Building engineering green energy-saving design optimization method and system

Abstract

The invention relates to a building engineering green energy-saving design optimization method and system. The method comprises the steps that a BIM building model and a multi-target optimization model used for reflecting green building evaluation performance indexes are acquired; inputting the structural layout data of the target building and the surrounding buildings into a multi-target optimization model to obtain target building distinguishing information and surrounding building distinguishing information; and comparing the two pieces of distinguishing information to obtain different pieces of distinguishing information, obtaining target building perfection information based on the different pieces of distinguishing information, and designing a new target building BIM model. Through the arrangement, the distinguishing information between the target building and the surrounding buildings is obtained through the BIM building model and the multi-target optimization model, the defect points of the target building and the surrounding buildings can be known according to the distinguishing information, the problem that traditional building design lacks systematic comparative analysis is solved, meanwhile, the trial and error cost is reduced, and the efficiency is improved. The conditions that key differences are masked and information is confused are avoided, and the accuracy of model evaluation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of green buildings, and in particular to a green energy-saving design optimization method and system for a construction project. Background Art

[0002] Green buildings refer to high-quality buildings that save resources, protect the environment, reduce pollution, provide people with healthy, applicable and efficient use space, and maximize the harmonious coexistence of man and nature throughout their life cycle. In the traditional architectural design process, there is often a lack of systematic comparative analysis between the target building and the surrounding buildings. When planning the target building, designers rely more on personal experience and rarely consider its synergy with the surrounding building environment. For example, they only focus on the functional layout of the target building itself, ignoring the interactive impact with surrounding buildings in energy utilization, indoor environmental quality, space utilization efficiency and other aspects.

[0003] At the same time, the existing evaluation methods are relatively simple, making it difficult to conduct a comprehensive and in-depth analysis of the building. There is a lack of accurate and effective tools for the implementation of green building evaluation performance indicators. Although BIM building models have been used to a certain extent, most of them are only used for basic visual display, and their potential in optimization design has not been fully explored. Furthermore, the construction and application of multi-objective optimization models are insufficient. The structural layout data of the target building and the surrounding buildings are not input into the model for independent evaluation, which can easily cause key differences to be covered up and information to be confused. It is impossible to accurately locate the shortcomings of the target building, and it is difficult to provide a strong basis for subsequent design improvements. In summary, there is an urgent need for an innovative method to use BIM models and multi-objective optimization models to work together to comprehensively improve the level of green building design. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and to provide a green energy-saving design optimization method for a construction project, the method comprising:

[0005] Obtain BIM building models and multi-objective optimization models for reflecting green building evaluation performance indicators;

[0006] The BIM building model includes an initially designed target building BIM model and a surrounding building BIM model; and the target building structure layout data and the surrounding building structure layout data are obtained respectively according to the initially designed target building BIM model and the surrounding building BIM model;

[0007] Inputting the target building structure layout data and the surrounding building structure layout data into a multi-objective optimization model, obtaining target building distinction information and surrounding building distinction information output by comparing the target building and the surrounding buildings with the index values ​​in the green building evaluation performance index respectively;

[0008] Based on the target building distinction information and the surrounding building distinction information, the two distinction information are compared to obtain inconsistent distinction information, and the target building completion information is obtained based on the inconsistent distinction information;

[0009] A new target building BIM model is designed based on the target building improvement information.

[0010] Preferably, the multi-objective optimization model for obtaining green building evaluation performance indicators includes:

[0011] Conduct a survey on the surrounding building technologies and select a certain number of green building technologies with the highest frequency of use;

[0012] Based on the selected green building technologies, a green building assessment method is constructed;

[0013] Based on the evaluation data in the green building evaluation method, multiple intelligent evaluation algorithms are used for evaluation, and the average accuracy of each intelligent evaluation algorithm is calculated according to the evaluation results;

[0014] Based on the intelligent evaluation algorithm with the highest average accuracy, the green building evaluation method is optimized and adjusted by constructing a green building professional data set and question-answer pairs;

[0015] Use the optimized and adjusted green building assessment method to assess surrounding buildings and identify surrounding buildings with better scoring results;

[0016] Selecting surrounding buildings with better scoring results as cases, expanding the surrounding building cases, and constructing a multi-objective optimization model;

[0017] The multi-objective optimization model is used to optimize the technical solution of the target building.

