote sensing image interpretation results, geological exploration points from exploration data, and profile lines from topographic features; generating stratigraphic interfaces based on profile lines and borehole data to construct a topographic surface model, and correcting the interface morphology of the topographic surface model by combining stratigraphic tonal differences in remote sensing images; constructing a geological body model based on geological boundaries and geological exploration points; and constructing a basic geographic information framework that includes topographic relief and underground structure based on the topographic surface model and the geological body model.

[0064] First, geological boundaries are identified from remote sensing image interpretation results, based on tonal differences or texture features of different rock and soil types in the images. Second, geological exploration points, such as borehole locations and depths, lithological information, etc., are extracted from exploration data, as well as profile lines in topographic elements, which are used to visually display the longitudinal or transverse morphological features of the earth's surface. Then, the two-dimensional geological information is converted into a three-dimensional model using borehole data and profile lines (for example, by using Kriging interpolation or triangular mesh modeling techniques to generate stratigraphic interfaces), which facilitates the understanding and analysis of deep geological structures. Finally, combined with topographic data, a topographic surface model is constructed using topographic surface modeling techniques to reflect the undulating features of the earth's surface.

[0065] Based on the differences in stratigraphic tones in remote sensing imagery, the stratigraphic boundaries in the topographic surface model are corrected. This correction takes into account supplementary information from the remote sensing data, which helps to more accurately depict the actual distribution of strata. Using extracted geological boundaries and geological survey points, a geological body model is constructed using geological modeling software. The model includes three-dimensional geometric information of underground structures such as rock strata and faults. Subsequently, the topographic surface model and the geological body model are integrated to create a three-dimensional geographic information framework that not only shows the morphology of the Earth's surface but also reveals the underground geological structure.

[0066] Step S102: Use fuzzy logic rules to perform geological stability assessments on different sub-regions to be assessed, and mark unfavorable geological sections based on the geological stability assessment results.

[0067] Optionally, the steps of using fuzzy logic rules to assess the geological stability of different sub-regions to be evaluated include: for each sub-region to be evaluated, determining a set of input variables related to geological stability, wherein the input variables include at least one of the following: rock type, seismic wave velocity, groundwater level, and soil moisture content; using membership functions to map the values ​​of the input variables to their respective fuzzy sets; based on a pre-defined fuzzy rule base and combined with the fuzzy sets of the input variables, calculating the fuzzy output of the geological stability of each sub-region to be evaluated; and using a defuzzification strategy to convert the fuzzy output into a geological stability level.

[0068] For each sub-region to be evaluated, a set of input variables closely related to geological stability is defined. These variables may include rock type, seismic wave velocity, groundwater level, and soil moisture content. Each variable carries unique information about geological stability; for example, rock type can indicate the physical properties of the strata, while seismic wave velocity reflects the compactness of the subsurface structure. By establishing a membership function (MF), the precise values ​​of the input variables are mapped to a series of fuzzy sets. For example, rock type can be divided into fuzzy sets of "very stable," "stable," "moderately stable," "unstable," and "very unstable," while soil moisture content can be defined as a fuzzy set of "low," "medium," and "high."

[0069] In this embodiment, a pre-defined Fuzzy Rule Base (FRB) is established, which contains fuzzy logic rules extracted from experts and historical cases. For example, "If the rock type is very stable and the seismic wave velocity is high, then the geological stability is very stable." These rules reflect the complex interactions between geological variables and the domain knowledge of their comprehensive impact on geological stability.

[0070] Based on fuzzy sets and fuzzy rule bases of input variables, a fuzzy output for the geological stability of each sub-region to be evaluated is calculated through a fuzzy logic inference mechanism, yielding the geological stability assessment results for each sub-region. Finally, a defuzzification strategy is employed to convert the calculated fuzzy output into clear geological stability levels, such as "extremely stable," "stable," "moderate," "unstable," and "extremely unstable." Commonly used defuzzification methods may include the centroid method or the maximum membership method, ensuring that the assessment results reflect both the uncertainty of geological conditions and are easy for decision-makers to understand and apply.

[0071] Step S103: Based on the pre-planned set of canal route selection rules, historical case knowledge base, basic geographic information framework, river system transportation demand in the target area, and geological stability assessment results, N canal route schemes are initially proposed, where N is a positive integer greater than 1.

[0072] Optionally, step S103 includes: generating preliminary route selection guidelines based on the canal route selection rule set, combined with the geographical conditions and environmental protection requirements of the target area; using a historical case knowledge base, identifying successful route selection patterns of historical canal projects under similar conditions to the target area through case reasoning; conducting multi-source data analysis based on the basic geographic information framework and geological stability assessment results to identify potential risk points and adjustment space of the canal route; extracting historical freight volume data, shipping demand, water resource allocation targets, and existing transportation network correlation information from river system transportation demand to determine the transportation demand priority of the canal route; and using a heuristic search algorithm to initially formulate N canal route schemes based on the route selection guidelines, successful route selection patterns of historical canal projects, potential risk points of the canal route, adjustment space, and transportation demand priority.

