Urban construction industry carbon reduction path optimizing and determining system, medium and equipment

Abstract

The invention discloses an urban construction industrial carbon reduction path optimization and determination system, medium and equipment, and the system is characterized in that a model composed of an industrial carbon reduction object evaluation index obtaining module, an industrial carbon reduction object typing module, an industrial carbon reduction technology path generation module and a carbon reduction technology path optimization module is established; a comprehensive evaluation function is constructed for the industry of the city construction boundary range class through a genetic algorithm and the city based on the development characteristics of the city, so that the optimal carbon reduction technology path under each industry type is obtained, and finally, the economical efficiency and carbon reduction performance comprehensive optimal carbon reduction technology path in the low-carbon city construction industry field is formed. The path can fully reflect the advantages and characteristics of urban low-carbon development and the carbon reduction target, the carbon reduction target of the city can be achieved conveniently, the problem that the industrial carbon reduction path is unknown in the current urban construction process is effectively solved, and the urban construction industrial carbon reduction path conforming to the urban development policy is provided while the urban economic development is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of urban construction industry carbon reduction, and in particular to a method for optimizing urban construction industry carbon reduction paths based on environmental and economic coupling benefits. Background Art

[0002] Cities, as centers of economic activities, produce 70% of CO2. As one of the world's industrial producers, my country's industrial production has driven the rapid development of the urban economy and produced a large amount of greenhouse gases and pollutants, which has made my country face severe CO2 emissions and environmental pollution problems. Building an industrial carbon reduction technology path is of great strategic significance to the construction of low-carbon cities.

[0003] The "National Low-Carbon City Pilot Work Progress Assessment Report" pointed out that among the current 81 pilot cities, less than 50% were rated as excellent. The average scores of "innovative measures" and "low-carbon development system and mechanism construction" of each pilot city were slightly low. Most pilot cities did not make enough innovation in low-carbon development, and generally had room for improvement in the construction of low-carbon development systems and mechanisms.

[0004] In the prior art, the "A pollution reduction and carbon reduction path planning method, system, medium and equipment" disclosed in CN202410215629.1 constructs a scale-emission-cost pollution reduction and carbon reduction path planning model that changes dynamically under technological progress, and improves the accuracy of solving the optimal pollution reduction and carbon reduction path; the "A method and system for evaluating the synergistic effect of urban pollution reduction and carbon reduction" disclosed in CN202410665080.6 constructs a long-term series greenhouse gas and pollutant emission inventory for different industries in the city, analyzes the driving factors corresponding to greenhouse gases and pollutants, and evaluates the synergistic effect of urban pollution reduction and carbon reduction based on this. However, the above-mentioned technologies have the following limitations: First, the degree of concentration is insufficient. The above-mentioned similar patents analyze the impact of factors such as urban green technology on carbon emissions, and construct or evaluate the urban pollution reduction and carbon reduction path based on the degree of influence of each factor. However, the pollution reduction and carbon reduction path fails to reflect the characteristics of industries such as industry, resulting in the pollution reduction and carbon reduction path being unable to represent the carbon reduction path in the urban construction industry; Second, the content is incomplete. The above-mentioned and similar patents do not take into account the strategic positioning of urban low-carbon development and the basic laws and phased characteristics of low-carbon development in the region. The impact on the urban carbon reduction path cannot develop its own low-carbon development advantages and distinctive highlights and respond to the country's demand for low-carbon cities.

[0005] Therefore, in view of the urgent need for low-carbon city construction and the wide variety of industrial sectors and carbon reduction technologies applicable to each sector in each city and the complex carbon reduction paths, technical personnel in this field urgently need to build a system for optimizing and determining industrial carbon reduction paths for urban construction. Summary of the invention

[0006] In view of the problems existing in the prior art, the purpose of the present invention is to provide a method for optimizing the carbon reduction path of urban construction industry based on the coupled benefits of environment and economy, so as to provide the urban construction industry with the optimal industrial carbon reduction path with urban characteristics.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions:

[0008] A system for optimizing and determining industrial carbon reduction paths for urban construction, including an industrial carbon reduction object evaluation index acquisition module, an industrial carbon reduction object classification module, an industrial carbon reduction technology path generation module, and a carbon reduction technology path optimization module;