[0018] Preferably, the initially designed target building BIM model is the most frequently used surrounding building BIM model.

[0019] Preferably, the redesigning the target building BIM model based on the target building improvement information includes: inputting the target building improvement information into the multi-objective optimization model to obtain a new target building technical solution, and obtaining a new target building BIM model according to the new target building technical solution.

[0020] Preferably, the green building assessment method comprises:

[0021] Determine the comprehensive perfection coefficient of the green building technology based on energy consumption, construction difficulty, environmental adaptability, technical maturity and reliability, and economic investment;

[0022] Calculate the potential improvement scores of various green building technology-related parameters, where the potential improvement refers to the extent to which different performances of the current green building technology can be improved;

[0023] The comprehensive improvement coefficient is used to perform weighted calculation on the score of the space that can be improved for each green building technology to obtain a comprehensive score for the green building technology.

[0024] Preferably, the constructing of a multi-objective optimization model comprises:

[0025] Create a physical model based building model;

[0026] Establishing a neural network model, and using the building model to create a training data set, and training and debugging the neural network model;

[0027] A multi-objective decision support model is established to make optimization decisions in the dimensions of energy consumption, construction difficulty, comfort, technology maturity and cost based on multi-objective decision-making theory, and to generate a comprehensive optimization plan that balances various objectives.

[0028] Preferably, the difference information includes energy consumption differences, environmental impact differences, indoor quality environment differences and building layout differences;

[0029] The inconsistent distinguishing information may include: parts with lower energy efficiency than surrounding buildings, design elements or materials with greater environmental impact, areas or features with poor indoor environmental quality, and unreasonable design of building layout, such as layout that blocks natural lighting or ventilation;

[0030] The target building improvement information includes: Structural adjustment: the structural layout of the building may need to be adjusted to improve energy efficiency or reduce environmental impact; Material selection: Improve the selection of building materials to meet the material standards of green buildings; System optimization: Optimize the building's HVAC, lighting, and water systems to improve overall performance; Landscape and environment: Optimize the interaction between the building and the surrounding environment, including natural ventilation, daylight utilization, and heat island effect mitigation; Sustainability strategies: Implement renewable energy utilization, rainwater collection, and waste management strategies.

[0031] Preferably, the evaluation data in the green building evaluation method is evaluated by using multiple intelligent evaluation algorithms, and the average accuracy of each intelligent evaluation algorithm is calculated according to the evaluation results, specifically including:

[0032] The evaluation data in the green building evaluation method is divided into a training set and a validation set, wherein the training set is used to train the algorithm model so that the algorithm can learn the relationship between the building characteristics and the evaluation results; and the validation set is used to evaluate the performance of the method during the training process to prevent overfitting;

[0033] The multiple intelligent evaluation algorithms include a decision tree algorithm, a SVM algorithm and a neural network algorithm;

[0034] The calculation evaluation index in calculating the average correct rate of each intelligent evaluation algorithm may be accuracy, precision, recall, or precision and recall.

[0035] A green energy-saving design optimization system for a building project, the green energy-saving design optimization system for a building project is used to implement a green energy-saving design optimization method for a building project; comprising:

[0036] A data acquisition module is used to acquire a BIM building model and a multi-objective optimization model for reflecting green building evaluation performance indicators; the BIM building model includes an initially designed target building BIM model and surrounding building BIM models;

[0037] A data acquisition module is used to obtain the target building structure layout data and the surrounding building structure layout data respectively according to the initially designed target building BIM model and the surrounding building BIM model;

[0038] A data processing module, used for inputting the target building structure layout data and the surrounding building structure layout data into a multi-objective optimization model, and obtaining target building distinction information and surrounding building distinction information output by comparing the target building and the surrounding buildings with the index values ​​in the green building evaluation performance index respectively;

[0039] The data output module is used to compare the target building difference information and the surrounding building difference information to obtain inconsistent difference information, obtain the target building improvement information based on the inconsistent difference information; and design a new target building BIM model according to the target building improvement information.

[0040] The beneficial effects of the present invention are as follows: through the BIM building model and the multi-objective optimization model that can be used to reflect the green building evaluation performance indicators, the difference information between the target building and the surrounding buildings can be obtained. According to the difference information, the shortcomings of the target building and the surrounding buildings can be known, and a new BIM model of the target building can be designed according to the shortcomings, which solves the problem of lack of systematic comparative analysis in traditional building design, reduces the cost of trial and error, avoids the situation where key differences are concealed and information is confused, and improves the accuracy of model evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying creative labor, other drawings obtained based on these drawings still belong to the scope of the present invention.

