Engineering scheme intelligent optimization method and system based on AI generative design

Abstract

The invention relates to the technical field of engineering optimization, in particular to an intelligent engineering scheme optimization method and system based on AI generative design, and the method comprises the steps: obtaining a historical engineering design scheme and engineering design feedback after the scheme demand information sent by a user terminal is detected, performing optimization processing on the historical engineering design schemes according to the scheme demand information and the engineering design feedback to obtain an optimized engineering design scheme set, sending the engineering design scheme set to the user terminal, and receiving a scheme check report sent by the user terminal, judging whether the project design scheme selected by the user terminal exists in the scheme check report, if yes, defining the project design scheme selected by the user terminal as a target project design scheme, and after it is detected that the target project design scheme is started and implemented, carrying out real-time potential scheme optimization on the target project design scheme, and controlling and displaying the optimized target engineering design scheme. The engineering implementation efficiency is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of engineering optimization, in particular to an engineering scheme intelligent optimization method and system based on AI generative design. BACKGROUND

[0002] In today's rapidly developing social and economic environment, various engineering projects are emerging like mushrooms, covering many fields such as construction, transportation, energy, communication and so on. Engineering scheme as the core blueprint of project implementation, its quality directly determines the cost, progress, quality and sustainability of engineering project and other key indicators.

[0003] At present, the traditional AI generative design-based engineering scheme intelligent optimization process is that engineers conceive and optimize design schemes by relying on their own past project experience, professional knowledge and subjective judgment. Although experience can provide an optimization framework for the scheme to a certain extent, when facing complex and variable engineering scenarios, personal experience has limitations and it is difficult to fully consider all potential factors and variables. The experience level and thinking way of different engineers are different, which leads to uneven quality and feasibility of the optimized scheme, increasing the project risk. In addition, during the implementation of the engineering scheme, various unexpected situations and changes will be encountered, such as changes in construction environment, material supply problems, etc. The existing optimization method usually cannot adjust and optimize the scheme in real time during the project implementation stage, and it is difficult to respond to these dynamic changes in time, thereby reducing the efficiency of engineering implementation. SUMMARY

[0004] In order to solve at least one of the above technical problems, the application provides an engineering scheme intelligent optimization method and system based on AI generative design.

[0005] In the first aspect, the application provides an engineering scheme intelligent optimization method based on AI generative design, which adopts the following technical scheme: When detecting the scheme requirement information sent by the user terminal, the historical engineering design schemes and engineering design feedbacks are obtained, the engineering design feedbacks being the construction feedbacks of each engineering design scheme in the construction stage and the application feedbacks corresponding to the application stage of the historical engineering design schemes; According to the scheme requirement information and the engineering design feedbacks, the historical engineering design schemes are subjected to AI optimization processing to obtain an optimized engineering design scheme set; The set of engineering design schemes is sent to the user terminal, and a scheme receipt report sent by the user terminal is received. It is determined whether the engineering design scheme selected by the user terminal exists in the scheme receipt report. If it exists, the engineering design scheme selected by the user terminal is defined as the target engineering design scheme. After the target engineering design scheme is detected to be started and implemented, the target engineering design scheme is optimized in real time, and the optimized target engineering design scheme is displayed.

[0006] By adopting the above technical solution, upon detecting the solution requirement information sent by the user terminal, the system immediately obtains historical engineering design schemes and engineering design feedback. The engineering design feedback covers actual feedback from both the construction and application phases, accurately reflecting the strengths and weaknesses of the schemes in real-world scenarios. The combination of these two provides a comprehensive and accurate data foundation for subsequent optimization. AI optimization of historical engineering design schemes based on solution requirement information and engineering design feedback allows for targeted improvements, removing unreasonable parts, strengthening advantageous aspects, and ultimately obtaining an optimized set of engineering design schemes, effectively improving the quality and applicability of the schemes. After obtaining the optimized set of engineering design schemes, it is sent to the user terminal. Upon receiving the schemes, the user terminal provides a scheme receipt report, and the system uses this report to determine if the user-selected engineering design scheme exists. This process ensures the accuracy and effectiveness of scheme delivery, allowing users to promptly obtain and filter schemes. If a user-selected scheme exists, it is defined as the target engineering design scheme. After detecting the initiation of implementation of the target engineering design scheme, real-time potential scheme optimization is performed, allowing for timely adjustments based on actual conditions, avoiding problems caused by insufficient prior consideration, and ensuring the smooth implementation and efficient execution of the scheme. Implementation is a complex and ever-changing process. Real-time optimization can quickly identify various potential problems, such as changes in the construction environment and fluctuations in material supply, and adjust the details of the plan in a timely manner. The optimized plan is more in line with actual needs and can effectively avoid project delays or quality degradation caused by unforeseen circumstances. The control display shows the optimized target project design plan, enabling construction personnel to obtain the latest and most accurate plan information as soon as possible, and strictly follow the optimized plan to operate, thereby significantly improving the quality and efficiency of the entire project and ensuring that the project can be completed with high quality and high efficiency.

[0007] In one possible implementation, the step of performing AI optimization processing on the historical engineering design schemes based on the scheme requirement information and the engineering design feedback to obtain an optimized set of engineering design schemes includes: An AI solution generation model is constructed, and the historical engineering design scheme is used as a training sample and input into the AI ​​solution generation model for training, so as to obtain the trained AI solution generation model. The solution requirement information is input into the trained AI solution generation model for identification, resulting in a set of engineering design solutions that match the solution requirement information; Based on the engineering design feedback, the corresponding engineering design schemes in the set of engineering design schemes are optimized to obtain an optimized set of engineering design schemes.

[0008] In one possible implementation, real-time potential solution optimization is performed on the target engineering design scheme, including: The project collects the engineering implementation difficulties of the target engineering design scheme, real-time engineering implementation images, and real-time engineering implementation environment. The engineering implementation difficulties refer to the engineering construction situation where the engineering implementation procedures and / or the amount of engineering building materials meet the preset implementation difficulty standards. Based on the engineering implementation images, a three-dimensional model of the engineering project is constructed to obtain the engineering implementation model; Based on the engineering implementation environment and the historical engineering design scheme, determine the material performance data of each engineering material in the real-time project; Based on the engineering implementation model, determine whether the progress of the real-time project involves the difficulties in project implementation. If so, determine the project implementation timeline and project implementation area based on the difficulties in project implementation. Then, divide the project implementation area into multiple sub-regions with different implementation environments based on the project implementation environment. Collect real-time material performance data of different engineering materials in the multiple sub-regions according to the project implementation timeline. Determine whether there is a preset comparison difference between the material performance data and the real-time material performance data. If there is, determine the optimized engineering material corresponding to the material performance data and the implementation area location corresponding to the optimized engineering material. Use the implementation area location as the first screening condition and the optimized engineering material as the second screening condition to screen the optimized engineering design scheme set to obtain the target optimized scheme. Based on the project implementation timeline and the target optimization scheme, the target project design scheme is disassembled and replaced to obtain the optimized target project design scheme.