[0009] The industrial carbon reduction object evaluation index acquisition module is used to obtain evaluation indicators that can reflect the future development benefits of urban industry and transmit them to the industrial carbon reduction object classification module;

[0010] The industrial carbon reduction object classification module is used to establish a classification model to classify urban construction industrial carbon reduction objects, match classification labels for each urban construction industrial carbon reduction object, and transmit them to the specific industrial carbon reduction technology path generation module;

[0011] The industrial carbon reduction technology path generation module is used to match carbon reduction strategies and carbon reduction technologies according to the classification labels of industrial carbon reduction objects in low-carbon city construction through a decision tree model, obtain a set of carbon reduction technology paths for the classification results of industrial carbon reduction objects in low-carbon city construction, and transmit it to the carbon reduction technology path selection and optimization module;

[0012] The carbon reduction technology path optimization module is used to combine the background characteristics of the carbon reduction path with the city's low-carbon development goals, so as to obtain the optimal carbon reduction technology path under each industrial type, and finally form the optimal urban construction industrial carbon reduction technology path.

[0013] The industrial carbon reduction object evaluation index acquisition module uses CiteSpace software to perform keyword analysis on the literature related to current industrial development research, removes keywords with a frequency of less than q, and combines the context information of the remaining keywords to obtain the corresponding word vectors and evaluation indicators For keywords that cannot directly obtain evaluation indicators in the text, the missing evaluation indicators are supplemented through literature search The industrial development basic word set T1 is formed, and the word set T1 is matched with the three dimensions of industrial foundation, economic proportion and environmental impact for similarity, and the evaluation index of each keyword is calculated according to the matching results. Classify into corresponding sections and give labels P(A ij )={A 1j -Industrial Base-Indicator Name, A 2j -Economic proportion-Indicator name, A3j - environmental impact - indicator name}, forming the industrial evaluation indicator set T2, and transmitting it to the industrial carbon reduction object classification module. The calculation method is:

[0014]

[0015] Among them, R(x) is the similarity matching value, is the text embedding vector extracted from the i-th keyword in T1 after training; B j The text embedding vectors extracted after training for industrial base, economic share, and environmental impact respectively;

[0016] In the industrial carbon reduction object classification module, combined with the urban land types classified in the "Urban and Rural Land Classification and Planning and Construction Land Standards" GB50137, the urban construction industrial carbon reduction objects are locked into the manufacturing category. According to the corresponding evaluation indicators in the industrial evaluation indicator set T2, the ranking of urban construction industrial categories is obtained by establishing an entropy weight TOPSIS model. Based on the ranking, each category is divided into leading industries and non-leading industries in urban construction industrial development, and corresponding industrial type labels are assigned. According to the carbon benefit scores of each industrial category, the industry is further divided into encouraged, restricted and eliminated categories, forming an urban construction industrial category set T3 with industrial classification labels, and transmitted to the industrial carbon reduction technology path generation module.

[0017] The specific steps of establishing the entropy weight TOPSIS model to obtain the ranking of urban construction industrial categories and form an urban construction industrial category set T3 with industrial classification labels include:

[0018] 1) Build a decision matrix

[0019] A decision matrix is ​​constructed for m objects in the manufacturing industry category and n evaluation indicators in the industrial development evaluation indicator set T2 of each city. The evaluation object set is A = (A1, A2, ..., A m ), the evaluation index set is T2 = (T1, T2, ..., T n ), A i The corresponding value of each indicator in T2 is X ij (i=1,2,…,m;j=1,2,…,n), forming a decision matrix:

[0020]

[0021] 2) Standardization of evaluation indicators

[0022] The evaluation indicators include positive indicators and negative indicators. For negative indicators, take X mn The reciprocal of the negative indicator is converted into a positive indicator and substituted into the decision matrix to replace X mn, and obtain the standardized matrix.

