Intelligent evaluation method for application value of green building BIM model

Abstract

The invention provides an application value intelligent evaluation method for a green building BIM model, and relates to the technical field of intelligent building evaluation, and the method comprises the steps: carrying out the stage division of a green building on an information set of the green building, generating stage identifiers, and constructing a value factor set, the method comprises the following steps of: configuring value standards of factors in a value factor set through big data to carry out value calculation of associated information and an information set, mapping value elements according to the value standards to carry out association of value subjects, and determining subject association coefficients to generate mapping data of the value factor set; and generating an application value evaluation result of the BIM model through the stage identifier and the mapping data, thereby solving the technical problem of low application value of the green building due to lack of application value evaluation on the green building in the prior art, realizing establishment of the BIM model for the green building and accurate and intelligent evaluation of the application value, and improving the application value evaluation efficiency. And the application value of green buildings is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent building evaluation, and in particular to an intelligent evaluation method for the application value of a green building BIM model. Background Art

[0002] With the rapid development of the construction industry, the problem of building energy consumption has also emerged. In order to better conform to the concepts and principles of low-carbon, environmental protection and energy conservation, the concept and idea of ​​green buildings have been derived, and the concept of green buildings has been integrated into the entire life cycle of buildings. As society progresses and develops, people must also solve and respond to problems such as ecological and energy crises and population growth in development. This has also led to the concept of green development. The construction industry is a traditional high-energy consumption industry. However, in existing technologies, there is a lack of application value assessment for green buildings, resulting in the technical problem of low application value of green buildings. Summary of the invention

[0003] The present application provides a method for intelligently evaluating the application value of a green building BIM model, which is used to solve the technical problem in the prior art that the application value of green buildings is low due to the lack of application value evaluation of green buildings.

[0004] In view of the above problems, the present application provides an intelligent evaluation method for the application value of a green building BIM model.

[0005] In the first aspect, the present application provides an intelligent evaluation method for the application value of a green building BIM model, the method comprising: collecting building information of green buildings and constructing an information set of the green buildings; dividing the green buildings into stages based on the information set and generating stage identifiers; extracting value factors in the same stage based on the stage identifiers and constructing a value factor set, wherein the value factor set includes economic value factors, functional value factors, social value factors, environmental value factors, safety value factors and physical value factors; configuring the value standards of the factors in the value factor set through big data; interacting with the associated information of the green buildings and calculating the value of the associated information and the information set based on the value standards; mapping value elements based on the value standards, and associating the value elements with value subjects, performing principal component analysis of the value subjects and determining subject association coefficients; compensating the calculation results based on the subject association coefficients and generating mapping data of the value factor set; performing linear weighted calculations through the stage identifiers and the mapping data to generate application value evaluation results of the BIM model.

[0006] In the second aspect, the present application provides an application value intelligent evaluation system for a green building BIM model, the system comprising: a building information collection module, the building information collection module is used to collect building information of green buildings and construct an information set of the green buildings; a stage division module, the stage division module is used to divide the green buildings into stages according to the information set and generate stage identifiers; a factor extraction module, the factor extraction module is used to extract value factors in the same stage based on the stage identifier and construct a value factor set, wherein the value factor set includes economic value factors, functional value factors, social value factors, environmental value factors, safety value factors and physical value factors; a value standard configuration module, the value standard configuration module is used to The value standard of the factors in the value factor set is configured; a value calculation module, which is used to interact with the associated information of the green building and calculate the value of the associated information and the information set according to the value standard; a principal component analysis module, which is used to map the value elements according to the value standard, associate the value elements with the value subjects, perform principal component analysis of the value subjects, and determine the subject association coefficient; a compensation module, which is used to compensate the calculation results according to the subject association coefficient and generate the mapping data of the value factor set; a linear weighted calculation module, which is used to perform linear weighted calculation through the stage identification and the mapping data to generate the application value evaluation result of the BIM model.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application provides a method for intelligent evaluation of the application value of a green building BIM model, which relates to the technical field of intelligent building evaluation. It solves the technical problem in the prior art that the application value of green buildings is low due to the lack of application value evaluation of green buildings, and realizes the establishment of a BIM model for green buildings and accurate intelligent evaluation of their application value, thereby improving the application value of green buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flow chart of an intelligent evaluation method for the application value of a green building BIM model is provided for this application; Figure 2 A schematic diagram of the process of determining the subject correlation coefficient in the intelligent evaluation method of the application value of a green building BIM model is provided for this application; Figure 3 A schematic diagram of the process of obtaining mapping data in an intelligent evaluation method for application value of a green building BIM model is provided for this application; Figure 4A schematic diagram of the process of generating fuzzy application value evaluation results in an intelligent evaluation method for application value of a green building BIM model is provided for this application; Figure 5 A schematic diagram of the structure of an intelligent evaluation system for the application value of a green building BIM model is provided for this application.