[0073] First, this embodiment, based on the "Code for Design of Waterway Engineering" (JTS181-2016) and engineering practice experience, combined with the specific geographical conditions of the target area (such as topographic relief and water system distribution) and environmental protection requirements (such as the protection of ecologically sensitive areas and basic farmland), generates route selection guidelines to ensure that the canal route design makes full use of natural topography and hydraulic conditions while minimizing environmental impact. Then, using a historical case knowledge base and case-based reasoning techniques, it identifies successful route selection patterns from previous canal projects with similar natural and socio-economic conditions to the target area.

[0074] Based on the constructed basic geographic information framework and geological stability assessment results, spatial analysis of multi-source data was conducted to identify potential geological risk points (such as landslides and karst areas) and their adjustment space along the canal route. The analysis comprehensively considered multiple dimensions such as topography, geological structure, hydrological conditions, and ecological environment to ensure the comprehensiveness and robustness of the route selection scheme.

[0075] In addition, this embodiment starts from the transportation demand of the river system in the target area, extracts historical freight volume data, analyzes the seasonal changes in shipping demand, cargo types, transportation frequency, etc., and at the same time considers water resource allocation targets (such as irrigation and urban water supply) and the utilization efficiency of the existing transportation network to determine the priority of transportation demand for the canal route.

[0076] Based on the above analysis, heuristic search algorithms such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO) are used to initially propose canal routes. These algorithms continuously explore and optimize route options by simulating natural selection or ant colony behavior. This ensures that, considering route selection guidelines, historical patterns, risk points, and transportation demand priorities, the initially proposed N canal routes meet engineering objectives while minimizing adverse environmental impacts.

[0077] Optionally, the construction of the historical case knowledge base includes: obtaining a set of completed historical canal engineering cases; extracting key information from the case documents and remote sensing images of each historical canal engineering case using text mining and image recognition strategies to obtain a set of key information, wherein the key information includes at least one of the following: terrain features, geological conditions, route selection scheme, engineering volume, construction difficulties, and environmental factors; and integrating the extracted set of key information into the knowledge base using a case reasoning framework to obtain the historical case knowledge base.

[0078] This study collects a set of completed historical canal engineering case studies, focusing on gathering documents such as survey reports, design documents, construction summaries, and environmental impact assessment reports, as well as relevant remote sensing imagery and topographic mapping data. Using text mining and image recognition strategies, key information is automatically extracted from the case study documents and remote sensing images. Text mining utilizes natural language processing to identify keywords or phrases such as topographic features, geological conditions, and engineering quantities, while image recognition uses deep learning models to identify specific features such as river course, topography, and ecological protection zones. The extracted key information is integrated into a case study reasoning framework, forming part of a knowledge base. By comparing the similarities between current project requirements and historical cases, this knowledge base assists the decision-making process and reduces redundant research and trial-and-error costs. The key information for each case study is organized into structured entries for easy searching and citation, while also providing rich example resources for subsequent intelligent decision-making.

[0079] Specifically, when selecting cases, the selection principles may include: representativeness, that is, covering different geographical environments (plains, mountains, river deltas), climate zones (humid zones, arid zones), and project scale (large, medium, and small); and completeness, that is, the cases should include the background of the route selection (such as shipping demand and water resource allocation objectives), technical parameters (such as route length, drop, and canal bottom width), key influencing factors (such as geological disaster risks and the distribution of ecological protection zones), and implementation effects (such as construction period, cost, and operational benefits).

[0080] Step S104: Identify the matching relationship between each initially proposed canal route and the set of natural resource constraints, and adjust the constraints in the canal route.

[0081] Optionally, the step of identifying the matching relationship between each initially proposed canal route and the set of natural resource constraints, and adjusting the canal route, includes: digitizing each initially proposed canal route and storing it in a geographic information system (GIS) format; using the spatial analysis function of the GIS to identify conflict points between the canal route and the set of natural resource constraints; analyzing the identified conflict points, assessing the impact of the conflict points on the canal engineering corresponding to the canal route, and obtaining the assessment results; and adjusting the canal route based on the assessment results.

[0082] First, each initially proposed canal route is converted into digital form and stored in a GIS-compatible format. Then, using the spatial analysis capabilities of GIS, this embodiment identifies conflict points between the canal route proposals and a set of natural resource constraints. These constraints cover ecologically sensitive areas (such as wetland parks and nature reserves), basic farmland, mineral resource distribution areas, and cultural relic protection areas. Through spatial overlay analysis, the overlapping or near-overlapping areas between the canal route and these constraints—i.e., conflict points—can be clearly displayed.

[0083] It should be noted that for each identified conflict point, this embodiment assesses the impact factors of these conflict points on the canal project, including but not limited to: the potential degree of damage to the ecological environment, the amount of arable land occupied, the interference with mineral resource extraction, and the protection requirements for cultural relics and heritage. Finally, based on the assessment results, this embodiment adjusts the canal route plan to reduce or avoid conflicts with natural resource constraints. Adjustment strategies may include: bypassing ecologically sensitive areas, adjusting the route to reduce the occupation of basic farmland, optimizing the path to avoid mineral resource overlay, and designing special protection measures to take into account cultural relics and historical sites.

