A method and system for intelligent arrangement optimization of stay cables for a cable-stayed bridge

Abstract

The application discloses a cable-stayed bridge cable intelligent arrangement optimization method and system, which comprises the following steps: step 101, obtaining a cable arrangement scheme of a cable-stayed bridge and extracting a first feature vector group of the cable-stayed bridge; step 102, simulating the cable arrangement scheme by using finite elements, establishing a finite element model of a main beam, a cable and an anchoring system of the cable-stayed bridge, and extracting a second feature vector group of the cable-stayed bridge in the cable arrangement scheme; step 103, establishing a symbolic rule, mapping the second feature vector group into a state symbol string of the cable arrangement scheme, and combining the first feature vector group to calculate a structure performance comprehensive index of the cable arrangement scheme; and step 104, evolving and updating the first feature vector group to obtain a new first feature vector group, and finding out an optimal new first feature vector group as final cable-stayed bridge arrangement parameters of the cable arrangement scheme.

Description

Technical Field

[0001] This invention belongs to the field of cable-stayed bridge optimization technology, and more specifically, relates to a method and system for intelligent cable arrangement optimization of cable-stayed bridges. Background Technology

[0002] Cable-stayed bridges are a common type of long-span bridge structure, widely used in transportation engineering projects across rivers, seas, valleys, and other complex terrains. Their basic structure consists of a main girder, towers (or pylons), and numerous stay cables. One end of each stay cable is anchored to the top of the tower, and the other end connects to the main girder. The cables transfer the load from the bridge deck to the pylon, and then from the pylon to the piers and foundation. Compared to suspension bridges, cable-stayed bridges offer greater flexibility in structural layout. The number of pylons can be designed according to the terrain and span. They also have higher deck stiffness and superior wind resistance, making them suitable for medium to large spans (generally 200 to 1000 meters). Common stay cable arrangements include single-plane, double-plane, fan-shaped, and parallel arrangements, selected based on a balance between aesthetics and load-bearing performance. In recent years, with the development of high-strength materials and construction techniques, cable-stayed bridges have achieved more complex geometric forms and ultra-long spans, becoming one of the iconic structural forms embodying the integration of modern engineering technology and urban landscape.

[0003] Currently, the arrangement of the stay cables is mainly adjusted through simulation, relying heavily on manual parameter adjustments, which leads to low efficiency. Summary of the Invention

[0004] To address the above technical problems, this invention proposes an intelligent cable arrangement optimization method for cable-stayed bridges, comprising:

[0005] Step 101: Obtain the cable-stayed bridge cable arrangement scheme and extract the first feature vector group of the cable-stayed bridge;

[0006] Step 102: Simulate the cable-stayed bridge arrangement scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge arrangement scheme;

[0007] Step 103: Establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme;

[0008] Step 104: Evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters of the cable-stayed bridge layout scheme.

[0009] Furthermore, mapping the second feature vector group to a state symbol string of the cable-stayed bridge arrangement scheme also includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

[0010] Furthermore, the feature vectors in the first feature vector group and the second feature vector group are normalized.

[0011] Furthermore, combining the first set of feature vectors, the comprehensive structural performance index of the cable-stayed bridge arrangement scheme is calculated as follows:

[0012] ,

[0013] in, For the second feature vector group The corresponding comprehensive structural performance index, For the first The weights of the structural performance index values ​​corresponding to each feature vector For the second feature vector group The Middle The structural performance index values ​​corresponding to each feature vector. The weight of the sign penalty value, For the second feature vector group Corresponding state symbol string The symbolic penalty value.

[0014] Furthermore, with the second feature vector group Corresponding state symbol string Symbolic penalty value include:

[0015] ,

[0016] in, For the first The weight of each state symbol, State symbol string The Middle A state symbol, The set of high-risk state symbol strings, This is an indicator function.