[0009] Explanation of the accompanying drawings: building information collection module 1, stage division module 2, factor extraction module 3, value standard configuration module 4, value calculation module 5, principal component analysis module 6, compensation module 7, linear weighted calculation module 8. DETAILED DESCRIPTION

[0010] The present application provides an intelligent evaluation method for the application value of a green building BIM model, so as to solve the technical problem in the prior art that the application value of green buildings is low due to the lack of application value evaluation for green buildings.

[0011] Embodiment 1 like Figure 1 As shown, the embodiment of the present application provides an intelligent evaluation method for the application value of a green building BIM model, the method comprising: Step S100: collecting building information of green buildings and constructing an information set of the green buildings; Specifically, the application value intelligent evaluation method of a green building BIM model provided by the embodiment of the present application is applied to an application value intelligent evaluation system of a green building BIM model. In order to ensure the accuracy of the later application value evaluation of the green building BIM model, the multi-dimensional collection of building information of the green building can be carried out through manual collection, automatic collection, drone collection, cloud collection and other collection methods. Manual collection is to collect the building data of the green building by manual input, such as the hand-drawn drawings of the architect. The engineer fills in the construction plan and other operations, the automatic collection is to automatically collect data through automatic sensors, monitoring equipment, intelligent terminals, etc., the drone collection is to carry out field survey or data collection of the green building through drones equipped with cameras, laser scanners and other equipment, such as three-dimensional scanning of the appearance of the green building, land measurement, etc., the cloud collection is to upload the building data to the cloud computing server for online storage and management, and use the cloud algorithm to analyze and process the uploaded data, so that the building information collected by the collection methods such as manual collection, automatic collection, drone collection, cloud collection, etc. is summarized and recorded as the information set of the green building, which is an important reference for the later intelligent evaluation of the application value of the green building BIM model.

[0012] Step S200: dividing the green building into stages according to the information set and generating stage identifiers; Specifically, using the above-mentioned green building information set as the division standard data, the target green building is divided into stages, which means that the stages can be divided according to the building structure, building materials, building cost, building area, building environment, construction conditions, building location, etc. in the green building information set. The divided stages may include the early stage of green building construction, the preparation stage of construction, the implementation stage of construction, the building acceptance stage, etc. The early stage of green building construction refers to the stage of feasibility analysis of the green building, the preparation stage of green building construction refers to the stage of investigation and design of the green building, the implementation stage of green building construction refers to the stage of preparation for engineering construction and production of the green building, and the building acceptance stage of the green building refers to the stage of acceptance after the green building is completed. The stages divided by the green building are marked with data marks representing the individual stages derived from the stage division, and the marked stages are recorded as the stage marks of the green building, thereby ensuring the realization of intelligent evaluation of the application value of the green building BIM model.