[0084] In this embodiment, GIS is not only used to store and manage canal route plans, but also serves as a core spatial analysis tool for identifying conflict points, providing a wealth of spatial analysis modules. Matching the canal route plan with natural resource constraints is a dynamic process; as the project progresses, new constraints may emerge. This embodiment continuously and dynamically adjusts the plan to ensure that the design always matches the latest constraints.

[0085] Step S105: Use a multi-objective optimization model to compare and select the multiple canal route schemes that have been adjusted, and determine the recommended canal route scheme.

[0086] Optionally, step S105 includes: obtaining the objective index function of the multi-objective optimization model and defining the constraints in the multi-objective optimization model; inputting the parameters of each canal route scheme into the multi-objective optimization model, running the multi-objective optimization algorithm by the multi-objective optimization model, iteratively optimizing different canal route schemes, and selecting the canal route scheme with the highest comprehensive evaluation score as the recommended canal route scheme.

[0087] The objective indicator function can include key performance indicators of canal projects, such as minimizing project costs, minimizing environmental impact, and maximizing transportation efficiency. Specifically, the objective of minimizing project costs can focus on the calculation of earthwork volume, concrete and steel usage, and the market prices of these materials; the objective of minimizing environmental impact can consider the length of the crossing of ecologically sensitive areas, the area of ​​basic farmland occupied, and the degree of impact on specific environmental factors (such as water quality and soil); and the objective of maximizing transportation efficiency can focus on the matching degree between the designed navigation capacity and the actual freight volume.

[0088] Setting constraints is crucial to ensuring the feasibility of the optimization process. Constraints may include, but are not limited to: the turning radius of the waterway must exceed a specific threshold to ensure the safe passage of ships; active faults or high-risk earthquake zones must be avoided to ensure engineering safety; and the canal route design must meet ecological protection requirements, such as minimizing interference with drinking water sources.

[0089] Detailed parameters of each canal route scheme, such as route length, rivers along the route, number of ecologically sensitive areas to be traversed, and estimated engineering costs, are input into a multi-objective optimization model. The model will run multi-objective optimization algorithms, such as non-dominated sorting genetic algorithms or particle swarm optimization, to iteratively optimize different canal route schemes. By evaluating the performance of each scheme on the objective index function, the optimal solution or solution set that can balance engineering, environmental, and socio-economic benefits is identified.

[0090] Through the above steps, multi-source geographic information of the target area for the proposed canal project can be fused, and a basic geographic information framework can be constructed based on the fused information. The target area is divided into multiple sub-areas to be evaluated. Fuzzy logic rules are used to conduct geological stability assessments on different sub-areas to be evaluated, and unfavorable geological sections are marked based on the geological stability assessment results. According to the pre-planned set of canal route selection rules, historical case knowledge base, basic geographic information framework, river system transportation demand in the target area, and geological stability assessment results, N preliminary canal route schemes are proposed, where N is a positive integer greater than 1. The matching relationship between each preliminary proposed canal route scheme and the set of natural resource constraints is identified, and the constraints in the canal route are adjusted. A multi-objective optimization model is used to compare and select the multiple adjusted canal route schemes to determine the recommended canal route scheme. In this embodiment, by fusing multi-source geographic information to construct a basic geographic information framework, the limitations of a single data source can be overcome, providing more comprehensive and accurate topographic and geological information. This reduces the workload and cost of on-site investigation. In the geological condition assessment stage, a fuzzy inference system is used to handle uncertainties and incomplete information, assessing the geological stability of different regions and shifting the assessment of geological conditions from qualitative to quantitative, thereby reducing the intensity and cost of geological exploration. The canal route utilizes intelligent algorithms to establish a multi-objective optimization model, automatically adjusting the route plan to find the canal path with the best cost-effectiveness ratio. Based on historical data feedback, parameter adjustments and model optimizations are performed to improve accuracy and reliability, reducing errors and costs in planning. This solves the technical problems of high workload and high cost in the planning and route selection of long-distance canal projects due to the influence of topography and geology.

[0091] The following describes in detail another optional implementation method.

[0092] This implementation method uses the Xiang-Gui Canal connection project as an example to illustrate the canal selection method, which is characterized by multi-source data fusion technology, fuzzy and uncertainty processing technology, experience and knowledge case base, and major avoidance factors, which significantly reduces the cost of preliminary work and shortens the preliminary work cycle.

[0093] In a first aspect, this invention proposes a method for route selection in canal engineering under conditions of limited information over long distances, comprising the following steps:

[0094] S1: Collect topographic mapping and survey data, and combine them with satellite remote sensing imagery to establish a basic geographic information framework. Collect topographic and geological data on roads and bridges within the project area, combine low-precision topographic data with satellite remote sensing imagery, and initially outline the topographic relief and water system distribution to provide a basic geographic information framework for canal route selection. At the same time, identify the distribution locations of important mineral resources and industrial parks.