[0017] Furthermore, the evolutionary update of the first feature vector group includes:

[0018] ,

[0019] in, For the first feature vector group, the first... 1 eigenvector The first feature vector group is the first eigenvector. 1 eigenvector For the perturbation step size, The weights are Gaussian random perturbations. For Gaussian random perturbation, The weights for remembering the bias values, For the first eigenvectors The biased guiding factor. For the first eigenvectors A feasibility indicator function within the corresponding constraint domain.

[0020] Furthermore, finding the optimal new first eigenvector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme includes: obtaining a new first eigenvector group for each evolution update, repeating steps 102 to 104, calculating the comprehensive structural performance index of each new first eigenvector group, and finding the new first eigenvector group corresponding to the largest comprehensive structural performance index as the optimal new first eigenvector group.

[0021] Furthermore, iterate through all eigenvectors in the first eigenvector group, and perform evolution and update on each eigenvector. After all eigenvectors have completed evolution and update, a new first eigenvector group is formed.

[0022] This invention also proposes an intelligent cable arrangement optimization system for cable-stayed bridges, comprising:

[0023] The module for extracting the first feature vector group is used to obtain the cable arrangement scheme of the cable-stayed bridge and extract the first feature vector group of the cable-stayed bridge.

[0024] The module for extracting the second feature vector group is used to simulate the cable-stayed bridge layout scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge layout scheme;

[0025] The mapping module is used to establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme.

[0026] The optimization module is used to evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme.

[0027] Furthermore, mapping the second feature vector group to a state symbol string of the cable-stayed bridge arrangement scheme also includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

[0028] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0029] The present invention, through the above technical solutions, can accurately and intelligently complete the optimized arrangement of stay cables, thereby improving design efficiency. Attached Figure Description

[0030] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention;

[0031] Figure 2 This is a system structure diagram of Embodiment 2 of the present invention. Detailed Implementation

[0032] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0033] The method provided by this invention can be implemented in a terminal environment that may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0034] A processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the terminal, and performs various functions and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and by calling data stored in the storage medium.

[0035] Storage media can include random access memory (RAM) or read-only memory (ROM). Storage media can be used to store instructions, programs, code, code sets, or instructions.

[0036] The display screen is used to show the user interface of each application.

[0037] In addition, those skilled in the art will understand that the above-described structure of the terminal does not constitute a limitation on the terminal. The terminal may include more or fewer components, or combine certain components, or have different component arrangements. For example, the terminal may also include radio frequency circuits, input units, sensors, audio circuits, power supplies, and other components, which will not be described in detail here.

[0038] Example 1

[0039] like Figure 1 This embodiment proposes a method for intelligent arrangement optimization of stay cables in cable-stayed bridges, including:

[0040] Step 101: Obtain the cable-stayed bridge cable arrangement scheme and extract the first feature vector group of the cable-stayed bridge;

[0041] ,

[0042] Step 102: Simulate the cable-stayed bridge arrangement scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge arrangement scheme;

[0043] For example, the second set of eigenvectors extracted by the finite element method can be represented by the eigenvectors shown in the table below:

[0044] ,

[0045] Step 103: Establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme;

[0046] Specifically, mapping the second feature vector group to a state symbol string of the cable-stayed bridge arrangement scheme further includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

[0047] Regarding high-risk state symbol strings, for example, if > Then, "excessive deflection" indicates insufficient stiffness of the main beam and unsafe vertical load-bearing capacity; if >0.85⋅ Then, the "critical deflection" indicates that the deflection is approaching the specification limit, requiring increased stiffness configuration; if <0.2⋅ Then, "excessive stiffness": the main beam is relatively stiff, and material optimization can be considered; if >0.95⋅ Then, "ultimate overstretching" means approaching material failure, which is dangerous; if... >0.9⋅ Then, "over-tension": approaching the design limit, further increases are not recommended; if <0.3⋅ Then, "low utilization": low cable utilization rate and structural redundancy; if >0.4⋅ Then, "excessive tension difference" means that the cables are unevenly distributed, resulting in uneven stress on the main beam; if >1.2⋅ Then, "tension concentration"—the accumulation of cable forces in a localized area—may lead to structural eccentric loading; if <0.5⋅ Then, "sparse tension" means the cables are loose and unable to effectively support the main beam; if - If the angle is greater than 15 degrees, then the "angle deviation is large": the construction difficulty increases and it may affect the stress performance;