[0013] Step S300: extracting the value factors in the same stage based on the stage identifier, and constructing a value factor set, wherein the value factor set includes economic value factors, functional value factors, social value factors, environmental value factors, safety value factors and physical value factors; Specifically, according to the stage identification of green buildings, value factors are extracted for each identified and in the same stage. Value factors refer to multi-dimensional value measurement of green buildings, which can include the economic value dimension, functional value dimension, social value dimension, environmental value dimension, and safety value dimension of green buildings. At the same time, the economic value factor, functional value factor, social value factor, environmental value factor, safety value factor and physical value factor of green buildings are determined respectively in the economic value dimension, functional value dimension, social value dimension, environmental value dimension, and safety value dimension. The economic value factor of green buildings refers to the engineering cost data of green buildings, and the functional value factor of green buildings refers to the convenience of engineering when carrying out green buildings. , coordination data, the social value factor of green buildings refers to the data on the significance and usefulness achieved by green buildings in satisfying society, the environmental value factor of green buildings refers to the data on the effectiveness and significance of the surrounding environment of green buildings to human survival and development, the safety value factor of green buildings refers to the data on the use of value engineering to evaluate the structural safety and material safety of green buildings, and the physical value factor of green buildings refers specifically to the value data of green buildings such as blast furnaces, mines, bridges, water towers, chimneys, sewers, etc. Finally, the construction of the value factor set is completed based on the economic value factor, functional value factor, social value factor, environmental value factor, safety value factor and physical value factor, laying a solid foundation for the subsequent intelligent evaluation of the application value of the green building BIM model.

[0014] Step S400: configuring the value standards of factors in the value factor set through big data; Specifically, in order to ensure the accuracy of the application value assessment of green buildings, it is necessary to evaluate the economic value factors, functional value factors, social value factors, environmental value factors, safety value factors and physical value factors in the value factor set through the economic value dimensions, functional value dimensions, social value dimensions, environmental value dimensions, safety value factors and physical value dimensions contained in big data. Therefore, it is first necessary to define the value judgment standards within the dimension matching of the economic value dimensions, functional value dimensions, social value dimensions, environmental value dimensions, safety value dimensions and physical value dimensions of green buildings in big data, and determine the economic value standards, functional value standards, social value standards, environmental value standards, safety value standards and physical value standards. Furthermore, based on the standards determined by big data, the configuration of the value standards in the value factor set is completed, which plays a limited role in realizing the intelligent evaluation of the application value of the green building BIM model.

[0015] Step S500: exchanging the associated information of the green building, and calculating the value of the associated information and the information set according to the value standard; Specifically, since a more comprehensive value assessment of green buildings is required, data interaction of the associated information of green buildings is required. The associated information of green buildings refers to data other than the main body of green buildings, which can be green building environmental data, green building location data, etc. Further, the value of the associated information of green buildings and the information set of green buildings is calculated based on the above-configured value standards. The formula is as follows: ; Among them, P is the calculation result of the value of green buildings, V is the building data of green buildings contained in the information set, n is the weight coefficient of the building data of green buildings contained in the information set, S is the building data of green building related information, m is the weight coefficient of the building data of green building related information, and Q is the value standard of green buildings.

[0016] The value of green buildings is calculated using the above formula to obtain the value calculation results, which can be used as reference data for the subsequent intelligent evaluation of the application value of the green building BIM model.

[0017] Step S600: mapping the value elements according to the value standard, and associating the value elements with the value subjects, performing principal component analysis of the value subjects, and determining the subject association coefficients; Furthermore, if Figure 2 As shown, step S600 of the present application also includes: Step S610: calling the standard database to perform calibration and segmentation of the value subject, and determining the core value subject, the general value subject and the marginal value subject, wherein the calibration and segmentation results carry the initial assessment weight value; Step S620: Identify the basic attributes of the value subject based on the associated information and the information set, and generate an attribute associated value; Step S630: Perform principal component analysis of the value subject based on the initial assessment weight value and the attribute association value to determine the subject association coefficient.