[0042] Figure 1 The invention provides a method for constructing an embodiment of the invention. DETAILED DESCRIPTION

[0043] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

[0044] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are for distinguishing two non-identical entities with the same name or non-identical parameters. It can be seen that "first" and "second" are only for the convenience of expression and should not be understood as limitations on the embodiments of the present invention. The subsequent embodiments will not explain this one by one.

[0045] The directions and positions mentioned in the present invention, such as "upper", "lower", "front", "back", "left", "right", "inside", "outside", "top", "bottom", "side", etc., are only for reference to the directions or positions of the drawings. Therefore, the directions and positions used are for explaining and understanding the present invention, but not for limiting the scope of protection of the present invention.

[0046] like Figure 1 As shown in the figure, in an embodiment of the present invention, a green energy-saving design optimization method for a construction project is provided, and the method comprises:

[0047] Obtain BIM building models and multi-objective optimization models for reflecting green building evaluation performance indicators;

[0048] The BIM building model includes an initially designed target building BIM model and a surrounding building BIM model; and the target building structure layout data and the surrounding building structure layout data are obtained respectively according to the initially designed target building BIM model and the surrounding building BIM model;

[0049] Inputting the target building structure layout data and the surrounding building structure layout data into a multi-objective optimization model, obtaining target building distinction information and surrounding building distinction information output by comparing the target building and the surrounding buildings with the index values ​​in the green building evaluation performance index respectively;

[0050] Based on the target building distinction information and the surrounding building distinction information, the two distinction information are compared to obtain inconsistent distinction information, and the target building completion information is obtained based on the inconsistent distinction information;

[0051] A new target building BIM model is designed based on the target building improvement information.

[0052] It can be understood that the difference information between the target building and the surrounding buildings is obtained through the BIM building model and the multi-objective optimization model that can be used to reflect the green building evaluation performance index. When the target building and the surrounding buildings have consistent distinguishing features with the multi-objective optimization model, it means that the distinguishing features cannot be changed in the actual environment, so the focus should be placed on the inconsistent distinguishing features. According to the difference information, the shortcomings of the target building and the surrounding buildings can be known, and a new target building BIM model can be designed based on the shortcomings;

[0053] By inputting the target building structure layout data and the surrounding building structure layout data into the multi-objective optimization model for evaluation, we can first obtain complete information about their respective green building evaluation performance indicators. This independent evaluation can ensure that the performance of each building in many aspects such as energy utilization, indoor environmental quality, and space utilization efficiency is fully considered under the complex evaluation system of the multi-objective optimization model.

[0054] The multi-objective optimization model is a complex system built based on green building evaluation performance indicators. By inputting the data of the target building and the surrounding buildings separately, the model can better adapt to the data processing of different building types and different design characteristics. This can improve the accuracy of the model in the evaluation process, focus on key differences and avoid information confusion, because the multi-objective optimization model can perform targeted analysis and calculations based on the independent data of each building, rather than being disturbed by the differences between the two at the beginning.

[0055] The target building BIM model of the initial design is the most frequently used BIM model of the surrounding buildings.

[0056] It is understandable that the design and layout of the surrounding building BIM model have been tested in practice and can adapt to actual building needs, site conditions, usage functions and other factors. Using such a model as a reference for the initial design of the target building can draw on these successful experiences, reduce the cost of trial and error in the design process, reduce the complexity of the design, and improve the design efficiency.

[0057] The multi-objective optimization model for obtaining green building evaluation performance indicators includes:

[0058] Conduct a survey on the surrounding building technologies and select a certain number of green building technologies with the highest frequency of use;

[0059] Based on the selected green building technologies, a green building assessment method is constructed;

[0060] Based on the evaluation data in the green building evaluation method, multiple intelligent evaluation algorithms are used for evaluation, and the average accuracy of each intelligent evaluation algorithm is calculated according to the evaluation results;

[0061] Based on the intelligent evaluation algorithm with the highest average accuracy, the green building evaluation method is optimized and adjusted by constructing a green building professional data set and question-answer pairs;

[0062] Use the optimized and adjusted green building assessment method to assess surrounding buildings and identify surrounding buildings with better scoring results;

[0063] Selecting surrounding buildings with better scoring results as cases, expanding the surrounding building cases, and constructing a multi-objective optimization model;

[0064] The multi-objective optimization model is used to optimize the technical solution of the target building.