[0009] In one possible implementation, determining the material performance data of each engineering material in the real-time project based on the engineering implementation environment and the historical engineering design scheme includes: Based on the historical engineering design scheme, determine the material standard performance data of the historical engineering materials under different environments at each construction node of the project. By associating the historical engineering materials with the material performance data, material environmental data is obtained; The material performance data of each engineering material in the real-time project are determined based on the engineering implementation environment and the material environment data.

[0010] In one possible implementation, the step of disassembling and replacing the target engineering design scheme according to the engineering implementation timeline and the target optimization scheme to obtain the optimized target engineering design scheme further includes: The material performance data and the real-time material performance data are imported into the engineering implementation model according to the implementation area location to obtain the engineering data model; The optimized target engineering design scheme is imported into the engineering data model according to the implementation area location to obtain the engineering monitoring model.

[0011] In one possible implementation, determining whether there is a preset comparison difference between the material performance data and the real-time material performance data includes: If there is no preset comparison difference between the material performance data and the real-time material performance data, then the engineering implementation model is extrapolated to the future time period according to the preset engineering implementation schedule and the target engineering design scheme to obtain the future engineering implementation model; Based on the future project implementation model, the difficulties involved in the future project schedule, as well as the future project implementation timeline and the future project implementation area corresponding to the future project difficulties, are determined. Based on the engineering implementation environment, the future engineering implementation area is divided into multiple first engineering sub-regions with different implementation environments. The first material performance data corresponding to the first engineering sub-region is determined according to the future engineering implementation timeline and the material environment data. The future implementation environment of the future implementation project area within the future time period is collected, and the future implementation project area is divided into regions based on the future implementation environment to form multiple second project sub-regions with different implementation environments. The second material performance data corresponding to the second project sub-region is determined according to the future project implementation timeline and the material environment data. Determine whether the first engineering sub-region and the second engineering sub-region are consistent. If they are consistent, calculate the difference between the first material performance data and the second material performance data to obtain the material mutation data. Determine whether the material mutation data conforms to the preset material change floating value. If it does not conform, import the first material performance data and the second material performance data into the future engineering implementation model according to the engineering area location for standardization to obtain the early warning engineering implementation model.

[0012] In one possible implementation, determining whether the first engineering sub-region and the second engineering sub-region are regionally consistent includes: If at least one region is inconsistent between the first engineering sub-region and the second engineering sub-region, then the first abnormal sub-region in the first engineering sub-region and the second abnormal sub-region in the second engineering sub-region will be determined, and the containment and contained relationship between the first abnormal sub-region and the second abnormal sub-region will be determined. When the first abnormal sub-region encompasses the second abnormal sub-region, the remaining abnormal sub-regions located in the first abnormal sub-region but excluding the second abnormal sub-region within the second engineering sub-region are determined. The average material performance data is calculated based on the proportion of the second abnormal sub-region and the remaining abnormal sub-regions within the first abnormal sub-region. The calculated comprehensive material performance data representing the second abnormal sub-region and the remaining abnormal sub-regions is used to update the second material performance data. The difference between the first material performance data and the updated second material performance data is calculated to obtain the material mutation data. When the second abnormal sub-region encompasses the first abnormal sub-region, the remaining abnormal sub-regions located in the second abnormal sub-region outside the first abnormal sub-region within the first engineering sub-region are determined. The average material performance data is calculated according to the proportion of the first abnormal sub-region and the remaining abnormal sub-regions within the second abnormal sub-region. The calculated comprehensive material performance data representing the first abnormal sub-region and the remaining abnormal sub-regions is used to update the first material performance data. The difference between the updated first material performance data and the second material performance data is calculated to obtain the material mutation data.

[0013] Secondly, this application provides an intelligent optimization system for engineering solutions based on AI generative design, which adopts the following technical solution: An intelligent optimization system for engineering solutions based on AI generative design includes: The engineering acquisition module is used to acquire historical engineering design schemes and engineering design feedback after detecting the scheme requirement information sent by the user terminal. The engineering design feedback is the construction feedback of each engineering design scheme in the historical engineering design scheme during the construction phase and the application feedback corresponding to the application phase. An optimization processing module is used to perform AI optimization processing on the historical engineering design schemes based on the scheme requirement information and the engineering design feedback, so as to obtain a set of optimized engineering design schemes. The real-time optimization module is used to send the set of engineering design schemes to the user terminal, receive the scheme receipt report sent by the user terminal, determine whether the engineering design scheme selected by the user terminal exists in the scheme receipt report, if so, define the engineering design scheme selected by the user terminal as the target engineering design scheme, and after detecting that the target engineering design scheme has started implementation, perform real-time potential scheme optimization on the target engineering design scheme, and control the display of the optimized target engineering design scheme.

[0014] In one possible implementation, when the optimization processing module performs AI optimization processing on the historical engineering design schemes based on the scheme requirement information and the engineering design feedback to obtain an optimized set of engineering design schemes, it is specifically used for: An AI solution generation model is constructed, and the historical engineering design scheme is used as a training sample and input into the AI ​​solution generation model for training, so as to obtain the trained AI solution generation model. The solution requirement information is input into the trained AI solution generation model for identification, resulting in a set of engineering design solutions that match the solution requirement information; Based on the engineering design feedback, the corresponding engineering design schemes in the set of engineering design schemes are optimized to obtain an optimized set of engineering design schemes.

[0015] In another possible implementation, the real-time optimization module, when performing real-time potential solution optimization on the target engineering design scheme, is specifically used for: The project collects the engineering implementation difficulties of the target engineering design scheme, real-time engineering implementation images, and real-time engineering implementation environment. The engineering implementation difficulties refer to the engineering construction situation where the engineering implementation procedures and / or the amount of engineering building materials meet the preset implementation difficulty standards. Based on the engineering implementation images, a three-dimensional model of the engineering project is constructed to obtain the engineering implementation model; Based on the engineering implementation environment and the historical engineering design scheme, determine the material performance data of each engineering material in the real-time project; Based on the engineering implementation model, determine whether the progress of the real-time project involves the difficulties in project implementation. If so, determine the project implementation timeline and project implementation area based on the difficulties in project implementation. Then, divide the project implementation area into multiple sub-regions with different implementation environments based on the project implementation environment. Collect real-time material performance data of different engineering materials in the multiple sub-regions according to the project implementation timeline. Determine whether there is a preset comparison difference between the material performance data and the real-time material performance data. If there is, determine the optimized engineering material corresponding to the material performance data and the implementation area location corresponding to the optimized engineering material. Use the implementation area location as the first screening condition and the optimized engineering material as the second screening condition to screen the optimized engineering design scheme set to obtain the target optimized scheme. Based on the project implementation timeline and the target optimization scheme, the target project design scheme is disassembled and replaced to obtain the optimized target project design scheme.