[0095] S2: Drawing on the route selection experience of other canal projects under similar geological and topographical conditions, formulate canal route selection principles and establish a knowledge base based on case-based reasoning. The canal route selection principles include: first, fully utilizing topography and river conditions to achieve a relatively straight route and minimize engineering investment; second, maximizing hinterland transport capacity and maximizing its driving effect on economic and social development; third, minimizing the difficulty of water supply for navigation and ensuring good comprehensive utilization of water resources; fourth, facilitating environmental protection and reducing the impact on the ecological environment along the route; and fifth, appropriately considering the development of resources along the route.

[0096] S3: Perform fuzzy evaluation of geological stability and identify unfavorable geological sections. With only a limited amount of borehole data, a fuzzy inference system is used to perform fuzzy evaluation of the geological stability of different areas, dividing them into relatively stable, less unstable, and other fuzzy regions, providing a basis for route selection to avoid unfavorable geological sections.

[0097] It should be noted that a fuzzy inference system may include input variables, output variables, fuzzy sets, fuzzy rules, fuzzy inference mechanisms, defuzzification, system evaluation and optimization, etc. The following is an illustrative explanation of each part.

[0098] (1) Determine the input variables: Select physical and mechanical parameters related to the stratigraphic distribution and lithology as input variables, such as the elevation, unit weight, cohesion, friction angle, groundwater level, peak ground acceleration, etc. of each soil layer. These variables can be obtained using existing borehole data, remote sensing data, or through supplementary geological exploration.

[0099] (2) Determine the output variables: Divide them into stability levels such as extremely stable (0.8-1.0), stable (0.6-0.8), moderate (0.4-0.6), unstable (0.2-0.4), and extremely unstable (0-0.2), and output a risk zoning map in combination with GIS visualization.

[0100] (3) Define fuzzy sets.

[0101] For each input and output variable, several fuzzy sets are defined based on their value range and actual geological significance. For example, for rock types, fuzzy sets such as "sandstone," "shale," and "limestone" can be defined; for soil layers, fuzzy sets such as "silt," "clay," "silty clay," and "sand" can be defined. Each fuzzy set is described by a membership function, which maps the variable's value to a membership degree between 0 and 1, indicating the degree to which the value belongs to the fuzzy set. For example, the elevation of a soil layer can be determined by inference from nearby boreholes. Cohesion and friction angle can be determined by difference from nearby boreholes.

[0102] (4) Establish fuzzy rules.

[0103] A fuzzy rule base is established, where the premise of each rule is a fuzzy set combination of input variables, and the conclusion is a fuzzy set of output variables. The number and complexity of the rules depend on the complexity of the geological conditions and the available knowledge. For example, "If the rock type is sandstone and the seismic wave velocity is high, then the strata are likely shallow, dense sandstone strata." "If the rock type is limestone and the seismic wave velocity varies greatly, then the strata may contain karst caves or geological fracture zones." "If the soil type is cohesive soil and the seismic wave velocity is low, then the strata may contain silt."

[0104] (5) Design a fuzzy reasoning mechanism.

[0105] Taking the Mamdani reasoning method as an example, its process includes the following steps:

[0106] 1) Fuzzification: The precise value of the input variable is converted into the membership degree of the corresponding fuzzy set according to its membership function.

[0107] 2) Rule matching: Match the fuzzy input with the rules in the rule base to find all rules that meet the preconditions.

[0108] 3) Inference Calculation: For each matching rule, the membership degree of the conclusion part is calculated based on the membership degree of its premise part. Methods such as taking the minimum value or multiplication are commonly used to determine the membership degree of the conclusion.

[0109] 4) Fuzzy Synthesis: The conclusions of all matching rules are synthesized to obtain the final fuzzy output. Methods such as taking the average value can be used for synthesis.

[0110] (6) Defuzzification.

[0111] The fuzzy output obtained through fuzzy inference needs to be converted into a precise value. Common defuzzification methods include the centroid method and the maximum membership method. For example, the centroid method obtains the precise value by calculating the centroid of the fuzzy output set, while the maximum membership method selects the element with the largest membership degree as the precise value.

[0112] (7) System evaluation and optimization.

[0113] The constructed fuzzy inference system is tested and evaluated using known geological data. The system's prediction accuracy, recall, and other indicators are calculated. If the system's performance does not meet the requirements, adjustments and optimizations can be made to the fuzzy set partitioning, the shape of the membership function, and the rules in the rule base to improve the system's accuracy and reliability.

[0114] When constructing a fuzzy inference system for stratigraphic distribution, it is necessary to fully integrate geological expertise and actual data, and continuously adjust and improve each part of the system so that it can accurately reflect the laws and characteristics of stratigraphic distribution.