[0065] It is understandable that by investigating surrounding building technologies and selecting the most frequently used green building technologies, the multi-objective optimization model construction can focus on technologies that are widely used and effective in practice. This makes the multi-objective optimization model highly technically targeted in the optimization process of the target building.

[0066] Constructing a green building assessment method and using multiple intelligent assessment algorithms for assessment can combine the advantages of multiple assessment methods. According to the assessment results, the algorithm with the highest average accuracy is selected to optimize the assessment method, which can improve the accuracy of the assessment.

[0067] The surrounding buildings with good scoring results were selected as cases to construct the multi-objective optimization model, providing a practical and successful example reference for the target building. These case buildings have proven their advantages in green building performance in practice.

[0068] The multi-objective optimization model can comprehensively consider multiple performance indicators of green buildings. During the construction process, from screening green building technologies to optimizing evaluation methods and then to case expansion, it covers energy conservation, environmental protection, indoor environmental quality, resource utilization and other aspects. This enables the model to comprehensively consider the relationship between various performance indicators when optimizing the technical solutions of the target building, avoiding the situation of focusing on a single indicator and ignoring other important factors.

[0069] Since the multi-objective optimization model is built based on the actual conditions of the surrounding buildings, including the application of technology and evaluation data, it has good adaptability to the regional environment where the target building is located. When the target building is optimized using this model, it can better integrate into the local building environment and climate conditions. For example, if the surrounding buildings use specific shading and ventilation technologies to cope with the local high temperature climate, these technologies are reflected in the multi-objective optimization model, and the target building can also optimize and apply these technologies through the model to improve the building's comfort and energy efficiency under local climate conditions.

[0070] The green building assessment method comprises:

[0071] Determine the comprehensive perfection coefficient of the green building technology based on energy consumption, construction difficulty, environmental adaptability, technical maturity and reliability, and economic investment;

[0072] Calculate the potential improvement scores of various green building technology-related parameters, where the potential improvement refers to the extent to which different performances of the current green building technology can be improved;

[0073] The comprehensive improvement coefficient is used to perform weighted calculation on the score of the space that can be improved for each green building technology to obtain a comprehensive score for the green building technology.

[0074] It is understandable that by considering energy consumption, construction difficulty, environmental adaptability, technical maturity and reliability, and economic investment to determine the comprehensive improvement coefficient, a comprehensive assessment of green building technology can be conducted. This assessment method avoids the limitation of focusing on a single factor (such as only considering energy-saving effects) while ignoring other important aspects (such as construction complexity or economic feasibility).

[0075] Different construction projects may have different emphases on these factors. For example, for some projects with tight budgets, economic input factors may account for a larger proportion; while for buildings with extremely high environmental quality requirements, environmental adaptability and energy consumption factors may be more critical. The calculation of the comprehensive improvement coefficient can flexibly adjust the weight of each factor according to the specific needs of the project, so as to more accurately evaluate whether the green building technology meets the project requirements.

[0076] The multi-objective optimization model construction comprises:

[0077] Create a physical model based building model;

[0078] Establishing a neural network model, and using the building model to create a training data set, and training and debugging the neural network model;

[0079] A multi-objective decision support model is established to make optimization decisions in the dimensions of energy consumption, construction difficulty, comfort, technology maturity and cost based on multi-objective decision-making theory, and to generate a comprehensive optimization plan that balances various objectives.

[0080] The difference information includes energy consumption difference, environmental impact difference, indoor quality environment difference and building layout difference;

[0081] The inconsistent distinguishing information may include: parts with lower energy efficiency than surrounding buildings, design elements or materials with greater environmental impact, areas or features with poor indoor environmental quality, and unreasonable design of building layout, such as layout that blocks natural lighting or ventilation;

[0082] The target building improvement information includes: structural adjustment: it may be necessary to adjust the structural layout of the building to improve energy efficiency or reduce environmental impact; material selection: improve the selection of building materials to meet the material standards of green buildings; system optimization: optimize the building's HVAC, lighting, water systems, etc. to improve overall performance; landscape and environment: optimize the interaction between the building and the surrounding environment, including natural ventilation, daylight utilization, heat island effect mitigation, etc.; sustainability strategies: implement strategies such as renewable energy utilization, rainwater collection, and waste management.