[0016] In another possible implementation, when the real-time optimization module determines the material performance data of each engineering material in the real-time project based on the engineering implementation environment and the historical engineering design scheme, it is specifically used for: Based on the historical engineering design scheme, determine the material standard performance data of the historical engineering materials under different environments at each construction node of the project. By associating the historical engineering materials with the material performance data, material environmental data is obtained; The material performance data of each engineering material in the real-time project are determined based on the engineering implementation environment and the material environment data.

[0017] In another possible implementation, the system further includes: a presentation import module and a scheme import module, wherein, The performance import module is used to import the material performance data and the real-time material performance data into the engineering implementation model according to the implementation area location, so as to obtain the engineering data model. The scheme import module is used to import the optimized target engineering design scheme into the engineering data model according to the implementation area location to obtain the engineering monitoring model.

[0018] In another possible implementation, when the real-time optimization module determines whether there is a preset comparison difference between the material performance data and the real-time material performance data, it is specifically used for: If there is no preset comparison difference between the material performance data and the real-time material performance data, then the engineering implementation model is extrapolated to the future time period according to the preset engineering implementation schedule and the target engineering design scheme to obtain the future engineering implementation model; Based on the future project implementation model, the difficulties involved in the future project schedule, as well as the future project implementation timeline and the future project implementation area corresponding to the future project difficulties, are determined. Based on the engineering implementation environment, the future engineering implementation area is divided into multiple first engineering sub-regions with different implementation environments. The first material performance data corresponding to the first engineering sub-region is determined according to the future engineering implementation timeline and the material environment data. The future implementation environment of the future implementation project area within the future time period is collected, and the future implementation project area is divided into regions based on the future implementation environment to form multiple second project sub-regions with different implementation environments. The second material performance data corresponding to the second project sub-region is determined according to the future project implementation timeline and the material environment data. Determine whether the first engineering sub-region and the second engineering sub-region are consistent. If they are consistent, calculate the difference between the first material performance data and the second material performance data to obtain the material mutation data. Determine whether the material mutation data conforms to the preset material change floating value. If it does not conform, import the first material performance data and the second material performance data into the future engineering implementation model according to the engineering area location for standardization to obtain the early warning engineering implementation model.

[0019] In another possible implementation, when the real-time optimization module determines whether the first engineering sub-region and the second engineering sub-region are regionally consistent, it is specifically used for: If at least one region is inconsistent between the first engineering sub-region and the second engineering sub-region, then the first abnormal sub-region in the first engineering sub-region and the second abnormal sub-region in the second engineering sub-region will be determined, and the containment and contained relationship between the first abnormal sub-region and the second abnormal sub-region will be determined. When the first abnormal sub-region encompasses the second abnormal sub-region, the remaining abnormal sub-regions located in the first abnormal sub-region but excluding the second abnormal sub-region within the second engineering sub-region are determined. The average material performance data is calculated based on the proportion of the second abnormal sub-region and the remaining abnormal sub-regions within the first abnormal sub-region. The calculated comprehensive material performance data representing the second abnormal sub-region and the remaining abnormal sub-regions is used to update the second material performance data. The difference between the first material performance data and the updated second material performance data is calculated to obtain the material mutation data. When the second abnormal sub-region encompasses the first abnormal sub-region, the remaining abnormal sub-regions located in the second abnormal sub-region outside the first abnormal sub-region within the first engineering sub-region are determined. The average material performance data is calculated according to the proportion of the first abnormal sub-region and the remaining abnormal sub-regions within the second abnormal sub-region. The calculated comprehensive material performance data representing the first abnormal sub-region and the remaining abnormal sub-regions is used to update the first material performance data. The difference between the updated first material performance data and the second material performance data is calculated to obtain the material mutation data.

[0020] Thirdly, this application provides an electronic device that adopts the following technical solution: At least one processor; Memory; At least one application, wherein the application is stored in memory and configured to be executed by at least one processor, the application being configured to: execute an AI-based generative design-based intelligent optimization method for engineering schemes as described in any of the first aspects.

[0021] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform an intelligent optimization method for an engineering scheme based on AI generative design, as described in any of the first aspects.

[0022] In summary, this application includes at least one of the following beneficial technical effects: Upon detecting the solution requirement information sent by the user terminal, the system immediately retrieves historical engineering design schemes and engineering design feedback. The engineering design feedback covers actual feedback from both the construction and application phases, accurately reflecting the strengths and weaknesses of the schemes in real-world scenarios. The combination of these two provides a comprehensive and accurate data foundation for subsequent optimization. AI optimization of historical engineering design schemes based on the solution requirement information and engineering design feedback allows for targeted improvements, removing unreasonable parts, strengthening advantageous aspects, and ultimately obtaining an optimized set of engineering design schemes, effectively improving the quality and applicability of the schemes. After obtaining the optimized set of engineering design schemes, it is sent to the user terminal. Upon receiving the schemes, the user terminal sends a scheme receipt report, and the system uses this report to determine if the user-selected engineering design scheme exists. This process ensures the accuracy and effectiveness of scheme delivery, allowing users to promptly obtain and filter schemes. If a user-selected scheme exists, it is defined as the target engineering design scheme. After detecting the initiation of implementation of the target engineering design scheme, real-time potential scheme optimization is performed, allowing for timely adjustments based on actual conditions, avoiding problems caused by insufficient initial considerations, and ensuring the smooth implementation and efficient execution of the scheme. Implementation is a complex and ever-changing process. Real-time optimization can quickly identify various potential problems, such as changes in the construction environment and fluctuations in material supply, and adjust the details of the plan in a timely manner. The optimized plan is more in line with actual needs and can effectively avoid project delays or quality degradation caused by unforeseen circumstances. The control display shows the optimized target project design plan, enabling construction personnel to obtain the latest and most accurate plan information as soon as possible, and strictly follow the optimized plan to operate, thereby significantly improving the quality and efficiency of the entire project and ensuring that the project can be completed with high quality and high efficiency. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating an intelligent optimization method for engineering solutions based on AI generative design, provided in an embodiment of this application.

[0024] Figure 2 This is a schematic diagram of the structure of an intelligent optimization system for engineering solutions based on AI generative design, provided in an embodiment of this application.

[0025] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0026] The following is in conjunction with the appendix Figures 1-3 This application will be described in further detail.

[0027] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they are within the scope of this application.