[0023] 3) Determine the weight of evaluation indicators using entropy weight method

[0024] 1. Use the power coefficient method to make the standardized matrix dimensionless:

[0025]

[0026] 2. Calculate the entropy value based on the proportion of m evaluation objects under n evaluation indicators in the dimensionless data:

[0027]

[0028] Where: E j is the entropy value of evaluation index j, d ij is the proportion of the i-th evaluation object under the j-th evaluation index;

[0029] 3. Calculate the index weight W based on the dimensionless processing results and entropy value j :

[0030]

[0031] 4) Establishing TOPSIS model based on entropy weight

[0032] 4.1) Construct a weighted matrix based on the dimensionless processed data and entropy value. The calculation formula of the weighted matrix Z is as follows:

[0033] Z ij =W j ×D ij (6)

[0034] Z=[Z ij ] m×n (7)

[0035] 4.2) Determine the optimal solution Z in the weighted matrix for each evaluation index + and the worst solution Z - :

[0036]

[0037] Where: Z + is the optimal solution, is the maximum value of each column, Z - is the optimal solution, is the minimum value of each column, j = 1, 2, ..., n;

[0038] 4.3) Obtain the distance between each evaluation object and the optimal solution and the worst solution. The distance calculation formula between the evaluation object and the optimal solution and the worst solution is as follows:

[0039]

[0040] Where: is the distance between the evaluation object and the optimal solution, is the distance between the evaluation object and the worst solution;

[0041] 4.4) The relative closeness is calculated based on the distance between each evaluation object and the optimal solution and the worst solution. The closer each evaluation object is to the optimal solution, the higher the development potential of the industrial category. The closer each evaluation object is to the worst solution, the worse the development potential of the industrial category. i The calculation formula is as follows:

[0042]

[0043] 5) Obtain the city construction industry development industry type

[0044] According to K i The different evaluation objects are ranked according to the size of the values, and the industrial categories in the first half of the ranking constitute the dominant industries for urban construction and industrial development, and the industrial categories in the second half constitute the non-dominant industries.

[0045] The carbon benefits of the leading and non-leading industries in the urban construction industry are calculated respectively. The carbon benefit score calculation formula is as follows:

[0046]

[0047] C i =E i ×EF j (14)

[0048]

[0049] Where: CE i is the carbon efficiency score of the ith industrial sector, ICE i is the carbon benefit of the ith industrial sector, W i is the revenue of the ith industrial sector, C i is the carbon emissions of the ith industrial sector, E i is the comprehensive energy consumption value of the i-th industrial sector, EF j ICE is the carbon emission factor corresponding to the converted energy in the industry's comprehensive energy consumption value. i0 is the median carbon benefit of the ith industrial sector in cities across the country, ICE imax is the optimal carbon benefit of the i-th industrial category in cities across the country. i When the calculation structure is less than zero, it is directly assigned to 0;

[0050] Industries with carbon efficiency scores below 40 are classified as eliminated, industries with carbon efficiency scores above 80 are classified as encouraged, and industries with carbon efficiency scores between 40 and 80 are classified as restricted. According to the structure of "industry dominance-industry category", each industry is given a label P(B ij )={B 11 -Leading Industry-Encouraged Category, B 12 - Dominant Industry - Restricted Category, B 13 -Leading Industry-Elimination Category, B 21 -Non-dominant industry-encouraged category, B 22 - Non-dominant industry - Restricted category, B 23 - non-dominant industries-elimination categories}, forming an urban construction industrial category set T3 with industrial classification labels, which is transmitted to the industrial carbon reduction technology path generation module.

[0051] The industrial carbon reduction technology path generation module, by searching policy documents, sorts out six major industrial carbon reduction measures and their corresponding carbon reduction technology types, namely, green product substitution production, industrial infrastructure construction carbon reduction, industrial production process carbon reduction path design, resource recycling, industrial substitution and exit policy, to form an industrial carbon reduction measure set T4. A decision tree model is constructed based on the industrial classification labels in set T3 and the carbon reduction measure descriptions in the industrial carbon reduction measure set T4, and then the industrial carbon reduction measures are matched to form a composition of various types of industrial carbon reduction measures for low-carbon city construction. Carbon reduction technologies suitable for each carbon reduction measure are selected from the carbon reduction technology library for traversal and combination, and the carbon reduction technology paths of each industrial type are assigned labels P(B) based on the economic cost and carbon reduction effect of each carbon reduction technology path. ij C ijk )={B 11 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 12 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 13 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 21 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 22 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 23 -C ijk -serial number-carbon reduction cost-carbon reduction amount}, forming a carbon reduction technology path set T5 of various types of industries with labels, and transmitting it to the carbon reduction technology path optimization module.