[0018] Specifically, the value standard is first mapped to obtain the value elements that have a mapping relationship with the value standard. The mapping relationship between the value standard and the value element can be that when a value is taken within the value element, the value standard has one and only one corresponding value, while when a value is taken within the value standard, the value element can have multiple corresponding values. Further, the mapped value element is associated with the value subject, which refers to calling the standard database. The standard database is constructed by multi-dimensional standard data of green buildings. The value subject is calibrated and segmented through the standard database, which refers to the segmentation according to the degree of influence of the intelligent evaluation of the application value of the green building BIM model. The value subject with an influence greater than or equal to 80% is regarded as the core value subject, the value subject with an influence less than 80% and greater than 30% is regarded as the general value subject, and the value subject with an influence less than or equal to 30% is regarded as the marginal value subject. The value subject and the marginal value subject are taken as the calibration segmentation results, wherein the calibration segmentation results all carry the initial assessment weight values. Further, the basic attributes of the core value subject, the general value subject and the marginal value subject in the value subject are respectively identified based on the associated information and the information set. According to the subject attributes contained in the core value subject, the general value subject and the marginal value subject, the attribute association value is generated, that is, the higher the data consistency between the core value subject, the general value subject and the marginal value subject and the subject attributes, the greater the attribute association value. Finally, principal component analysis is performed on the value subject based on the initial assessment weight values ​​and the attribute association values, which means that a few principal components are derived from the value subject based on the initial assessment weight values ​​and the attribute association values, so that as much information of the value subject is retained as much as possible and they are not related to each other, thereby determining the subject association coefficient and improving the accuracy of the intelligent evaluation of the application value of the green building BIM model in the later stage.

[0019] Step S700: compensating the calculation result according to the subject association coefficient to generate mapping data of the value factor set; Specifically, in order to compensate for the loss of the value calculation result, it is necessary to compensate the calculation result according to the subject association coefficient determined above, which means first extracting the model data of the green building BIM model, and using the data extraction result and the information set for data consistency verification. The verification result and the comparison result obtained by comparing the BIM model with the green building function one by one are used as the basic data for judgment, and the degree of influence of the value standard evaluation of the green building are determined. Finally, the result of the value calculation is compensated according to the degree of influence. The greater the degree of influence, the more data needs to be compensated, and then the mapping data of the value factor set is obtained based on the compensation result, so as to ensure better intelligent evaluation of the application value of the green building BIM model in the later stage.

[0020] Furthermore, if Figure 3As shown, step S700 of the present application also includes: Step S710: extracting model data from the BIM model, performing data consistency verification on the data extraction result and the information set, and generating a data verification result; Step S720: comparing the functions of the BIM model and the green building one by one to generate a function verification result; Step S730: determining the influencing factor of the value standard evaluation according to the data verification result and the function verification result; Step S740: Compensate the result of the value calculation using the impact factor, and obtain the mapping data according to the compensation result.

[0021] Furthermore, step S740 of the present application includes: Step S741: Analyze the convenience of calling functions of the BIM model and generate the calling step length of each function; Step S742: performing step length comparison of the calling step length according to the value standard corresponding to the convenience, and generating a convenience value calculation result according to the step length comparison result; Step S743: performing model data update analysis on the BIM model to generate data update speed data; Step S744: performing a functional collaboration analysis on the BIM model to generate collaboration evaluation data, performing coordination value calculation based on the data update speed data and the collaboration evaluation data to generate a coordination value calculation result; Step S745: Compensate the convenience value calculation result and the coordination value calculation result with the corresponding subject association coefficient to obtain mapping data of the functional value factor.

[0022] Specifically, the model data of the green building BIM model is extracted, and the extracted model data contains the data elements corresponding to the green building body in the model. Furthermore, the data extraction result is checked for consistency with the information set, and the building data in the data extraction result is matched with the green building data in the information set to obtain the data matching degree, and the data verification result of the data extraction result and the information set is generated according to the data matching degree.

[0023] Furthermore, the function-by-function comparison between the BIM model and the green building is to compare the convenience function and completeness function of the BIM technology in the BIM model with the building use function and building requirement function in the green building in sequence, so as to generate the function verification result of the BIM model and the green building according to the consistency of the comparison data, and at the same time, use the data verification result and the function verification result as the standard evaluation data to determine the influencing factor of the value standard evaluation of the green building. The influencing factor of the value standard evaluation is the factor used to assess the degree of influence on the value of the green building, and finally the result of the value calculation is supplemented by the influencing factor. Compensation refers to first analyzing the convenience of function calling of the BIM model. It means that after the functions in the BIM model are serialized, the calling step of each function is generated according to the convenience of function calling in the determined sequence. The calling step of each function refers to the number of elements spanned by each function in the sequence access order. Furthermore, the step length of the calling step is compared by the value standard corresponding to the convenience. It means taking the value standard step corresponding to the convenience in the BIM model as the standard comparison step length, comparing it with the called step length, and determining the calculation result of the convenience value according to the length of the step in the step comparison result.