[0115] S4: Based on the principles of proximity to river systems, high demand for cargo transportation, and avoidance of unfavorable geological sections, several canal routes are initially proposed. Proximity to river systems means shorter canal excavation distances and less workload.

[0116] Table 1 below illustrates the four proposed initial canal routes and the connecting lines between them.

[0117] Table 1. Description of the Canal Route

[0118]

[0119]

[0120] S5: Identify the relationship between the canal route and constraints such as high-speed rail bridges, railway bridges, ecological protection areas, cultural relics, and mineral resources.

[0121] Table 2 below illustrates the relationship between the proposed canal route and the main limiting factors of the ecological environment.

[0122] Table 2. Relationship between canal routes and major ecological and environmental limiting factors.

[0123]

[0124] S6: Conduct comparative analysis of avoidance and unavoidable options, and propose an optimized route selection scheme.

[0125] For each factor identified by S5, alternative schemes are compared and evaluated. For sensitive points that can be avoided, conflict points are avoided during canal route selection, optimizing the canal route, reducing the difficulty of project implementation, and saving project investment. For unavoidable conflict points, unavoidable alternative schemes are evaluated, and the project investment for the conflict points is determined.

[0126] S7: Compare and select from the initial proposed route options to preliminarily determine the recommended route. List the advantages and disadvantages of each route, and use an intelligent algorithm for canal route optimization. Combine the canal route optimization constraints and objective function to conduct qualitative and quantitative comparisons and determine the recommended route for the canal project.

[0127] For example, among the four routes illustrated above, Route 1 has fewer tiers, a relatively low elevation in the mountain-crossing section, and a shorter length (28km, of which 16km is a dry, excavated section); the navigation time across the canal is relatively short, resulting in higher operational efficiency; the mountain-crossing section can be replenished by gravity flow; it does not involve the reconstruction of high-speed railway bridges; there are no catastrophic factors affecting the ecologically sensitive targets involved; the investment amount is relatively small; the difficulty of land acquisition, demolition, and reconstruction is moderate; and it has good planning compliance. Based on a comprehensive comparison, Route 1 is the recommended option.

[0128] The optimization objective functions include functions for minimizing engineering costs, minimizing environmental impact, and maximizing transportation efficiency.

[0129] In the context of large-span, limited information, comprehensive and detailed data collection is costly and time-consuming. This embodiment addresses the problems of long distances and limited basic data reserves in canal connection projects such as the Xiang-Gui Canal. It proposes a canal route selection method characterized by multi-source data fusion technology, fuzzy and uncertainty processing technology, experience and knowledge case library, and major avoidance factors, which significantly reduces the cost and shortens the preliminary work cycle.

[0130] The following is a detailed description with reference to another embodiment.

[0131] Example 2

[0132] The device for recommending a canal engineering route selection scheme provided in this embodiment includes multiple implementation units, each of which corresponds to a specific implementation step in Embodiment 1 above.

[0133] Figure 2 This is a schematic diagram of a recommended device for an optional canal engineering route selection scheme according to an embodiment of the present invention, as shown below. Figure 2 As shown, the recommended device for the canal project route selection scheme may include: an information fusion unit 21, a geological stability assessment unit 22, a route planning unit 23, a constraint adjustment unit 24, and a recommended route determination unit 25.

[0134] Among them, the information fusion unit 21 is used to fuse multi-source geographic information of the target area for the proposed canal project site selection, and to construct a basic geographic information framework based on the multi-source fused information, wherein the target area is divided into multiple sub-areas to be evaluated.

[0135] The geological stability assessment unit 22 is used to assess the geological stability of different sub-regions to be assessed using fuzzy logic rules, and to mark unfavorable geological sections based on the geological stability assessment results.

[0136] The route planning unit 23 is used to initially plan N canal route schemes based on the pre-planned set of canal route selection rules, historical case knowledge base, basic geographic information framework, river system transportation demand in the target area and geological stability assessment results, where N is a positive integer greater than 1.

[0137] The constraint adjustment unit 24 is used to identify the matching relationship between each initially proposed canal route scheme and the set of natural resource constraints, and to adjust the constraints in the canal route.

[0138] The recommended route determination unit 25 is used to compare and select multiple canal route schemes that have been adjusted using a multi-objective optimization model, and determine the recommended canal route scheme.

[0139] The aforementioned device for recommending canal route selection schemes can fuse multi-source geographic information of the target area for the proposed canal project site selection through information fusion unit 21, construct a basic geographic information framework based on the multi-source fused information, wherein the target area is divided into multiple sub-areas to be evaluated, and the geological stability assessment unit 22 uses fuzzy logic rules to conduct geological stability assessments on different sub-areas to be evaluated, and marks unfavorable geological sections based on the geological stability assessment results, and the route formulation unit 23 preliminarily formulates N canal route schemes based on the pre-formulated canal route selection rule set, historical case knowledge base, basic geographic information framework, river system transportation demand in the target area, and geological stability assessment results, wherein N is a positive integer greater than 1, and the constraint condition adjustment unit 24 identifies the matching relationship between each preliminarily formulated canal route scheme and the natural resource constraint condition set, and adjusts the constraints in the canal route, and the recommended route determination unit 25 uses a multi-objective optimization model to compare and select the multiple adjusted canal route schemes to determine the recommended canal route scheme.