[0052] The carbon reduction technology path optimization module classifies the paths according to the labels of the paths in the carbon reduction technology path set T5 of the above-mentioned various types of industries according to the industrial type, and then optimizes the carbon reduction technology path for each industrial type respectively, and obtains the comprehensive evaluation score M of the carbon reduction path of the urban construction industry according to the expected weight coefficient of the carbon reduction cost and carbon reduction effect set by the decision maker's own needs. ij The difference between economic efficiency and carbon reduction effect D ij , the comprehensive evaluation score calculation formula is:

[0053]

[0054] M ij =X EF ER′ ij +(1-X BF )C′ ij (18)

[0055] D ij =C′ iE -ER′ ij (19)

[0056] Where: M ij is the comprehensive evaluation score of j carbon reduction technology pathways for type i industry; D ij is the difference between the economic efficiency and carbon reduction effect of j carbon reduction technology paths of type i industry; ER′ ij C′ is the amount of carbon dioxide reduced by the j carbon reduction technology pathways of the i-type industry within the applicable range after normalization, with a value range of 0-1; ij is the normalized carbon reduction cost of the j carbon reduction technology pathways of the i-type industry within the applicable range, with a value range of 0-1; ER jh C is the amount of carbon dioxide reduced by j carbon reduction technology pathways of type i industry within the applicable range; ij is the carbon reduction cost of j carbon reduction technology paths of type i industry within the applicable range; X EF ER is the expected weight coefficient of carbon reduction determined by decision makers based on their own needs, with a value range of 0-1; i,max and ER i,min C is the maximum and minimum value of the amount of carbon dioxide reduced by the carbon reduction technology path of type i industry within the applicable range; i,max and c i,min The maximum and minimum carbon reduction costs of the carbon reduction technology path for type i industry within the available range.

[0057] In view of the fact that cities hope to have lower economic efficiency and better carbon reduction effect, the comprehensive evaluation score maximization MAX{M ij} and the difference between economic efficiency and carbon reduction effect is minimized MIN{Dij} is the optimization target, and the result that appears most frequently in the 100 calculation results of the NSGA-II algorithm is taken as the optimal solution M with the comprehensive evaluation score. best By calculating the carbon reduction technology path and optimal solution M for each industrial type best The relative closeness F ij , and its calculation formula is as follows:

[0058]

[0059] Where: F ij M is the relative closeness between j carbon reduction technology paths of type i industry and the optimal solution; best is the optimal solution for the comprehensive evaluation score of type i of industry; M ij is the comprehensive evaluation score of j carbon reduction technology pathways for type i industry.

[0060] According to the relative closeness F ij , sort the carbon reduction technology paths of each industrial type, output the industrial carbon reduction technology path that ranks first under each industrial type, and finally form the optimal industrial carbon reduction technology path for urban construction.

[0061] The present invention also includes a computer-readable storage medium and a computer device, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the function of the urban construction industry carbon reduction path optimization system is realized. The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the function of the urban construction industry carbon reduction path optimization system is realized.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] 1. The present invention establishes a model consisting of four modules: an industrial carbon reduction object evaluation index acquisition module, an industrial carbon reduction object classification module, an industrial carbon reduction technology path generation module, and a carbon reduction technology path optimization module. The genetic algorithm is used for industries within the boundary range of urban construction. The city constructs a comprehensive evaluation function based on its own development characteristics to obtain the optimal carbon reduction technology path for each industrial type, and finally forms a low-carbon city construction industrial field carbon reduction technology path with the best comprehensive economic and carbon reduction performance. This path can fully reflect the city's low-carbon development advantages, characteristics and carbon reduction goals, and facilitate the city to achieve its carbon reduction goals.

[0064] 2. The present invention can formulate the direction of industrial development in combination with local resource endowments: The method of the present invention obtains industrial development potential evaluation indicators based on the current research status, divides urban construction industries into dominant industries and non-dominant industries, and can solve the problem of unclear industrial development goals when building low-carbon cities. Combined with the city's carbon benefit scores, each industrial category is further divided into encouraged, restricted and eliminated categories, and differentiated industrial carbon reduction technology paths are formed in combination with the characteristics of each industrial category to solve the problem of unclear carbon reduction paths in the urban construction industry.