[0048] If a cable-stayed bridge layout scheme includes =0.92>0.75= , =970>0.95⋅1000( ), =460>0.4⋅1000( ), =1.3⋅ Then, the high-risk state symbol string is {"excessive deflection", "excessive over-tension", "excessive tension difference", "tension concentration"}.

[0049] Specifically, the feature vectors in the first feature vector group and the second feature vector group are normalized.

[0050] Specifically, based on the first feature vector set, the comprehensive structural performance index of the cable-stayed bridge arrangement scheme is calculated as follows:

[0051] ,

[0052] in, For the second feature vector group The corresponding comprehensive structural performance index, For the first The weights of the structural performance index values ​​corresponding to each feature vector For the second feature vector group The Middle The structural performance index values ​​corresponding to each feature vector. The weight of the sign penalty value, For the second feature vector group Corresponding state symbol string The symbolic penalty value.

[0053] Specifically, with the second feature vector group Corresponding state symbol string Symbolic penalty value include:

[0054] ,

[0055] in, For the first The weight of each state symbol, State symbol string The Middle A state symbol, The set of high-risk state symbol strings, This is an indicator function.

[0056] Step 104: Evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters of the cable-stayed bridge layout scheme.

[0057] Specifically, the evolution and update of the first feature vector group includes:

[0058] ,

[0059] in, For the first feature vector group, the first... 1 eigenvector The first feature vector group is the first eigenvector. 1 eigenvector For the perturbation step size, The weights are Gaussian random perturbations. For Gaussian random perturbation, The weights for remembering the bias values, For the first eigenvectors The biased guiding factor. For the first eigenvectors A feasibility indicator function within the corresponding constraint domain.

[0060] Preferred, Used to guide the first during the evolutionary update process eigenvectors Evolution towards regions that have historically performed better typically takes values ​​in the range [−1,+1]. For example, in the cable arrangement design of a cable-stayed bridge, if… Indicates the location of the anchorage point of the stay cable on the main beam. A value >0 indicates that moving the anchoring point to the right (closer to the main tower or the fulcrum) has historically been beneficial in improving target performance, such as reducing deflection or tension fluctuations; if If <0, then conversely, it means shifting to the left is more advantageous; if Approaching ±1, representing the past... eigenvectors Changes in this area have a significant impact on the outcome (“highly sensitive area”); if ≈ 0, representing unbiasedness, indicating that the evolutionary update is for the th eigenvectors No significant effect, classified as "neutral".

[0061] calculate The formula is shown below:

[0062] ,

[0063] in, In order to be with the first eigenvectors The gradient of the corresponding sign penalty value.

[0064] For example, if >0 indicates an increase If it increases risk, then we should evolve in the opposite direction; if... <0 indicates an increase If it reduces risk, then the current direction is reasonable; if it is close to 0, it means... If the impact on current risks is small, then no adjustment is necessary or only a small adjustment can be made.

[0065] Preferably, the gradient can be obtained using the following approximate numerical derivative method:

[0066] ,

[0067] in, For the first eigenvectors The change in quantity.

[0068] Specifically, finding the optimal new first eigenvector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme includes: obtaining a new first eigenvector group for each evolution update, repeating steps 102 to 104, calculating the comprehensive structural performance index of each new first eigenvector group, and finding the new first eigenvector group corresponding to the largest comprehensive structural performance index as the optimal new first eigenvector group.

[0069] Specifically, iterate through all feature vectors in the first feature vector group, and perform evolution and update on each feature vector. After all feature vectors have completed evolution and update, a new first feature vector group is formed.