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0030] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0031] This application provides an intelligent optimization method for engineering solutions based on AI generative design, executed by an electronic device. This electronic device can be an independent physical electronic device, a cluster of multiple physical electronic devices, a distributed system, or a cloud electronic device providing cloud computing services. This application does not impose any limitations on this method. Figure 1 As shown, the method includes: Step S10: After detecting the solution requirement information sent by the user terminal, obtain the historical engineering design scheme and engineering design feedback.

[0032] Among them, engineering design feedback includes construction feedback during the construction phase and application feedback during the application phase for each engineering design scheme in the historical engineering design scheme.

[0033] In the embodiments of this application, the solution requirement information refers to the relevant requirements and conditions of the design solution required for a specific engineering project, conveyed by the user through the user terminal, and is used to express the user's specific expectations for the engineering solution. Historical engineering design solutions refer to various engineering design solutions that have been completed and recorded in the past. These solutions cover engineering projects of different types, scales, and requirements, and are used to represent the planning and design results of previous engineering projects. Construction feedback refers to feedback information regarding various problems and effects that arise during the actual operation of the design solution during the engineering construction process. Application feedback refers to feedback information collected after the engineering design solution is put into practical application, based on its actual use effects and performance.

[0034] In this application, a real-time monitoring mechanism is established. The system is equipped with a dedicated monitoring module that continuously monitors the network connection between the user terminal and the system to ensure timely capture of solution requirement information sent by the user terminal. Upon receiving solution requirement information, the system parses the information and extracts key parameters, such as project type, scale, and requirements, to more accurately filter historical engineering design schemes. Based on the extracted key parameters, a fuzzy search and exact match retrieval operation is performed in the historical engineering design scheme database to obtain potentially relevant historical engineering design schemes. For each obtained historical engineering design scheme, its unique identifier is used to query the engineering design feedback database to obtain corresponding construction and application feedback.

[0035] Step S11: Based on the scheme requirements information and engineering design feedback, perform AI optimization on the historical engineering design schemes to obtain a set of optimized engineering design schemes.

[0036] Specifically, an AI-powered solution generation model is constructed, and historical engineering design schemes are input as training samples into the AI ​​solution generation model for training, resulting in a trained AI solution generation model. Solution requirement information is then input into the trained AI solution generation model for identification, yielding a set of engineering design schemes that match the solution requirement information. Based on engineering design feedback, the corresponding engineering design schemes in the set of engineering design schemes are optimized, resulting in an optimized set of engineering design schemes.

[0037] Based on the acquired historical engineering design schemes, feedback, and scheme requirements, the AI ​​scheme generation model is constructed. When building the model, a suitable deep learning framework and model architecture must be selected according to the specific engineering domain and design requirements. This includes convolutional neural networks (CNNs), recurrent neural networks (RNNs) or their variants, as well as models specifically designed for generation tasks, such as the generator part in generative adversarial networks (GANs). After determining the model architecture, historical engineering design schemes are used as training samples and input into the AI ​​scheme generation model for training. During training, the model continuously learns the features and patterns in historical engineering design schemes, gradually mastering the ability to generate similar engineering design schemes by adjusting its internal parameters. Supervised learning is typically used during training, assigning corresponding labels or targets to each training sample to guide the model's learning direction. After multiple iterations of training, the model's performance on the validation set reaches a preset standard, at which point the trained AI scheme generation model is obtained.

[0038] Next, the solution requirement information is input into the trained AI solution generation model for recognition. The model extracts and analyzes features from the solution requirement information to understand the user's specific needs, including the type, scale, functional requirements, and budget constraints of the engineering project. Based on this understanding, the model generates a set of engineering design solutions that match the solution requirement information from its learned knowledge base. Each solution in this set is a candidate solution that meets the user's needs to a certain extent. The engineering design solutions in the set are then optimized based on engineering design feedback. For each solution in the set, its corresponding historical engineering design solutions are identified, along with the corresponding construction and application feedback. This feedback is analyzed to identify potential problems and shortcomings, such as high construction difficulty, cost overruns, poor performance, or failure to meet actual needs in practical applications. To address these issues, the solutions in the set are optimized in a targeted manner, adjusting parameters, structures, and materials to improve the quality and feasibility of the solutions, ultimately resulting in an optimized set of engineering design solutions.

[0039] Step S12: Send the set of engineering design schemes to the user terminal and receive the scheme receipt report sent by the user terminal. Determine whether there is an engineering design scheme selected by the user terminal in the scheme receipt report. If there is, define the engineering design scheme selected by the user terminal as the target engineering design scheme. After detecting that the target engineering design scheme has started implementation, perform real-time potential scheme optimization on the target engineering design scheme and control the display of the optimized target engineering design scheme.

[0040] In this embodiment, after optimizing the set of engineering design schemes, the system sends the set to the user terminal. This process typically involves using network communication protocols such as HTTP and WebSocket to encapsulate the scheme set in a specific data format (e.g., JSON, XML) and transmit it to the user terminal. Upon receiving the set of engineering design schemes, the user views, analyzes, and compares these schemes, then generates a scheme acceptance report based on their needs and judgment, and sends this report back to the system via the user terminal. Upon receiving the scheme acceptance report, the system parses it to determine if the selected engineering design scheme exists within the report. This determination is usually achieved by searching for specific identifiers, such as scheme number and name, in the scheme acceptance report and matching them with the schemes in the set of engineering design schemes. If a selected engineering design scheme exists, the system defines that scheme as the target engineering design scheme.

[0041] Upon detecting the commencement of the target engineering design scheme, the system activates a real-time potential scheme optimization mechanism. This mechanism continuously collects various data related to the implementation of the target engineering design scheme, including but not limited to construction progress data, on-site environmental monitoring data (such as temperature, humidity, wind speed, etc.), and material supply data. The system analyzes and processes this collected data in real time, using preset algorithms and models, such as machine learning models and optimization algorithms, to predict potential problems and risks, and adjusts and optimizes the target engineering design scheme in real time based on the analysis results. For example, if on-site environmental monitoring data shows that excessively high temperatures may affect material performance, the system will promptly adjust the construction process or replace materials. The optimized target engineering design scheme is promptly fed back to relevant implementation personnel and displayed through user terminals or other display devices, enabling implementation personnel to understand and operate according to the new scheme in a timely manner.