[0065] 3. The system needs to cover the following functions: First, identify the key points of industrial carbon reduction in urban construction, so as to obtain the evaluation indicators of industrial carbon reduction objects and ensure the pertinence of the evaluation indicators; second, develop an industrial classification strategy that combines urban resource endowments and industrial development goals, and assign classification labels to urban construction industrial development objects; third, based on the classification labels of urban construction industrial development objects, generate carbon reduction technology paths corresponding to each industrial type; fourth, based on the economic and carbon reduction effects of the carbon reduction path, combined with the city's low-carbon development goals, obtain the optimal carbon reduction technology path under each industrial type, and finally form the optimal urban construction industrial carbon reduction technology path. By constructing an urban construction industrial carbon reduction path optimization method based on environmental and economic coupling benefits that can cover the above functions, it can better provide strong technical support for low-carbon city construction, promote green and sustainable development in the urban industrial field, and solve the problem of unclear development and carbon reduction paths in the urban construction industrial field.

[0066] 4. Each module in the urban construction industry carbon reduction path acquisition system of the present invention can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. The computer-readable storage medium stores a computer program, which can be used to execute Figure 1 Provides a carbon reduction pathway and planning method. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 An example diagram for optimizing the carbon reduction path for urban construction industry based on the environmental and economic coupling benefits provided in the embodiment.

[0068] Figure 2 This is a judgment logic diagram of the decision tree model in the industrial carbon reduction path generation module provided in the embodiment. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. The following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but only represents selected embodiments of the present invention.

[0070] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] The present invention provides a system for optimizing and determining the carbon reduction path of urban construction industry, which is implemented by constructing the following modules:

[0072] 1) Industrial carbon reduction object evaluation index acquisition module: used to obtain evaluation indicators that can reflect the future development benefits of urban industry and transmit them to the industrial carbon reduction object classification module;

[0073] 2) Industrial carbon reduction object classification module: used to establish a classification model to classify urban construction industrial carbon reduction objects, match classification labels for each urban construction industrial carbon reduction object, and transmit them to the specific industrial carbon reduction technology path generation module;

[0074] 3) Industrial carbon reduction technology path generation module: used to match carbon reduction strategies and carbon reduction technologies based on the classification labels of industrial carbon reduction objects in low-carbon city construction through a decision tree model, obtain a set of carbon reduction technology paths based on the classification results of industrial carbon reduction objects in low-carbon city construction, and transmit it to the carbon reduction technology path selection and optimization module;

[0075] 4) Carbon reduction technology path optimization module: used to optimize specific carbon reduction technology paths according to the city’s carbon reduction goals and needs, and obtain the optimal carbon reduction path for the low-carbon city construction industry.

[0076] like Figure 1 As shown, each of the above modules is further explained.

[0077] The 1) industrial carbon reduction object evaluation index acquisition module, in the specific application implementation, the specific processing steps of obtaining the industrial carbon reduction object evaluation index include:

[0078] (1) Using the keyword "industrial development foundation" to search the full text of literature published in all academic fields, screen out X relevant literature, perform keyword analysis using CiteSpace software, and eliminate keywords with a frequency of less than q. The keyword frequency can be set by the user according to his or her own needs for the number of evaluation indicators.

[0079] (2) Extract and clean the context information covering the remaining keywords through structured data processing functions and text extraction functions to obtain the evaluation indicators corresponding to each keyword And context information, for those who do not obtain evaluation indicators Keywords are used as supplementary search terms to conduct literature search again and supplement the missing evaluation indicators. Form the basic vocabulary set T1 for industrial development.

[0080] (3) Combine the context information corresponding to each keyword and obtain the word vector of the keyword by using a pre-trained word vector model (such as Word2Vec, GloVe). In the specific application implementation, the Word2Vec word embedding model can be used for calculation. The context information corresponding to each keyword is used as a data set to train one's own Word2Vec model to ensure the model's ability to understand the keyword and finally output the corresponding word vector.