[0070] Example 2

[0071] like Figure 2 As shown, this embodiment proposes an intelligent cable arrangement optimization system for cable-stayed bridges, including:

[0072] The module for extracting the first feature vector group is used to obtain the cable arrangement scheme of the cable-stayed bridge and extract the first feature vector group of the cable-stayed bridge.

[0073] The module for extracting the second feature vector group is used to simulate the cable-stayed bridge layout scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge layout scheme;

[0074] The mapping module is used to establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme.

[0075] Specifically, mapping the second feature vector group to a state symbol string of the cable-stayed bridge arrangement scheme further includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

[0076] Specifically, the feature vectors in the first feature vector group and the second feature vector group are normalized.

[0077] Specifically, based on the first feature vector set, the comprehensive structural performance index of the cable-stayed bridge arrangement scheme is calculated as follows:

[0078] ,

[0079] in, For the second feature vector group The corresponding comprehensive structural performance index, For the first The weights of the structural performance index values ​​corresponding to each feature vector For the second feature vector group The Middle The structural performance index values ​​corresponding to each feature vector. The weight of the sign penalty value, For the second feature vector group Corresponding state symbol string The symbolic penalty value.

[0080] Specifically, with the second feature vector group Corresponding state symbol string Symbolic penalty value include:

[0081] ,

[0082] in, For the first The weight of each state symbol, State symbol string The Middle A state symbol, The set of high-risk state symbol strings, This is an indicator function.

[0083] The optimization module is used to evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme.

[0084] Specifically, the evolution and update of the first feature vector group includes:

[0085] ,

[0086] in, For the first feature vector group, the first... 1 eigenvector The first feature vector group is the first eigenvector. 1 eigenvector For the perturbation step size, The weights are Gaussian random perturbations. For Gaussian random perturbation, The weights for remembering the bias values, For the first eigenvectors The biased guiding factor. For the first eigenvectors A feasibility indicator function within the corresponding constraint domain.

[0087] Specifically, finding the optimal new first eigenvector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme includes: obtaining a new first eigenvector group for each evolution update, repeating steps 102 to 104, calculating the comprehensive structural performance index of each new first eigenvector group, and finding the new first eigenvector group corresponding to the largest comprehensive structural performance index as the optimal new first eigenvector group.

[0088] Specifically, iterate through all feature vectors in the first feature vector group, and perform evolution and update on each feature vector. After all feature vectors have completed evolution and update, a new first feature vector group is formed.

[0089] Example 3

[0090] This invention also proposes a storage medium storing multiple instructions for implementing the aforementioned intelligent cable arrangement optimization method for cable-stayed bridges.

[0091] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0092] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following method steps: Step 101, obtaining the cable arrangement scheme of the cable-stayed bridge and extracting the first feature vector group of the cable-stayed bridge;

[0093] Step 102: Simulate the cable-stayed bridge arrangement scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge arrangement scheme;

[0094] Step 103: Establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme;

[0095] Specifically, mapping the second feature vector group to a state symbol string of the cable-stayed bridge arrangement scheme further includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

[0096] Specifically, the feature vectors in the first feature vector group and the second feature vector group are normalized.

[0097] Specifically, based on the first feature vector set, the comprehensive structural performance index of the cable-stayed bridge arrangement scheme is calculated as follows:

[0098] ,

[0099] in, For the second feature vector group The corresponding comprehensive structural performance index, For the first The weights of the structural performance index values ​​corresponding to each feature vector For the second feature vector group The Middle The structural performance index values ​​corresponding to each feature vector. The weight of the sign penalty value, For the second feature vector group Corresponding state symbol string The symbolic penalty value.

[0100] Specifically, with the second feature vector group Corresponding state symbol string Symbolic penalty value include:

[0101] ,

[0102] in, For the first The weight of each state symbol, State symbol string The Middle A state symbol, The set of high-risk state symbol strings, This is an indicator function.