[0024] Further model data update analysis of the BIM model refers to modifying, deleting or adding model data stored in the BIM model, and recording the time spent on modifying, deleting or adding model data. On this basis, the model data update speed is calculated, and data update speed data is obtained based on the model data update speed. Then, the functional collaboration analysis of the BIM model refers to the functional collaboration of the model data through sharing data information inside and outside the BIM model, that is, data modification, addition and other operations, as well as completing data viewing and confirmation, thereby generating collaboration evaluation data, and finally generating collaboration evaluation data based on data update speed data and collaboration evaluation data. Calculating the coordination value of the BIM model refers to evaluating the collaborative evaluation data according to the data update speed data, and taking the evaluation result as the coordination value calculation result, and then compensating the convenience value calculation result and the coordination value calculation result with the corresponding subject association coefficient, which means traversing the subject association coefficient in sequence and then comparing and mapping the convenience and coordination in the subject association coefficient with the convenience value calculation result and the coordination value calculation result, and taking the comparison and mapping result as the basic data to determine the mapping data of the functional value factor, so as to ensure the efficiency of the intelligent evaluation of the application value of the green building BIM model.

[0025] Furthermore, step S700 of the present application also includes: Step S750: reading the evaluation requirement information of the green building; Step S760: performing demand analysis on the evaluation demand information to generate a constraint balance index for evaluation sensitivity and complexity; Step S770: The data accuracy of the value calculation is adjusted by the constraint balance index to generate a calculation result.

[0026] Furthermore, step S770 of the present application includes: Step S771: constructing a balance evaluation model, and inputting the constraint balance index into the balance evaluation model to initialize the hidden layer function of the model; Step S772: inputting the value standard, the associated information and the information set as input data into the balance evaluation model; Step S773: performing sensitivity and complexity fitting screening through the balance evaluation model to determine adjustment parameters; Step S774: Adjust the data accuracy of the value calculation based on the adjustment parameters.

[0027] Specifically, the evaluation demand information of green buildings is read. The evaluation demand can be the demand for extracting the impact that needs to be avoided when evaluating green buildings. Furthermore, the evaluation demand information is analyzed to obtain the displacement rate relative to the evaluated variable, the evaluation efficiency, etc. when evaluating green buildings, so as to determine the evaluation sensitivity according to the displacement rate, and determine the evaluation complexity according to the evaluation efficiency, thereby generating a constraint balance index of the evaluation sensitivity and complexity. Furthermore, the data accuracy of the value calculation is adjusted by the constraint balance index, which means that the data accuracy of the value calculation is within the constraint balance index and is retained, and the data accuracy of the value calculation is not within the constraint balance index and is eliminated. On this basis, a balanced evaluation model is constructed, and the constraint balance index is input into the balanced evaluation model, a fully connected neural network is constructed, and the input constraint balance index is trained using the neural network. The fully connected neural network refers to a multi-layer sensor network. A neural network with a knowledge-based structure is used to further construct a balance evaluation model, wherein the input data of the fully connected neural network includes constraint balance indicators, and each node of each layer of the fully connected neural network is fully connected to all nodes in the upper and lower layers. The balance evaluation model includes an input layer, a hidden layer, and an output layer. The input layer is a layer for data input, the hidden layer is used to better separate data features, and the output layer is a layer for result output. The balance evaluation model is obtained by training with a training data set and a supervision data set. At the same time, after the hidden layer of the balance evaluation model is initialized and configured with a function, the value standard, associated information, and information set are used as input data and input into the balance evaluation model. The sensitivity and complexity fitting screening is performed through the balance evaluation model. The balance evaluation model is obtained by training with a training data set and a supervision data set, wherein each set of training data in the training data set includes a value standard, associated information, and an information set, and the supervision data set is supervision data that corresponds one to one to the training data set.