[0081] (4) The word set T1 is matched with the three dimensions of industrial foundation, economic proportion and environmental impact for similarity. The calculation method is:

[0082]

[0083] Among them, R(x) is the similarity matching value, is the text embedding vector extracted from the i-th keyword in T1 after training; B j The text embedding vectors extracted after training for industrial base, economic share, and environmental impact respectively;

[0084] (5) According to the matching results, the evaluation index of each keyword is Classify into corresponding sections and give labels P(A ij )={A 1j -Industrial Base-Indicator Name, A 2j -Economic proportion-Indicator name, A 3j - environmental impact - indicator name}, forming the industrial evaluation indicator set T2, and transmitting it to the industrial carbon reduction object classification module.

[0085] In order to make the result presentation clearer, this embodiment briefly obtains the evaluation indicators based on the above steps, as shown in Table 1. It should be noted that this part is for reference only, and the user needs to refer to the above steps to obtain specific evaluation indicators.

[0086] Table 1 Industrial evaluation index set T2

[0087]

[0088] In the 2) industrial carbon reduction object classification module, combined with the urban land types classified in the "Urban and Rural Land Classification and Planning and Construction Land Standards" GB50137, the urban construction industrial carbon reduction objects applicable to the present invention are locked into the manufacturing category, and the urban construction industrial category ranking is obtained by establishing an entropy weight TOPSIS model. The dominant industries and non-dominant industries of urban construction industrial development are formed based on the ranking, and corresponding industrial type labels are assigned. Based on the carbon benefit scores of industrial categories in each set, the industry is further divided into encouraged, restricted and eliminated categories to form an urban construction industrial category set T3 with industrial classification labels, and transmitted to the industrial carbon reduction technology path generation module.

[0089] The specific steps of establishing the entropy weight TOPSIS model to obtain the ranking of urban construction industrial categories and form a set of urban construction industrial categories T3 with industrial classification labels include:

[0090] 2.1) Constructing a decision matrix

[0091] A decision matrix is ​​constructed for m manufacturing categories and n evaluation indicators in the industrial development evaluation indicator set T3 of each city. The evaluation object set is A = (A1, A2, ..., A m ), the evaluation index set is T3 = (T1, T2, ..., T n ), A i The corresponding value of each indicator in T3 is X ij (i=1,2,…,m;j=1,2,…,n), forming a decision matrix:

[0092]

[0093] 2.2) Standardization of evaluation indicators

[0094] The evaluation indicators include positive indicators and negative indicators. For negative indicators, take X mn The reciprocal of the negative indicator is converted into a positive indicator and substituted into the decision matrix to replace X mn , and obtain the standardized matrix.

[0095] 2.3) Determine the weight of evaluation index using entropy weight method

[0096] 2.3.1) Use the power coefficient method to make the standardized matrix dimensionless:

[0097]

[0098] 2.3.2) Calculate the entropy value based on the proportion of m evaluation objects under n evaluation indicators in the dimensionless data:

[0099]

[0100] Where: E j is the entropy value of evaluation index j, d ij is the proportion of the i-th evaluation object under the j-th evaluation index;

[0101] 2.4) Calculate the index weight W based on the dimensionless processing results and entropy value j :

[0102]

[0103] 2.4) Establishing TOPSIS model based on entropy weight

[0104] 2.4.1) Construct a weighted matrix based on the dimensionless processed data and entropy value. The calculation formula of the weighted matrix Z is as follows:

[0105] Z ij =W j ×D ij (6)

[0106] Z=[Z ij ] m×n (7)

[0107] 2.4.2) Determine the optimal solution Z in the weighted matrix for each evaluation index + and the worst solution Z - :

[0108]

[0109] Where: Z + is the optimal solution, is the maximum value of each column, Z - is the optimal solution, is the minimum value of each column, j = 1, 2, ..., n;

[0110] 2.4.3) Obtain the distance between each evaluation object and the optimal solution and the worst solution. The distance calculation formula between the evaluation object and the optimal solution and the worst solution is as follows:

[0111]

[0112] Where: is the distance between the evaluation object and the optimal solution, is the distance between the evaluation object and the worst solution;

[0113] 2.4.4) The relative closeness is calculated based on the distance between each evaluation object and the optimal solution and the worst solution. The closer each evaluation object is to the optimal solution, the higher the development potential of the industrial category. The closer each evaluation object is to the worst solution, the worse the development potential of the industrial category. i The calculation formula is as follows:

[0114]

[0115] 2.5) Obtain the city construction industry development industry type

[0116] According to K i The different evaluation objects are ranked according to the size of the values, and the industrial categories in the first half of the ranking constitute the dominant industries for urban construction and industrial development, and the industrial categories in the second half constitute the non-dominant industries.