[0103] Step 104: Evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters of the cable-stayed bridge layout scheme.

[0104] Specifically, the evolution and update of the first feature vector group includes:

[0105] ,

[0106] in, For the first feature vector group, the first... 1 eigenvector The first feature vector group is the first eigenvector. 1 eigenvector For the perturbation step size, The weights are Gaussian random perturbations. For Gaussian random perturbation, The weights for remembering the bias values, For the first eigenvectors The biased guiding factor. For the first eigenvectors A feasibility indicator function within the corresponding constraint domain.

[0107] Specifically, finding the optimal new first eigenvector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme includes: obtaining a new first eigenvector group for each evolution update, repeating steps 102 to 104, calculating the comprehensive structural performance index of each new first eigenvector group, and finding the new first eigenvector group corresponding to the largest comprehensive structural performance index as the optimal new first eigenvector group.

[0108] Specifically, iterate through all feature vectors in the first feature vector group, and perform evolution and update on each feature vector. After all feature vectors have completed evolution and update, a new first feature vector group is formed.

[0109] Example 4

[0110] This invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the aforementioned intelligent cable arrangement optimization method for cable-stayed bridges.

[0111] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0112] The storage medium can be used to store software programs and modules, such as the intelligent cable arrangement optimization method for cable-stayed bridges in this embodiment of the invention. The corresponding program instructions / modules are executed by the processor through running the software programs and modules stored in the storage medium, thereby performing various functional applications and data processing, thus realizing the aforementioned intelligent cable arrangement optimization method for cable-stayed bridges. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0113] The processor can call the information and application stored in the storage medium through the transmission system to perform the following steps: Step 101, obtain the cable arrangement scheme of the cable-stayed bridge and extract the first feature vector group of the cable-stayed bridge;

[0114] Step 102: Simulate the cable-stayed bridge arrangement scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge arrangement scheme;

[0115] Step 103: Establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme;

[0116] Specifically, mapping the second feature vector group to a state symbol string of the cable-stayed bridge arrangement scheme further includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

[0117] Specifically, the feature vectors in the first feature vector group and the second feature vector group are normalized.

[0118] Specifically, based on the first feature vector set, the comprehensive structural performance index of the cable-stayed bridge arrangement scheme is calculated as follows:

[0119] ,

[0120] in, For the second feature vector group The corresponding comprehensive structural performance index, For the first The weights of the structural performance index values ​​corresponding to each feature vector For the second feature vector group The Middle The structural performance index values ​​corresponding to each feature vector. The weight of the sign penalty value, For the second feature vector group Corresponding state symbol string The symbolic penalty value.

[0121] Specifically, with the second feature vector group Corresponding state symbol string Symbolic penalty value include:

[0122] ,

[0123] in, For the first The weight of each state symbol, State symbol string The Middle A state symbol, The set of high-risk state symbol strings, This is an indicator function.

[0124] Step 104: Evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters of the cable-stayed bridge layout scheme.

[0125] Specifically, the evolution and update of the first feature vector group includes:

[0126] ,

[0127] in, For the first feature vector group, the first... 1 eigenvector The first feature vector group is the first eigenvector. 1 eigenvector For the perturbation step size, The weights are Gaussian random perturbations. For Gaussian random perturbation, The weights for remembering the bias values, For the first eigenvectors The biased guiding factor. For the first eigenvectors A feasibility indicator function within the corresponding constraint domain.

[0128] Specifically, finding the optimal new first eigenvector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme includes: obtaining a new first eigenvector group for each evolution update, repeating steps 102 to 104, calculating the comprehensive structural performance index of each new first eigenvector group, and finding the new first eigenvector group corresponding to the largest comprehensive structural performance index as the optimal new first eigenvector group.

[0129] Specifically, iterate through all feature vectors in the first feature vector group, and perform evolution and update on each feature vector. After all feature vectors have completed evolution and update, a new first feature vector group is formed.