[0042] This application provides an intelligent optimization method for engineering solutions based on AI generative design. Upon detecting solution requirement information sent by a user terminal, the system immediately acquires historical engineering design solutions and engineering design feedback. The engineering design feedback covers actual feedback from both the construction and application phases, accurately reflecting the strengths and weaknesses of the solutions in real-world scenarios. The combination of these two provides a comprehensive and accurate data foundation for subsequent optimization. AI optimization of historical engineering design solutions based on solution requirement information and engineering design feedback allows for targeted improvements, removing unreasonable parts, strengthening advantageous aspects, and ultimately obtaining an optimized set of engineering design solutions, effectively improving the quality and applicability of the solutions. After obtaining the optimized set of engineering design solutions, it is sent to the user terminal. Upon receiving the solutions, the user terminal sends a solution receipt report. The system then uses the report to determine if the user-selected engineering design solution exists. This process ensures the accuracy and effectiveness of solution delivery, allowing users to promptly obtain and filter solutions. If a user-selected solution exists, it is defined as the target engineering design solution. Once the target engineering design scheme is detected and implemented, real-time optimization of potential solutions is performed. This allows for timely adjustments to the scheme based on actual conditions, preventing problems arising from insufficient initial planning and ensuring smooth and efficient implementation. During implementation, situations are complex and constantly changing. Real-time optimization quickly identifies various potential problems, such as changes in the construction environment and fluctuations in material supply, and adjusts scheme details promptly. The optimized scheme better meets actual needs, effectively preventing project delays or quality degradation due to unforeseen circumstances. The optimized target engineering design scheme is displayed and controlled, enabling construction personnel to obtain the latest and most accurate scheme information immediately and operate strictly according to the optimized scheme. This significantly improves the overall quality and efficiency of the project, ensuring its high-quality and efficient completion.

[0043] Furthermore, real-time potential scheme optimization is performed on the target engineering design scheme, including: collecting the engineering implementation difficulties of the target engineering design scheme, real-time engineering implementation images, and real-time engineering implementation environment. The engineering implementation difficulties are the engineering implementation process and / or the engineering construction quantity that meet the preset implementation difficulty standards. Based on the engineering implementation images, a three-dimensional model of the project is constructed to obtain the engineering implementation model. Based on the engineering implementation environment and historical engineering design schemes, the material performance data of each engineering material in the real-time project is determined. Based on the engineering implementation model, it is determined whether the project progress of the real-time project involves engineering implementation difficulties. If so, the engineering implementation timeline and engineering implementation area are determined based on the engineering implementation difficulties. The engineering implementation area is divided into multiple engineering sub-regions with different implementation environments based on the engineering implementation environment. Real-time material performance data of different engineering materials in multiple engineering sub-regions are collected according to the engineering implementation timeline. If there is a pre-defined comparison difference between the material performance data and the real-time material performance data, then the optimized engineering materials corresponding to the material performance data and the implementation area location corresponding to the optimized engineering materials are determined. The implementation area location is used as the first screening condition and the optimized engineering materials are used as the second screening condition to screen the set of optimized engineering design schemes to obtain the target optimized scheme. The target engineering design scheme is disassembled and replaced according to the engineering implementation timeline and the target optimized scheme to obtain the optimized target engineering design scheme.

[0044] In this embodiment, after the target engineering design begins implementation, the system first initiates data acquisition. Using various sensors, cameras, and other devices deployed at the project site, it collects information related to the difficulties in implementing the target engineering design, simultaneously capturing real-time images of the project implementation and collecting various data about the implementation environment. The difficulties in implementation are pre-defined based on the complexity of the implementation procedures and the scale of building materials, according to preset difficulty standards. For example, some procedures may require specialized skills or equipment, or the amount of building materials may exceed a certain threshold for conventional projects. Next, using the acquired images of the implementation, a 3D modeling algorithm is employed to construct a 3D model of the project, resulting in an implementation model that accurately reflects the actual state of the real-time project. Simultaneously, combining historical engineering design schemes and currently collected implementation environment data, data analysis and simulation calculations determine the material performance data for each type of engineering material in the real-time project, reflecting the expected performance of the materials under similar environmental and construction conditions. Then, based on the implementation model, the system analyzes whether the progress of the real-time project involves pre-defined difficulties in implementation. If so, the system further determines the implementation timeline and implementation area based on the difficulties. The project implementation timeline clearly defines the schedule for each construction phase, while the project implementation area delineates the construction scope requiring special attention and handling. Based on the project implementation environment, this area is further subdivided into multiple sub-regions with different environments, such as those based on factors like light intensity and temperature differences. Following the project implementation timeline, real-time material performance data for different engineering materials is collected within each of these sub-regions. After collection, the real-time material performance data is compared with previously determined material performance data to determine if any pre-set comparison discrepancies exist. These pre-set discrepancies are established based on engineering experience and actual needs, such as material strength variations exceeding a certain range or deformation exceeding expectations.

[0045] If pre-defined comparison discrepancies exist, the system will identify optimized engineering materials corresponding to the material performance data—materials that can improve the current material performance and better meet engineering requirements. Simultaneously, it will determine the corresponding implementation area locations for these optimized engineering materials. Then, using the implementation area location as the first screening condition and the optimized engineering materials as the second screening condition, the system will screen the optimized engineering design scheme set to find the most suitable target optimization scheme for the current situation. Based on the engineering implementation timeline and the target optimization scheme, the target engineering design scheme will be disassembled and replaced. The parts of the target engineering design scheme involving relevant engineering sub-regions and engineering materials will be modified and replaced according to the target optimization scheme to obtain the optimized target engineering design scheme, ensuring smoother and more efficient project implementation.

[0046] Specifically, based on the historical engineering design scheme, the material standard performance data of historical engineering materials under different environments are determined for each construction node. The historical engineering materials are correlated with the material performance data to obtain material environment data. Based on the engineering implementation environment and material environment data, the material performance data of each engineering material in the real-time project is determined.

[0047] In the embodiments of this application, construction nodes are used to represent stages or time points that have specific significance and key roles in the implementation of a project. They refer to important links divided according to the construction process and schedule of the project. For example, the completion node of foundation construction and the topping-out node of the main structure in a building project.

[0048] Historical engineering materials refer to all types of building materials selected and actually used in the design schemes of historical engineering projects. These are substances used to construct the physical structure of the project, including various types such as steel, cement, wood, and concrete. Material standard performance data refers to the performance indicators that materials should achieve under specified standard environmental conditions. These are benchmark data used to measure material quality and performance, determined through extensive experimental research and standard specifications. For example, the tensile strength standard value of a certain type of steel specified in a national standard.

[0049] Furthermore, the material performance data and real-time material performance data are imported into the engineering implementation model according to the implementation area location to obtain the engineering data model. The optimized target engineering design scheme is then imported into the engineering data model according to the implementation area location to obtain the engineering monitoring model.