[0117] The carbon benefits of the leading and non-leading industries in the urban construction industry are calculated respectively. The carbon benefit score calculation formula is as follows:

[0118]

[0119] C i =E i ×EF j (14)

[0120]

[0121] Where: CE i is the carbon efficiency score of the ith industrial sector, ICE i is the carbon benefit of the ith industrial sector, W i is the revenue of the ith industrial sector, C i is the carbon emissions of the ith industrial sector, E i is the comprehensive energy consumption value of the i-th industrial sector, EF j ICE is the carbon emission factor corresponding to the converted energy in the industry's comprehensive energy consumption value. i0 is the median carbon benefit of the ith industrial sector in cities across the country, ICE imax is the optimal carbon benefit of the i-th industrial category in cities across the country. i When the calculation structure is less than zero, it is directly assigned to 0;

[0122] Industries with carbon efficiency scores below 40 are classified as eliminated, industries with carbon efficiency scores above 80 are classified as encouraged, and industries with carbon efficiency scores between 40 and 80 are classified as restricted. According to the structure of "industry dominance-industry category", each industry is given a label P(B ij )={B 11 -Leading Industry-Encouraged Category, B 12 - Dominant Industry - Restricted Category, B 13 -Leading Industry-Elimination Category, B 21 -Non-dominant industry-encouraged category, B 22 - Non-dominant industry - Restricted category, B 23 - non-dominant industry - elimination category}, forming an urban construction industrial category set T3 with industrial classification labels, which is transmitted to the industrial carbon reduction technology path generation module. In order to make this embodiment describe the present invention more clearly, this embodiment combines relevant literature and reports to prepare a classification result of urban construction industrial categories (see Table 2 for details) as an illustration.

[0123] Table 2 Urban construction industry categories with industrial classification labels

[0124]

[0125] In the 3) industrial carbon reduction technology path generation module, six major industrial carbon reduction measures and their corresponding carbon reduction technology types, including green product substitution production, industrial infrastructure construction carbon reduction, industrial production process carbon reduction path design, resource recycling, industry substitution and exit policy, were sorted out by searching policy documents to form an industrial carbon reduction measures set T4.

[0126] Among them, a decision tree model is constructed based on the industrial classification labels in set T3 and the description of carbon reduction measures in industrial carbon reduction measures set T4. The specific detailed process is as follows: Figure 2 As shown. The obsolete types under the main industrial types adopt green product substitution production, among which the substituted green products are selected from the same type of industries in the encouraged category of the national industrial adjustment catalog for substitution production, and their production still needs to meet the following judgment conditions; the obsolete types under the non-main industrial types stop production and implement the exit policy within the exit time limit specified by the city; all types of industries need to implement industrial infrastructure construction to reduce carbon; industries with carbon emissions generated by the use of raw materials and fuels in the production process accounting for ≥50% need to design a carbon reduction path based on their industrial production processes; industries whose comprehensive utilization rate of solid waste and industrial water recycling rate in the production process do not meet the E and F values ​​given in the national carbon peak action plan implement resource recycling and utilization transformation; when the industry belongs to the restricted category, its carbon benefit is calculated, and the industry with a carbon benefit of less than 60 points implements an industrial substitution policy, among which the alternative industry type is selected from the encouraged category of the industrial adjustment catalog; the final output is the carbon reduction measures matched by each industry to form its specific carbon reduction path.

[0127] Then, industrial carbon reduction measures are matched to form various types of industrial carbon reduction measures for low-carbon city construction. Carbon reduction technologies suitable for each carbon reduction measure are selected from the carbon reduction technology library for traversal and combination. The carbon reduction technology types of each carbon reduction measure are shown in Table 3.