[0028] Furthermore, each group of training data in the training data set is input into the balance evaluation model, and the output supervision adjustment of the balance evaluation model is performed through the supervision data corresponding to this group of training data. When the output result of the balance evaluation model is consistent with the supervision data, the training of the current group is completed. After all the training data in the training data set are trained, the fitting screening of sensitivity and complexity in the balance evaluation model is completed, so as to determine the adjustment parameters. At the same time, the adjustment parameters are used as the adjustment standards to adjust the data accuracy of the value calculation. The data accuracy of the value calculation result is updated according to the adjusted data accuracy to obtain the value calculation result, so as to achieve the technical effect of intelligent evaluation of the application value of the green building BIM model.

[0029] Step S800: Performing linear weighted calculation on the stage identifier and the mapping data to generate an application value assessment result of the BIM model.

[0030] Specifically, in order to improve the accuracy of intelligent evaluation of the application value of BIM models, it is necessary to use stage identification and mapping data as basic data and perform linear weighted calculations on them. The linear weighted calculations need to be based on a large amount of data aggregation and accurate determination of weights before performing targeted calculations. For example, the weight ratio of stage identification and mapping data can be the first influence coefficient: the second influence coefficient is 4:6, and the influence parameters after the linear weighted calculation process are the first influence parameter*0.4 and the second influence parameter*0.6, respectively. The linear weighted calculation results are recorded as the application value evaluation results of the BIM model and output, so as to achieve a more accurate intelligent evaluation of the application value of the green building BIM model based on the application value evaluation results.

[0031] Furthermore, if Figure 4 As shown, step S800 of the present application also includes: Step S810: mapping and storing the application value evaluation result, the information set and the associated information to construct an evaluation result database; Step S820: extracting data features of the information set and the associated information, and constructing a matching feature set; Step S830: When performing subsequent fuzzy application value evaluation, similarity matching of data is performed through the matching feature set, and the evaluation result database is called according to the matching result to generate a fuzzy application value evaluation result.

[0032] Specifically, in order to make the application value evaluation results of the BIM model more accurate, the application value evaluation results, information sets and related information are first mapped and stored, which means that each evaluation result in the application value evaluation results is identified with the mapping data between the information set and the related information in turn, and the data with the identification is integrated and stored in the database in turn for recording, thereby completing the construction of the evaluation result database. Further, the building data features of the green building in the information set and the building related data features in the related information are extracted, and the building data features of the green building and the building related data features are summarized and stored, and recorded as a matching feature set. In order to avoid data redundancy during system operation, when performing subsequent fuzzy application value evaluation, the similarity matching of the building data can be first performed through the matching feature set, and the evaluation result database can be called according to the matching results at the same time. By extracting the evaluation results that meet the matching results in the evaluation result database, and outputting the extracted evaluation results as fuzzy application value evaluation results, the technical effect of providing an important basis for the later realization of intelligent evaluation of the application value of the green building BIM model is achieved.

[0033] To sum up, the embodiment of the present application provides a method for intelligent evaluation of the application value of a green building BIM model, which includes at least the following technical effects, which realizes the establishment of a BIM model for a green building and performs accurate intelligent evaluation of its application value, thereby improving the application value of the green building.

[0034] Embodiment 2 Based on the same inventive concept as the intelligent evaluation method for application value of a green building BIM model in the aforementioned embodiment, Figure 5 As shown, the present application provides an intelligent evaluation system for the application value of a green building BIM model, the system comprising: A building information collection module 1, the building information collection module 1 is used to collect building information of green buildings and construct an information set of the green buildings; A stage division module 2, the stage division module 2 is used to divide the green building into stages according to the information set and generate stage identifiers; A factor extraction module 3, wherein the factor extraction module 3 is used to extract the value factors in the same stage based on the stage identifier and construct a value factor set, wherein the value factor set includes an economic value factor, a functional value factor, a social value factor, an environmental value factor, a safety value factor and an entity value factor; A value standard configuration module 4, wherein the value standard configuration module 4 is used to configure the value standard of the factors in the value factor set through big data; A value calculation module 5, the value calculation module 5 is used to exchange the associated information of the green building, and calculate the value of the associated information and the information set according to the value standard; A principal component analysis module 6, which is used to map the value elements according to the value standard, associate the value elements with the value subjects, perform principal component analysis on the value subjects, and determine the subject association coefficient; A compensation module 7, the compensation module 7 is used to compensate the calculation result according to the subject association coefficient and generate mapping data of the value factor set; The linear weighted calculation module 8 is used to perform linear weighted calculation through the stage identification and the mapping data to generate an application value evaluation result of the BIM model.