[0083] The evaluation data in the green building evaluation method is evaluated by using multiple intelligent evaluation algorithms, and the average accuracy of each intelligent evaluation algorithm is calculated according to the evaluation results, specifically including:

[0084] The evaluation data in the green building evaluation method is divided into a training set and a validation set, wherein the training set is used to train the algorithm model so that the algorithm can learn the relationship between the building characteristics and the evaluation results; and the validation set is used to evaluate the performance of the method during the training process to prevent overfitting;

[0085] The multiple intelligent evaluation algorithms include a decision tree algorithm, a SVM algorithm and a neural network algorithm;

[0086] The calculation evaluation index in calculating the average correct rate of each intelligent evaluation algorithm may be accuracy, precision, recall, or precision and recall.

[0087] A green energy-saving design optimization system for a building project, the green energy-saving design optimization system for a building project is used to implement a green energy-saving design optimization method for a building project; comprising:

[0088] A data acquisition module is used to acquire a BIM building model and a multi-objective optimization model for reflecting green building evaluation performance indicators; the BIM building model includes an initially designed target building BIM model and surrounding building BIM models;

[0089] A data acquisition module is used to obtain the target building structure layout data and the surrounding building structure layout data respectively according to the initially designed target building BIM model and the surrounding building BIM model;

[0090] A data processing module, used for inputting the target building structure layout data and the surrounding building structure layout data into a multi-objective optimization model, and obtaining target building distinction information and surrounding building distinction information output by comparing the target building and the surrounding buildings with the index values ​​in the green building evaluation performance index respectively;

[0091] The data output module is used to compare the target building difference information and the surrounding building difference information to obtain inconsistent difference information, obtain the target building improvement information based on the inconsistent difference information; and design a new target building BIM model according to the target building improvement information.

[0092] A person skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, such as ROM / RAM, disk, CD-ROM, etc.

[0093] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

[0094] It should be noted that the embodiments of the present invention can be implemented by hardware, software or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in processor control codes, such as such codes provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.

[0095] In addition, although the operation of the method of the present invention is described in a particular order in the accompanying drawings, this does not require or imply that these operations must be performed in this particular order, or that all the operations shown must be performed to achieve the desired result. On the contrary, the steps described in the flow chart can change the order of execution. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution. It should also be noted that the features and functions of two or more devices according to the present invention can be embodied in one device. On the contrary, the features and functions of a device described above can be further divided into being embodied by multiple devices.

[0096] Although the invention has been described with reference to several specific embodiments, it should be understood that the invention is not limited to the specific embodiments disclosed. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A green energy-saving design optimization method for construction engineering, characterized in that: The method comprises: Obtain BIM building models and multi-objective optimization models for reflecting green building evaluation performance indicators; The BIM building model includes an initially designed target building BIM model and a surrounding building BIM model; and the target building structure layout data and the surrounding building structure layout data are obtained respectively according to the initially designed target building BIM model and the surrounding building BIM model; Inputting the target building structure layout data and the surrounding building structure layout data into a multi-objective optimization model, obtaining target building distinction information and surrounding building distinction information output by comparing the target building and the surrounding buildings with the index values ​​in the green building evaluation performance index respectively; Based on the target building distinction information and the surrounding building distinction information, the two distinction information are compared to obtain inconsistent distinction information, and the target building completion information is obtained based on the inconsistent distinction information; A new target building BIM model is designed based on the target building improvement information.

2. The green energy-saving design optimization method for construction projects according to claim 1 is characterized by: The multi-objective optimization model for obtaining green building evaluation performance indicators includes: Conduct a survey on the surrounding building technologies and select a certain number of green building technologies with the highest frequency of use; Based on the selected green building technologies, a green building assessment method is constructed; Based on the evaluation data in the green building evaluation method, multiple intelligent evaluation algorithms are used for evaluation, and the average accuracy of each intelligent evaluation algorithm is calculated according to the evaluation results; Based on the intelligent evaluation algorithm with the highest average accuracy, the green building evaluation method is optimized and adjusted by constructing a green building professional data set; Use the optimized and adjusted green building assessment method to assess surrounding buildings and identify surrounding buildings with better scoring results; Selecting surrounding buildings with better scoring results as cases, expanding the surrounding building cases, and constructing a multi-objective optimization model; The multi-objective optimization model is used to optimize the technical solution of the target building.