[0140] In this embodiment, by fusing multi-source geographic information to construct a basic geographic information framework, the limitations of a single data source can be overcome, providing more comprehensive and accurate topographic and geological information. This reduces the workload and cost of on-site investigation. In the geological condition assessment stage, a fuzzy inference system is used to handle uncertainties and incomplete information, assessing the geological stability of different regions and shifting the assessment of geological conditions from qualitative to quantitative, thereby reducing the intensity and cost of geological exploration. The canal route utilizes intelligent algorithms to establish a multi-objective optimization model, automatically adjusting the route plan to find the canal path with the best cost-effectiveness ratio. Based on historical data feedback, parameter adjustments and model optimizations are performed to improve accuracy and reliability, reducing errors and costs in planning. This solves the technical problems of high workload and high cost in the planning and route selection of long-distance canal projects due to the influence of topography and geology.

[0141] Optionally, the information fusion unit includes: an information preprocessing module, used to preprocess multi-source geographic information of the target area for the proposed canal project site selection, wherein the preprocessing strategies include at least one of the following: coordinate system unification, projection method unification, data format standardization, and data cleaning, wherein data cleaning includes: removing redundant nodes in topographic maps, removing cloud mask areas in remote sensing images, and correcting coordinate anomalies in survey data; and a remote sensing image acquisition module, used to obtain remote sensing images and topographic maps of the target area from multiple angles using optical stereo photogrammetry and radar interferometry strategies, based on the remote sensing data of the target area. The system constructs a 3D terrain model from images; an image registration module calculates transformation parameters using the least squares method; based on pre-selected ground feature points, it registers remote sensing images with topographic maps using transformation parameters; an image data relationship analysis module uses geospatial analysis tools to identify the correlation between registered remote sensing images and survey data; and an information integration module constructs a geospatial database model based on these correlations, integrates topographic features of the target area, remote sensing image interpretation results, and survey data using the geospatial database model to obtain a multi-dimensional dataset, and constructs a basic geographic information framework based on the multi-dimensional dataset.

[0142] Optionally, the information integration module includes: a geological information extraction module, used to extract geological boundaries from remote sensing image interpretation results, geological exploration points from exploration data, and profile lines from topographic elements; a topographic surface model construction module, used to generate stratigraphic interfaces based on profile lines and borehole data to construct a topographic surface model, and to correct the interface morphology of the topographic surface model by combining stratigraphic tonal differences in remote sensing images; a geological body model construction module, used to construct a geological body model based on geological boundaries and geological exploration points; and a basic geographic information framework construction module, used to construct a basic geographic information framework including topographic relief and underground structure based on the topographic surface model and the geological body model.

[0143] Optionally, when constructing a historical case knowledge base, the device for recommending canal engineering route selection schemes includes: a historical canal engineering case set acquisition unit, used to acquire a set of completed historical canal engineering cases; a historical canal engineering case information extraction unit, used to extract key information from the case documents and remote sensing images of each historical canal engineering case through text mining and image recognition strategies, to obtain a key information set, wherein the key information includes at least one of the following: terrain features, geological conditions, route selection scheme, engineering volume, construction difficulties, and environmental factors; and a historical case knowledge base determination unit, used to integrate the extracted key information set into the knowledge base using a case reasoning framework, to obtain the historical case knowledge base.

[0144] Optionally, the geological stability assessment unit includes: an input variable determination module, used to determine a set of input variables related to geological stability for each sub-region to be assessed, wherein the input variables include at least one of the following: rock type, seismic wave velocity, groundwater level, and soil moisture content; an input variable mapping module, used to map the values ​​of the input variables to their respective fuzzy sets using membership functions; a fuzzy output calculation module, used to calculate the fuzzy output of the geological stability of each sub-region to be assessed based on a pre-set fuzzy rule base and in combination with the fuzzy sets of the input variables; and a geological stability level conversion module, used to convert the fuzzy output into a geological stability level using a defuzzification strategy.

[0145] Optionally, the route planning unit includes: a route selection guidance principle generation module, used to generate preliminary route selection guidance principles based on the canal route selection rule set, combined with the geographical conditions and environmental protection requirements of the target area; a route selection success module identification module, used to identify successful route selection patterns of historical canal projects under similar conditions to the target area through case reasoning using a historical case knowledge base; a multi-source data analysis module, used to conduct multi-source data analysis by combining the basic geographic information framework and geological stability assessment results, and identify potential risk points and adjustment space of the canal route; a transportation demand extraction module, used to extract historical freight volume data, shipping demand, water resource allocation targets, and existing transportation network correlation information from the river system transportation demand, and determine the transportation demand priority of the canal route; and a canal route planning module, used to initially plan N canal route schemes based on the route selection guidance principles, successful route selection patterns of historical canal projects, potential risk points of the canal route, adjustment space, and transportation demand priority using a heuristic search algorithm.