[0035] Furthermore, the system also includes: A data consistency verification module, wherein the data consistency verification module is used to extract model data from the BIM model, perform data consistency verification on the data extraction result and the information set, and generate a data verification result; A first comparison module, the first comparison module is used to compare the functions of the BIM model and the green building one by one, and generate a function verification result; An impact factor determination module, the impact factor determination module is used to determine the impact factor of the value standard evaluation according to the data verification result and the function verification result; The first compensation module is used to compensate the result of value calculation using the impact factor, and obtain the mapping data according to the compensation result.

[0036] Furthermore, the system also includes: A calibration and segmentation module, which is used to call a standard database to perform calibration and segmentation of value subjects, and determine core value subjects, general value subjects, and marginal value subjects, wherein the calibration and segmentation results carry an initial assessment weight value; A basic attribute identification module, the basic attribute identification module is used to identify the basic attributes of the value subject according to the associated information and the information set, and generate an attribute association value; The first analysis module is used to perform principal component analysis of the value subject according to the initial assessment weight value and the attribute association value to determine the subject association coefficient.

[0037] Furthermore, the system also includes: An information reading module, the information reading module is used to read the evaluation requirement information of the green building; A requirement analysis module, the requirement analysis module is used to analyze the evaluation requirement information and generate a constraint balance index for evaluation sensitivity and complexity; The first calculation module is used to adjust the data accuracy of the value calculation through the constraint balance index to generate a calculation result.

[0038] Furthermore, the system also includes: A first input module, wherein the first input module is used to construct a balance evaluation model, input the constraint balance index into the balance evaluation model, and perform initialization configuration of a hidden layer function of the model; A second input module, the second input module is used to input the value standard, the associated information and the information set as input data into the balance evaluation model; A fitting screening module, the fitting screening module is used to perform fitting screening of sensitivity and complexity through the balance evaluation model to determine adjustment parameters; A second calculation module, wherein the second calculation module is used to adjust the data accuracy of the value calculation based on the adjustment parameter.

[0039] Furthermore, the system also includes: A second analysis module, the second analysis module is used to analyze the convenience of function calling of the BIM model and generate a calling step length of each function; A second comparison module, the second comparison module is used to compare the step lengths of the calling steps according to the value standard corresponding to the convenience, and generate a convenience value calculation result according to the step length comparison result; A third analysis module, the third analysis module is used to perform model data update analysis on the BIM model and generate data update speed data; A third calculation module, the third calculation module is used to perform a functional collaboration analysis on the BIM model, generate collaboration evaluation data, perform coordination value calculation according to the data update speed data and the collaboration evaluation data, and generate a coordination value calculation result; The second compensation module is used to compensate the convenience value calculation result and the coordination value calculation result for the corresponding subject association coefficient to obtain mapping data of the functional value factor.

[0040] Furthermore, the system also includes: A mapping storage module, the mapping storage module is used to map and store the application value evaluation result, the information set and the associated information to construct an evaluation result database; A matching feature module, the matching feature module is used to extract data features of the information set and the associated information, and construct a matching feature set; The matching module is used to perform similarity matching of data through the matching feature set when performing subsequent fuzzy application value evaluation, call the evaluation result database according to the matching result, and generate a fuzzy application value evaluation result.

[0041] Through the above-mentioned detailed description of the intelligent evaluation method for the application value of a green building BIM model, those skilled in the art can clearly know the intelligent evaluation system for the application value of a green building BIM model in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0042] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent evaluation method for the application value of a green building BIM model, characterized in that: The method comprises: Collecting building information of green buildings and constructing an information set of the green buildings; Dividing the green building into stages according to the information set and generating stage identifiers; Based on the stage identification, value factors in the same stage are extracted to construct a value factor set, wherein the value factor set includes economic value factors, functional value factors, social value factors, environmental value factors, safety value factors and physical value factors; Configure the value standards of factors in the value factor set through big data; Interacting the associated information of the green building, and calculating the value of the associated information and the information set according to the value standard; Mapping the value elements according to the value standard, and associating the value elements with the value subjects, performing principal component analysis of the value subjects, and determining the subject association coefficients; Compensating the calculation result according to the subject association coefficient to generate mapping data of the value factor set; A linear weighted calculation is performed through the stage identification and the mapping data to generate an application value assessment result of the BIM model.