3. The green energy-saving design optimization method for construction projects according to claim 2 is characterized in that: The target building BIM model of the initial design is the most frequently used BIM model of the surrounding buildings.

4. The green energy-saving design optimization method for construction engineering according to claim 2 is characterized in that: The redesigning of the target building BIM model based on the target building improvement information includes: inputting the target building improvement information into the multi-objective optimization model to obtain a new target building technical solution, and obtaining a new target building BIM model according to the new target building technical solution.

5. The green energy-saving design optimization method for construction engineering according to claim 2 is characterized in that: The green building assessment method comprises: Determine the comprehensive perfection coefficient of the green building technology based on energy consumption, construction difficulty, environmental adaptability, technical maturity and reliability, and economic investment; Calculate the potential improvement scores of various green building technology-related parameters, where the potential improvement refers to the extent to which different performances of the current green building technology can be improved; The comprehensive improvement coefficient is used to perform weighted calculation on the score of the space that can be improved for each green building technology to obtain a comprehensive score for the green building technology.

6. The green energy-saving design optimization method for construction engineering according to claim 2 is characterized by: The multi-objective optimization model construction comprises: Create a physical model based building model; Establishing a neural network model, and using the building model to create a training data set, and training and debugging the neural network model; A multi-objective decision support model is established to make optimization decisions in the dimensions of energy consumption, construction difficulty, comfort, technology maturity and cost based on multi-objective decision-making theory, and to generate a comprehensive optimization plan that balances various objectives.

7. The green energy-saving design optimization method for construction projects according to claim 1 is characterized by: The difference information includes energy consumption difference, environmental impact difference, indoor quality environment difference and building layout difference; The inconsistent distinguishing information may include: parts with lower energy efficiency than surrounding buildings, design elements or materials with greater environmental impact, areas or features with poor indoor environmental quality, and unreasonable design of building layout, such as layout that blocks natural lighting or ventilation; The target building improvement information includes: Structural adjustment: the structural layout of the building may need to be adjusted to improve energy efficiency or reduce environmental impact; Material selection: Improve the selection of building materials to meet the material standards of green buildings; System optimization: Optimize the building's HVAC, lighting, and water systems to improve overall performance; Landscape and environment: Optimize the interaction between the building and the surrounding environment, including natural ventilation, daylight utilization, and heat island effect mitigation; Sustainability strategies: Implement renewable energy utilization, rainwater collection, and waste management strategies.

8. The green energy-saving design optimization method for construction engineering according to claim 2 is characterized by: The evaluation data in the green building evaluation method is evaluated by using multiple intelligent evaluation algorithms, and the average accuracy of each intelligent evaluation algorithm is calculated according to the evaluation results, specifically including: The evaluation data in the green building evaluation method is divided into a training set and a validation set, wherein the training set is used to train the algorithm model so that the algorithm can learn the relationship between the building characteristics and the evaluation results; and the validation set is used to evaluate the performance of the method during the training process to prevent overfitting; The multiple intelligent evaluation algorithms include a decision tree algorithm, a SVM algorithm and a neural network algorithm; The evaluation indicators calculated in calculating the average correct rate of each intelligent evaluation algorithm according to the evaluation results may be accuracy, precision, recall, and precision and recall.

9. A green energy-saving design optimization system for construction engineering, characterized in that: The green energy-saving design optimization system for construction projects is used to implement the green energy-saving design optimization method for construction projects according to any one of claims 1 to 8; comprising: A data acquisition module is used to acquire a BIM building model and a multi-objective optimization model for reflecting green building evaluation performance indicators; the BIM building model includes an initially designed target building BIM model and surrounding building BIM models; A data acquisition module is used to obtain the target building structure layout data and the surrounding building structure layout data respectively according to the initially designed target building BIM model and the surrounding building BIM model; A data processing module, used for inputting the target building structure layout data and the surrounding building structure layout data into a multi-objective optimization model, and obtaining target building distinction information and surrounding building distinction information output by comparing the target building and the surrounding buildings with the index values ​​in the green building evaluation performance index respectively; The data output module is used to compare the target building difference information and the surrounding building difference information to obtain inconsistent difference information, obtain the target building improvement information based on the inconsistent difference information; and design a new target building BIM model according to the target building improvement information.

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