[0146] Optionally, the constraint adjustment unit includes: a route plan storage module, used to digitize each initially proposed canal route plan and store it in a geographic information system (GIS) format; a conflict point identification module, used to identify conflict points between the canal route plan and the set of natural resource constraints using the spatial analysis function of the GIS; an impact assessment module, used to analyze the identified conflict points, assess the impact of the conflict points on the canal project corresponding to the canal route plan, and obtain the assessment results; and a route adjustment module, used to adjust the canal route plan based on the assessment results.

[0147] Optionally, the recommended route determination unit includes: an index function acquisition module, used to acquire the objective index function of the multi-objective optimization model and define the constraints in the multi-objective optimization model; and a recommended route determination module, used to input the parameters of each canal route scheme into the multi-objective optimization model, run the multi-objective optimization algorithm in the multi-objective optimization model, iteratively optimize different canal route schemes, and select the canal route scheme with the highest comprehensive evaluation score as the recommended canal route scheme.

[0148] The device for recommending the route selection scheme of the canal project may also include a processor and a memory. The information fusion unit 21, the geological stability assessment unit 22, the route planning unit 23, the constraint adjustment unit 24, and the recommended route determination unit 25 are all stored in the memory as program units. The processor executes the program units stored in the memory to realize the corresponding functions.

[0149] The aforementioned processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and adjusting kernel parameters allows for route selection in canal engineering projects under conditions of limited information over long distances.

[0150] The aforementioned memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0151] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the recommended method of the canal engineering route selection scheme of any one of the above embodiments.

[0152] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the recommended method for canal engineering route selection schemes of any one of the above embodiments.

[0153] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method for recommending canal engineering route selection schemes as described in various embodiments of this application.

[0154] This application also provides a computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the recommended method for canal engineering route selection schemes described in various embodiments of this application.

[0155] Figure 3 This is a hardware structure block diagram of an electronic device (or mobile device) for implementing a recommended method for canal engineering route selection according to an embodiment of the present invention. Figure 3 As shown, an electronic device may include one or more ( Figure 3The processor (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and memory 304 for storing data are illustrated using 302a, 302b, ..., 302n. In addition, it may include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 3 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, the electronic device may also include components that are more... Figure 3 The more or fewer components shown, or having the same Figure 3 The different configurations shown.

[0156] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0157] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0162] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for recommending route selection schemes for canal engineering projects, characterized in that, include: Multi-source geographic information of the target area for the proposed canal project site selection is fused, and a basic geographic information framework is constructed based on the multi-source fused information. The target area is divided into multiple sub-areas to be evaluated. Fuzzy logic rules are used to assess the geological stability of different sub-regions to be evaluated, and unfavorable geological sections are marked based on the geological stability assessment results. Based on the pre-determined set of canal route selection rules, the historical case knowledge base, the basic geographic information framework, the river system transportation demand in the target area, and the geological stability assessment results, N canal route schemes are initially proposed, where N is a positive integer greater than 1. Identify the matching relationship between each initially proposed canal route and the set of natural resource constraints, and adjust the constraints in the canal route accordingly; A multi-objective optimization model was used to compare and select from multiple canal route schemes that had undergone adjustments, and a recommended canal route scheme was determined.

2. The method for recommending route selection schemes for canal projects according to claim 1, characterized in that, The steps for fusing multi-source geographic information of the target area for the proposed canal project site selection and constructing a basic geographic information framework based on the fused multi-source information include: The multi-source geographic information of the target area for the proposed canal project site selection is preprocessed, wherein the preprocessing strategy includes at least one of the following: coordinate system unification, projection method unification, data format standardization, and data cleaning. The data cleaning includes: removing redundant nodes in topographic maps, removing cloud mask areas in remote sensing images, and correcting coordinate anomalies in survey data. Using optical stereo photogrammetry and radar interferometry, remote sensing images and topographic maps of the target area are obtained from multiple angles, and a three-dimensional terrain model is constructed based on the remote sensing images of the target area. The transformation parameters are calculated using the least squares method; Based on pre-selected ground feature points, the remote sensing image and topographic map are registered using the transformation parameters. Geospatial analysis tools were used to identify the correlation between the registered remote sensing images and the survey data; Based on the aforementioned relationships, a geospatial database model is constructed. The geospatial database model is then used to integrate the topographic features, remote sensing image interpretation results, and survey data of the target area to obtain a multi-dimensional dataset. Based on the multi-dimensional dataset, the basic geographic information framework is constructed.

3. The method for recommending route selection schemes for canal projects according to claim 2, characterized in that, The steps for constructing the basic geographic information framework based on the multi-dimensional dataset include: Extract the geological boundaries from the remote sensing image interpretation results, the geological survey points from the survey data, and the profile lines from the topographic features; Based on the profile lines and borehole data, a stratigraphic interface is generated to construct a topographic surface model. The interface morphology of the topographic surface model is then corrected by combining the stratigraphic tonal differences in remote sensing images. A geological body model is constructed based on the geological boundary and the geological exploration points; Based on the terrain surface model and the geological body model, a basic geographic information framework including terrain undulations and underground structures is constructed.