2. The method according to claim 1, characterized in that The method further comprises: Extracting model data from the BIM model, performing data consistency verification on the data extraction result and the information set, and generating a data verification result; Compare the functions of the BIM model and the green building one by one to generate a function verification result; Determining the influencing factor of the value standard evaluation according to the data verification result and the function verification result; The result of value calculation is compensated by the impact factor, and the mapping data is obtained according to the compensation result.

3. The method according to claim 1, characterized in that The method further comprises: Call the standard database to calibrate and segment the value subject, determine the core value subject, general value subject and marginal value subject, wherein the calibration and segmentation results carry the initial assessment weight value; Identify the basic attributes of the value subject based on the associated information and the information set, and generate an attribute associated value; A principal component analysis of the value subject is performed based on the initial assessment weight value and the attribute association value to determine the subject association coefficient.

4. The method according to claim 1, characterized in that The method further comprises: Reading the evaluation requirement information of the green building; Performing demand analysis on the evaluation demand information to generate constraint balance indicators for evaluation sensitivity and complexity; The data accuracy of the value calculation is adjusted by the constraint balance index to generate a calculation result.

5. The method according to claim 4, characterized in that The method further comprises: Constructing a balance evaluation model, and inputting the constraint balance index into the balance evaluation model to perform initialization configuration of the hidden layer function of the model; Inputting the value standard, the associated information and the information set as input data into the balance evaluation model; Performing sensitivity and complexity fitting screening through the balance evaluation model to determine adjustment parameters; The data accuracy of the value calculation is adjusted based on the adjustment parameter.

6. The method according to claim 1, characterized in that The method further comprises: Analyze the convenience of calling the functions of the BIM model and generate the calling steps of each function; Comparing the step lengths of the calling steps according to the value standard corresponding to the convenience, and generating the convenience value calculation result according to the step length comparison result; Perform model data update analysis on the BIM model and generate data update speed data; Performing a functional collaboration analysis on the BIM model to generate collaboration evaluation data, performing coordination value calculation based on the data update speed data and the collaboration evaluation data to generate a coordination value calculation result; The calculation results of the convenience value and the calculation results of the coordination value are compensated by corresponding subject association coefficients to obtain mapping data of functional value factors.

7. The method according to claim 1, characterized in that The method further comprises: Mapping and storing the application value assessment result, the information set and the associated information to construct an assessment result database; Extracting data features of the information set and the associated information to construct a matching feature set; When performing subsequent fuzzy application value evaluation, similarity matching of data is performed through the matching feature set, and the evaluation result database is called according to the matching result to generate a fuzzy application value evaluation result.

8. An intelligent evaluation system for the application value of a green building BIM model, characterized in that: The system comprises: A building information collection module, the building information collection module is used to collect building information of green buildings and construct an information set of the green buildings; A stage division module, the stage division module is used to divide the green building into stages according to the information set and generate stage identifiers; A factor extraction module, the factor extraction module is used to extract the value factors in the same stage based on the stage identifier, and construct a value factor set, wherein the value factor set includes economic value factors, functional value factors, social value factors, environmental value factors, safety value factors and physical value factors; A value standard configuration module, the value standard configuration module is used to configure the value standard of the factors in the value factor set through big data; A value calculation module, the value calculation module is used to exchange the associated information of the green building and calculate the value of the associated information and the information set according to the value standard; A principal component analysis module, the principal component analysis module is used to map the value elements according to the value standard, associate the value elements with the value subject, perform principal component analysis on the value subject, and determine the subject association coefficient; A compensation module, the compensation module is used to compensate the calculation result according to the subject association coefficient and generate mapping data of the value factor set; A linear weighted calculation module is used to perform linear weighted calculation through the stage identification and the mapping data to generate an application value evaluation result of the BIM model.

Images