[0050] In this application embodiment, material performance data refers to the various performance index data exhibited by a material under specific conditions. It refers to a set of data obtained through experimental testing, theoretical calculations, etc., reflecting the material's strength, hardness, toughness, corrosion resistance, and other characteristics. For example, in construction engineering, the tensile strength and yield strength of steel are examples of material performance data. Real-time material performance data refers to material performance-related data collected in real time during the engineering implementation process using monitoring equipment such as sensors. It represents the material's actual state and performance at the current moment. For example, concrete temperature data collected in real time by temperature sensors installed in concrete structures. Implementation area location represents the specific geographical location or relative positional relationship of various parts of the project in the actual site. It refers to the range and coordinates of different areas determined according to engineering design drawings and construction plans. For example, in large bridge engineering, the specific location of the bridge piers and the location of different sections of the bridge deck are examples of implementation area locations. The engineering implementation model is a virtual model constructed using computer modeling technology based on engineering design drawings and construction plans. It can simulate the actual structure and construction process of the project and refers to a digital model that can intuitively display the project's appearance, structure, construction process, etc. An engineering data model is a comprehensive model that integrates material performance data and real-time material performance data, imported into the engineering implementation model according to the implementation area location. It represents the data characteristics of the project under different material performance states. An engineering monitoring model is a comprehensive model that, after importing the optimized target engineering design scheme into the engineering data model according to the implementation area location, can monitor the engineering implementation process in real time, predict changes in engineering status, and provide early warning information. It represents the dynamic monitoring system of the project during design and actual construction.

[0051] Furthermore, determining whether there is a pre-defined comparison difference between the material performance data and the real-time material performance data includes: if there is no pre-defined comparison difference between the material performance data and the real-time material performance data, then extrapolating the future time period of the project implementation model according to the pre-defined project implementation schedule and the target project design scheme to obtain the future project implementation model; determining the future project difficulties involved in the project progress of the future project and the future project implementation timeline and future project implementation area corresponding to the future project difficulties according to the future project implementation model; dividing the future project implementation area into multiple first project sub-regions with different implementation environments according to the project implementation environment; determining the first material performance data corresponding to the first project sub-region according to the future project implementation timeline and material environment data; collecting the future implementation environment of the future project implementation area within the future time period; dividing the future project implementation area into multiple second project sub-regions with different implementation environments according to the future project implementation timeline and material environment data; determining the second material performance data corresponding to the second project sub-region according to the future project implementation timeline and material environment data; determining whether the first project sub-region and the second project sub-region are consistent; if they are consistent, calculating the difference between the first material performance data and the second material performance data to obtain material mutation data. Determine whether the material mutation data conforms to the preset material change floating value. If not, import the first material performance data and the second material performance data into the future engineering implementation model according to the engineering area location for standardization, and obtain the early warning engineering implementation model.

[0052] Specifically, if at least one region in the first engineering sub-region and the second engineering sub-region is inconsistent, a first anomalous sub-region in the first engineering sub-region and a second anomalous sub-region in the second engineering sub-region will be identified, and the inclusion and contained relationships between the first and second anomalous sub-regions will be determined. When the first anomalous sub-region includes the second anomalous sub-region, the remaining anomalous sub-regions in the second engineering sub-region that are located within the first anomalous sub-region (excluding the second anomalous sub-region) will be identified. The average material performance data will be calculated based on the proportion of the second anomalous sub-region and the remaining anomalous sub-regions within the first anomalous sub-region. The calculated comprehensive material performance data representing the second anomalous sub-region and the remaining anomalous sub-regions will be used to update the second material performance data. The difference between the first material performance data and the updated second material performance data will be calculated to obtain the material mutation data. When the second abnormal sub-region encompasses the first abnormal sub-region, the remaining abnormal sub-regions located in the second abnormal sub-region but excluding the first abnormal sub-region within the first engineering sub-region are identified. The average material performance data is calculated based on the proportion of the first abnormal sub-region and the remaining abnormal sub-regions within the second abnormal sub-region. The calculated comprehensive material performance data representing the first abnormal sub-region and the remaining abnormal sub-regions is used to update the first material performance data. The difference between the updated first material performance data and the second material performance data is calculated to obtain the material mutation data.

[0053] The following describes an intelligent optimization system for engineering solutions based on AI generative design, provided in an embodiment of this application. The intelligent optimization system for engineering solutions based on AI generative design described below and the intelligent optimization method for engineering solutions based on AI generative design described above can be referred to accordingly. Figure 2 , Figure 2 This is a schematic diagram of the structure of an intelligent optimization system 20 for engineering solutions based on AI generative design, provided in an embodiment of this application, including: The engineering acquisition module 21 is used to acquire historical engineering design schemes and engineering design feedback after detecting the scheme requirement information sent by the user terminal. The engineering design feedback includes the construction feedback of each engineering design scheme in the historical engineering design scheme during the construction phase and the application feedback corresponding to the application phase. The optimization processing module 22 is used to perform AI optimization processing on historical engineering design schemes based on scheme requirement information and engineering design feedback to obtain a set of optimized engineering design schemes. The real-time optimization module 23 is used to send the set of engineering design schemes to the user terminal and receive the scheme receipt report sent by the user terminal. It determines whether there is an engineering design scheme selected by the user terminal in the scheme receipt report. If there is, the engineering design scheme selected by the user terminal is defined as the target engineering design scheme. After detecting that the target engineering design scheme has started implementation, it performs real-time potential scheme optimization on the target engineering design scheme and controls the display of the optimized target engineering design scheme.

[0054] In one possible implementation of this application embodiment, when the optimization processing module 22 performs AI optimization processing on historical engineering design schemes based on scheme requirement information and engineering design feedback to obtain an optimized set of engineering design schemes, it is specifically used for: Construct an AI solution generation model and input historical engineering design schemes as training samples into the AI ​​solution generation model for training to obtain the trained AI solution generation model; The solution requirement information is input into the trained AI solution generation model for recognition, resulting in a set of engineering design solutions that match the solution requirement information. Based on the feedback from the engineering design, the corresponding engineering design schemes in the set of engineering design schemes are optimized to obtain the optimized set of engineering design schemes.

[0055] In another possible implementation of this application embodiment, when the real-time optimization module 23 performs real-time potential scheme optimization on the target engineering design scheme, it is specifically used for: The project collects the engineering implementation difficulties of the target project design scheme, real-time engineering implementation images, and real-time engineering implementation environment. The engineering implementation difficulties are the engineering implementation procedures and / or the amount of engineering building materials that meet the preset implementation difficulty standards. A 3D model of the project is constructed based on the project implementation images to obtain the project implementation model; Based on the engineering implementation environment and historical engineering design schemes, determine the material performance data of each engineering material in the real-time project; Based on the engineering implementation model, determine whether the real-time engineering progress involves engineering implementation difficulties. If so, determine the engineering implementation timeline and engineering implementation area based on the engineering implementation difficulties. Then, divide the engineering implementation area into multiple engineering sub-areas with different implementation environments based on the engineering implementation environment. Collect real-time material performance data of different engineering materials in multiple engineering sub-areas according to the engineering implementation timeline. Determine whether there is a pre-defined comparison difference between the material performance data and the real-time material performance data. If there is, determine the optimized engineering material corresponding to the material performance data and the implementation area location corresponding to the optimized engineering material. Use the implementation area location as the first screening condition and the optimized engineering material as the second screening condition to screen the optimized engineering design scheme set to obtain the target optimized scheme. Based on the project implementation timeline and the target optimization scheme, the target project design scheme is disassembled and replaced to obtain the optimized target project design scheme.