4. The method for recommending a canal engineering route selection scheme according to claim 1, characterized in that, The construction of the historical case knowledge base includes: Obtain a collection of historical canal engineering case studies that have been completed; By employing text mining and image recognition strategies, key information is extracted from case documents and remote sensing images of each historical canal project, resulting in a set of key information. The key information includes at least one of the following: topographic features, geological conditions, route selection scheme, engineering volume, construction difficulties, and environmental factors. Using a case-based reasoning framework, the extracted key information set is integrated into a knowledge base to obtain the historical case knowledge base.

5. The method for recommending a canal engineering route selection scheme according to claim 1, characterized in that, The steps for conducting geological stability assessments of different sub-regions to be assessed using fuzzy logic rules include: For each of the sub-regions to be evaluated, a set of input variables related to geological stability is determined, wherein the input variables include at least one of the following: rock type, seismic wave velocity, groundwater level, and soil moisture content; Using membership functions, the values ​​of the input variables are mapped to their respective fuzzy sets; Based on a pre-defined fuzzy rule base and combined with a fuzzy set of input variables, the fuzzy output of the geological stability of each sub-region to be evaluated is calculated. A defuzzing strategy is employed to convert the fuzzy output into a geological stability level.

6. The method for recommending a canal engineering route selection scheme according to claim 1, characterized in that, Based on the pre-defined set of canal route selection rules, the historical case knowledge base, the basic geographic information framework, the river system transportation demand within the target area, and the geological stability assessment results, the steps for initially formulating N canal route schemes include: Based on the aforementioned set of canal route selection rules, and combined with the geographical conditions and environmental protection requirements of the target area, preliminary route selection guidelines are generated. Using the historical case knowledge base, successful route selection patterns for historical canal projects under conditions similar to the target area are identified through case reasoning. By combining the aforementioned basic geographic information framework and the geological stability assessment results, multi-source data analysis is conducted to identify potential risk points and adjustment space for the canal route; Extract historical freight volume data, shipping demand, water resource allocation targets, and existing transportation network information from the river system's transportation demand to determine the priority of transportation demand for canal routes; Based on the aforementioned route selection guidelines, the successful route selection patterns of historical canal projects, the potential risk points of the canal routes, the adjustment space, and the priority of transportation needs, a heuristic search algorithm is used to initially formulate N canal route schemes.

7. The method for recommending route selection schemes for canal projects according to claim 1, characterized in that, The steps of identifying the matching relationship between each initially proposed canal route and the set of natural resource constraints, and adjusting the canal route, include: Each of the initially proposed canal route schemes is digitized and stored in a geographic information system format; Using the spatial analysis function of a geographic information system, the conflict points between the proposed canal route and the set of natural resource constraints are identified; The identified conflict points are analyzed, and the impact of the conflict points on the canal engineering corresponding to the canal route scheme is evaluated to obtain the evaluation results. Based on the evaluation results, the proposed canal route was adjusted.

8. The method for recommending a canal engineering route selection scheme according to claim 1, characterized in that, The steps for comparing and selecting the recommended canal route using a multi-objective optimization model to determine the recommended canal route include: Obtain the objective index function of the multi-objective optimization model and define the constraints in the multi-objective optimization model; The parameters of each canal route scheme are input into a multi-objective optimization model, which then runs a multi-objective optimization algorithm to iteratively optimize the different canal route schemes. The canal route scheme with the highest comprehensive evaluation score is selected as the recommended canal route scheme.

9. A device for recommending route selection schemes for canal engineering projects, characterized in that, include: The information fusion unit is used to fuse multi-source geographic information of the target area for the proposed canal project site selection, and to construct a basic geographic information framework based on the multi-source fused information. The target area is divided into multiple sub-areas to be evaluated. A geological stability assessment unit is used to assess the geological stability of different sub-regions to be assessed using fuzzy logic rules, and to mark unfavorable geological sections based on the geological stability assessment results. The route planning unit is used to initially plan N canal route schemes based on the pre-planned set of canal route selection rules, the historical case knowledge base, the basic geographic information framework, the river system transportation demand in the target area, and the geological stability assessment results, where N is a positive integer greater than 1. The constraint adjustment unit is used to identify the matching relationship between each initially proposed canal route scheme and the set of natural resource constraints, and to adjust the constraints in the canal route. The recommended route determination unit is used to compare and select from multiple adjusted canal route schemes using a multi-objective optimization model, and determine the recommended canal route scheme.

10. An electronic device, characterized in that, It includes one or more processors and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the recommended method for the canal engineering route selection scheme according to any one of claims 1 to 8.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for recommending the canal engineering route selection scheme as described in any one of claims 1 to 8.

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