[0130] 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.

[0131] 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.

[0132] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0133] 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 network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0134] 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.

[0135] 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: USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0136] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for intelligent arrangement optimization of stay cables in cable-stayed bridges, characterized in that, include: Step 101: Obtain the cable-stayed bridge cable arrangement scheme and extract the first feature vector group of the cable-stayed bridge; Step 102: Simulate the cable-stayed bridge arrangement scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge arrangement scheme; Step 103: Establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme; Step 104: Evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters of the cable-stayed bridge layout scheme.

2. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 1, characterized in that, Mapping the second feature vector group to a state symbol string for a cable-stayed bridge arrangement scheme further includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

3. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 2, characterized in that, The feature vectors in the first feature vector group and the second feature vector group are normalized.

4. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 3, characterized in that, Combining the first set of feature vectors, the comprehensive structural performance index of the cable-stayed cable arrangement scheme is calculated as follows: ， in, For the second feature vector group The corresponding comprehensive structural performance index, For the first The weights of the structural performance index values ​​corresponding to each feature vector For the second feature vector group The Middle The structural performance index values ​​corresponding to each feature vector. The weight of the sign penalty value, For the second feature vector group Corresponding state symbol string The symbolic penalty value.

5. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 4, characterized in that, With the second feature vector group Corresponding state symbol string Symbolic penalty value include: ， in, For the first The weight of each state symbol, State symbol string The Middle A state symbol, The set of high-risk state symbol strings, This is an indicator function.

6. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 1, characterized in that, The evolutionary update of the first feature vector group includes: ， in, For the first feature vector group, the first... 1 eigenvector The first feature vector group is the first eigenvector. 1 eigenvector For the perturbation step size, The weights are Gaussian random perturbations. For Gaussian random perturbation, The weights for remembering the bias values, For the first eigenvectors The biased guiding factor. For the first eigenvectors A feasibility indicator function within the corresponding constraint domain.

7. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 1, characterized in that, Finding the optimal new first eigenvector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme includes: obtaining a new first eigenvector group for each evolution update, repeating steps 102 to 104, calculating the comprehensive structural performance index of each new first eigenvector group, and finding the new first eigenvector group corresponding to the largest comprehensive structural performance index as the optimal new first eigenvector group.

8. The intelligent cable arrangement optimization method for cable-stayed bridges as described in claim 7, characterized in that, Iterate through all eigenvectors in the first eigenvector group, and perform evolution and update on each eigenvector. After all eigenvectors have been evolved and updated, a new first eigenvector group is formed.

9. A smart cable arrangement optimization system for cable-stayed bridges, characterized in that, include: The module for extracting the first feature vector group is used to obtain the cable arrangement scheme of the cable-stayed bridge and extract the first feature vector group of the cable-stayed bridge. The module for extracting the second feature vector group is used to simulate the cable-stayed bridge layout scheme using finite element method, establish a finite element model of the main beam, cable-stayed bridge and anchorage system, and extract the second feature vector group of the cable-stayed bridge in the cable-stayed bridge layout scheme; The mapping module is used to establish symbolization rules, map the second feature vector group to the state symbol string of the cable-stayed arrangement scheme, and combine it with the first feature vector group to calculate the comprehensive structural performance index of the cable-stayed arrangement scheme. The optimization module is used to evolve and update the first feature vector group to obtain a new first feature vector group, and find the optimal new first feature vector group as the final cable-stayed bridge layout parameters for the cable arrangement scheme.

10. The intelligent cable arrangement optimization system for cable-stayed bridges as described in claim 9, characterized in that, Mapping the second feature vector group to a state symbol string for a cable-stayed bridge arrangement scheme further includes: setting a threshold corresponding to each feature vector in the second feature vector group, and mapping feature vectors in the second feature vector group that exceed the threshold to a high-risk state symbol string.

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