[0056] Another possible implementation in this application embodiment is that, when the real-time optimization module 23 determines the material performance data of each engineering material in the real-time project based on the engineering implementation environment and historical engineering design schemes, it is specifically used for: Based on the historical engineering design scheme, determine the material standard performance data of the historical engineering materials under different environments at each construction node of the project; By correlating historical engineering materials with material performance data, material environmental data can be obtained; Based on the engineering implementation environment and material environment data, determine the material performance data of each engineering material in the real-time engineering process.

[0057] In another possible implementation of this application embodiment, system 20 further includes: a presentation import module and a scheme import module, wherein, The presentation import module is used to import material performance data and real-time material performance data into the engineering implementation model according to the implementation area location, so as to obtain the engineering data model. The scheme import module is used to import the optimized target engineering design scheme into the engineering data model according to the implementation area location, so as to obtain the engineering monitoring model.

[0058] In another possible implementation of this application embodiment, when the real-time optimization module 23 determines whether there is a preset comparison difference between the material performance data and the real-time material performance data, it is specifically used for: If there is no pre-defined comparison difference between the material performance data and the real-time material performance data, then the engineering implementation model is extrapolated to the future time period according to the pre-defined engineering implementation schedule and the target engineering design scheme to obtain the future engineering implementation model. Based on the future project implementation model, determine the challenges involved in the future project's progress, as well as the corresponding timeline and implementation area of ​​the future project. Based on the engineering implementation environment, the future engineering implementation area is divided into multiple first engineering sub-regions with different implementation environments. The first material performance data corresponding to the first engineering sub-region is determined according to the future engineering implementation timeline and material environment data. Collect the future implementation environment of the future project area within a future time period, and divide the future project implementation area into multiple second project sub-regions with different implementation environments based on the future project implementation timeline and material environment data; determine the second material performance data corresponding to the second project sub-regions according to the future project implementation timeline and material environment data. Determine whether the first engineering sub-region and the second engineering sub-region are consistent. If they are consistent, calculate the difference between the first material performance data and the second material performance data to obtain the material mutation data. Determine whether the material mutation data conforms to the preset material change floating value. If not, import the first material performance data and the second material performance data into the future engineering implementation model according to the engineering area location for standardization, and obtain the early warning engineering implementation model.

[0059] Another possible implementation in this application embodiment is that, when the real-time optimization module 23 determines whether the first engineering sub-region and the second engineering sub-region are regionally consistent, it is specifically used for: If at least one region is inconsistent between the first engineering sub-region and the second engineering sub-region, the first abnormal sub-region in the first engineering sub-region and the second abnormal sub-region in the second engineering sub-region will be identified, and the containment and contained relationship between the first abnormal sub-region and the second abnormal sub-region will be determined. When the first abnormal sub-region encompasses the second abnormal sub-region, the remaining abnormal sub-regions located in the first abnormal sub-region but excluding the second abnormal sub-region within the second engineering sub-region are determined. The average material performance data is calculated based on the proportion of the second abnormal sub-region and the remaining abnormal sub-regions within the first abnormal sub-region. The calculated comprehensive material performance data representing the second abnormal sub-region and the remaining abnormal sub-regions is used to update the second material performance data. The difference between the first material performance data and the updated second material performance data is calculated to obtain the material mutation data. When the second abnormal sub-region encompasses the first abnormal sub-region, the remaining abnormal sub-regions located in the second abnormal sub-region but excluding the first abnormal sub-region within the first engineering sub-region are identified. The average material performance data is calculated based on the proportion of the first abnormal sub-region and the remaining abnormal sub-regions within the second abnormal sub-region. The calculated comprehensive material performance data representing the first abnormal sub-region and the remaining abnormal sub-regions is used to update the first material performance data. The difference between the updated first material performance data and the second material performance data is calculated to obtain the material mutation data.

[0060] This application provides an electronic device, such as... Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3The illustrated electronic device 300 includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this electronic device 300 does not constitute a limitation on the embodiments of this application.

[0061] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in connection with the embodiments of this application. Processor 301 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0062] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0063] The memory 303 may be a ROM (Read-Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or it may be an EEPROM (Electrically Erasable Programmable Read-Only Memory), a CD-ROM (Compact Disc Read-Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0064] The memory 303 is used to store application code that executes the scheme of the embodiments of this application, and its execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0065] Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 3 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0066] The following describes a computer-readable storage medium provided by an embodiment of this application. The computer-readable storage medium described below can be referred to in correspondence with the method described above.

[0067] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the AI-based generative design-based intelligent optimization system for engineering solutions as described above.

[0068] Since the embodiments of the computer-readable storage medium portion correspond to the embodiments of the method portion, please refer to the description of the embodiments of the method portion for the embodiments of the computer-readable storage medium portion.

[0069] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0070] The above are only some embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for intelligent optimization of engineering solutions based on AI generative design, characterized in that, include: After detecting the solution requirement information sent by the user terminal, the historical engineering design schemes and engineering design feedback are obtained. The engineering design feedback is the construction feedback of each engineering design scheme in the historical engineering design scheme during the construction phase and the application feedback corresponding to the application phase. Based on the solution requirements information and the engineering design feedback, the historical engineering design solutions are optimized using AI to obtain a set of optimized engineering design solutions. The set of engineering design schemes is sent to the user terminal, and a scheme receipt report sent by the user terminal is received. It is determined whether the engineering design scheme selected by the user terminal exists in the scheme receipt report. If it exists, the engineering design scheme selected by the user terminal is defined as the target engineering design scheme. After the target engineering design scheme is detected to be started and implemented, the target engineering design scheme is optimized in real time, and the optimized target engineering design scheme is displayed.

2. The intelligent optimization method for engineering solutions based on AI generative design according to claim 1, characterized in that, The AI ​​optimization process is performed on the historical engineering design schemes based on the scheme requirements information and the engineering design feedback to obtain an optimized set of engineering design schemes, including: An AI solution generation model is constructed, and the historical engineering design scheme is used as a training sample and input into the AI ​​solution generation model for training, so as to obtain the trained AI solution generation model. The solution requirement information is input into the trained AI solution generation model for identification, resulting in a set of engineering design solutions that match the solution requirement information; Based on the engineering design feedback, the corresponding engineering design schemes in the set of engineering design schemes are optimized to obtain an optimized set of engineering design schemes.

3. The intelligent optimization method for engineering solutions based on AI generative design according to claim 1, characterized in that, The real-time potential solution optimization of the target engineering design scheme includes: The project collects the engineering implementation difficulties of the target engineering design scheme, real-time engineering implementation images, and real-time engineering implementation environment. The engineering implementation difficulties refer to the engineering construction situation where the engineering implementation procedures and / or the amount of engineering building materials meet the preset implementation difficulty standards. Based on the engineering implementation images, a three-dimensional model of the engineering project is constructed to obtain the engineering implementation model; Based on the engineering implementation environment and the historical engineering design scheme, determine the material performance data of each engineering material in the real-time project; Based on the engineering implementation model, determine whether the progress of the real-time project involves the difficulties in project implementation. If so, determine the project implementation timeline and project implementation area based on the difficulties in project implementation. Then, divide the project implementation area into multiple sub-regions with different implementation environments based on the project implementation environment. Collect real-time material performance data of different engineering materials in the multiple sub-regions according to the project implementation timeline. Determine whether there is a preset comparison difference between the material performance data and the real-time material performance data. If there is, determine the optimized engineering material corresponding to the material performance data and the implementation area location corresponding to the optimized engineering material. Use the implementation area location as the first screening condition and the optimized engineering material as the second screening condition to screen the optimized engineering design scheme set to obtain the target optimized scheme. Based on the project implementation timeline and the target optimization scheme, the target project design scheme is disassembled and replaced to obtain the optimized target project design scheme.

4. The intelligent optimization method for engineering solutions based on AI generative design according to claim 3, characterized in that, The determination of material performance data for each engineering material in the real-time project based on the engineering implementation environment and the historical engineering design scheme includes: Based on the historical engineering design scheme, determine the material standard performance data of the historical engineering materials under different environments at each construction node of the project. By associating the historical engineering materials with the material performance data, material environmental data is obtained; The material performance data of each engineering material in the real-time project are determined based on the engineering implementation environment and the material environment data.

5. The intelligent optimization method for engineering solutions based on AI generative design according to claim 4, characterized in that, The step of disassembling and replacing the target engineering design scheme according to the project implementation timeline and the target optimization scheme to obtain the optimized target engineering design scheme further includes: The material performance data and the real-time material performance data are imported into the engineering implementation model according to the implementation area location to obtain the engineering data model; The optimized target engineering design scheme is imported into the engineering data model according to the implementation area location to obtain the engineering monitoring model.

6. The intelligent optimization method for engineering solutions based on AI generative design according to claim 4, characterized in that, The step of determining whether there is a preset comparison difference between the material performance data and the real-time material performance data includes: If there is no preset comparison difference between the material performance data and the real-time material performance data, then the engineering implementation model is extrapolated to the future time period according to the preset engineering implementation schedule and the target engineering design scheme to obtain the future engineering implementation model; Based on the future project implementation model, the difficulties involved in the future project schedule, as well as the future project implementation timeline and the future project implementation area corresponding to the future project difficulties, are determined. Based on the engineering implementation environment, the future engineering implementation area is divided into multiple first engineering sub-regions with different implementation environments. The first material performance data corresponding to the first engineering sub-region is determined according to the future engineering implementation timeline and the material environment data. The future implementation environment of the future implementation project area within the future time period is collected, and the future implementation project area is divided into regions based on the future implementation environment to form multiple second project sub-regions with different implementation environments. The second material performance data corresponding to the second project sub-region is determined according to the future project implementation timeline and the material environment data. Determine whether the first engineering sub-region and the second engineering sub-region are consistent. If they are consistent, calculate the difference between the first material performance data and the second material performance data to obtain the material mutation data. Determine whether the material mutation data conforms to the preset material change floating value. If it does not conform, import the first material performance data and the second material performance data into the future engineering implementation model according to the engineering area location for standardization to obtain the early warning engineering implementation model.

7. The intelligent optimization method for engineering solutions based on AI generative design according to claim 6, characterized in that, The step of determining whether the first engineering sub-region and the second engineering sub-region are regionally consistent includes: If at least one region is inconsistent between the first engineering sub-region and the second engineering sub-region, then the first abnormal sub-region in the first engineering sub-region and the second abnormal sub-region in the second engineering sub-region will be determined, and the containment and contained relationship between the first abnormal sub-region and the second abnormal sub-region will be determined. When the first abnormal sub-region encompasses the second abnormal sub-region, the remaining abnormal sub-regions located in the first abnormal sub-region but excluding the second abnormal sub-region within the second engineering sub-region are determined. The average material performance data is calculated based on the proportion of the second abnormal sub-region and the remaining abnormal sub-regions within the first abnormal sub-region. The calculated comprehensive material performance data representing the second abnormal sub-region and the remaining abnormal sub-regions is used to update the second material performance data. The difference between the first material performance data and the updated second material performance data is calculated to obtain the material mutation data. When the second abnormal sub-region encompasses the first abnormal sub-region, the remaining abnormal sub-regions located in the second abnormal sub-region outside the first abnormal sub-region within the first engineering sub-region are determined. The average material performance data is calculated according to the proportion of the first abnormal sub-region and the remaining abnormal sub-regions within the second abnormal sub-region. The calculated comprehensive material performance data representing the first abnormal sub-region and the remaining abnormal sub-regions is used to update the first material performance data. The difference between the updated first material performance data and the second material performance data is calculated to obtain the material mutation data.

8. An intelligent optimization system for engineering solutions based on AI generative design, characterized in that, include: The engineering acquisition module is used to acquire historical engineering design schemes and engineering design feedback after detecting the scheme requirement information sent by the user terminal. The engineering design feedback is the construction feedback of each engineering design scheme in the historical engineering design scheme during the construction phase and the application feedback corresponding to the application phase. An optimization processing module is used to perform AI optimization processing on the historical engineering design schemes based on the scheme requirement information and the engineering design feedback, so as to obtain a set of optimized engineering design schemes. The real-time optimization module is used to send the set of engineering design schemes to the user terminal, receive the scheme receipt report sent by the user terminal, determine whether the engineering design scheme selected by the user terminal exists in the scheme receipt report, if so, define the engineering design scheme selected by the user terminal as the target engineering design scheme, and after detecting that the target engineering design scheme has started implementation, perform real-time potential scheme optimization on the target engineering design scheme, and control the display of the optimized target engineering design scheme.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute an intelligent optimization method for an engineering scheme based on AI generative design, as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, include: The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1-7, which is an intelligent optimization method for engineering solutions based on AI generative design.

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