[0128] Table 3 Composition of carbon reduction technology types under various carbon reduction measures

[0129]

[0130]

[0131] The carbon reduction technology paths of various industrial types are given labels P(B ij C ijk )={B 11 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 12 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 13 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 21 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 22 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 23 -C ijk -sequence number-carbon reduction cost-carbon reduction amount}, forming a carbon reduction technology path set T5 of various types of industries with labels, and transmitting it to the carbon reduction technology path optimization module, where the calculation formulas for carbon reduction amount and carbon reduction cost are:

[0132] ER i =ES i ×EF e ×EA

[0133] Where: ER i is the amount of carbon dioxide reduced by the i technology path within the applicable range; ES i Energy saving brought by using i technology path; EF e is the CO2 emission factor of the e-th energy source, t / GJ; EA is the total amount of units that can be constructed and used in the i-th technology path.

[0134]

[0135] Where: C i,y is the unit emission reduction cost of the i-th technology path in the yth year, 10,000 yuan / t; IC i,y is the investment and maintenance cost of technology path i in year y, RMB 10,000; ERi is the CO2 emission reduction potential resulting from using technology pathway i.

[0136] It should be made clear that the above-mentioned carbon emission reduction technology paths have their own calculation methods for carbon reduction amounts and carbon reduction costs, which are for reference only. When applying them, users should formulate a specific set of carbon reduction technology paths based on actual conditions.

[0137] In the carbon reduction technology path optimization module, the specific steps are as follows:

[0138] (1) According to the labels of each path in the carbon reduction technology path set T5 of each type of industry, they are classified according to the industrial type, and then the carbon reduction technology path optimization is performed for each industrial type.

[0139] (2) Based on the carbon reduction cost and expected weight coefficient of carbon reduction effect set by the decision makers themselves, the comprehensive evaluation score M of the carbon reduction path of urban construction industry is obtained. ij The difference between economic efficiency and carbon reduction effect D ij , the comprehensive evaluation score calculation formula is:

[0140]

[0141] M ij =X EF ER′ ij +(1-X EF )C′ ij (18)

[0142] D ij =C′ ij -ER′ ij (19)

[0143] Where: M ij is the comprehensive evaluation score of j carbon reduction technology pathways for type i industry; D ij is the difference between the economic efficiency and carbon reduction effect of j carbon reduction technology paths of type i industry; ER′ ij C′ is the amount of carbon dioxide reduced by the j carbon reduction technology pathways of the i-type industry within the applicable range after normalization, with a value range of 0-1; ij is the normalized carbon reduction cost of the j carbon reduction technology pathways of the i-type industry within the applicable range, with a value range of 0-1; ER ij C is the amount of carbon dioxide reduced by j carbon reduction technology pathways of type i industry within the applicable range; ij is the carbon reduction cost of j carbon reduction technology paths of type i industry within the applicable range; X EF ER is the expected weight coefficient of carbon reduction determined by decision makers based on their own needs, with a value range of 0-1; i,max and ERi,min C is the maximum and minimum value of the amount of carbon dioxide reduced by the carbon reduction technology path of type i industry within the applicable range; i,max and C i,min The maximum and minimum carbon reduction costs of the carbon reduction technology path for type i industry within the available range.

[0144] (3) Select the comprehensive evaluation score that maximizes MAX{M ij} and the difference between economic efficiency and carbon reduction effect is minimized MIN{D ij} is the optimization goal, and the NSGA-II algorithm is used to obtain the optimal solution M for the comprehensive evaluation score. best .

[0145] (4) By calculating the carbon reduction technology path and optimal solution M for each industrial type best The relative closeness F ij , and its calculation formula is as follows:

[0146]

[0147] Where: F ij M is the relative closeness between j carbon reduction technology paths of type i industry and the optimal solution; best is the optimal solution for the comprehensive evaluation score of type i of industry; M ij is the comprehensive evaluation score of j carbon reduction technology pathways for type i industry.

[0148] (5) According to the relative closeness F ij , sort the carbon reduction technology paths of each industrial type, output the industrial carbon reduction technology path that ranks first under each industrial type, and finally form the optimal industrial carbon reduction technology path for urban construction.

[0149] In order to make the description of this embodiment clearer, it is proposed to encourage the leading industry B 11 The optimization of carbon reduction technology paths was carried out. 50 carbon reduction technology paths were randomly generated through the python function. The expected weight coefficient of the city's carbon reduction was set to 0.65. Some carbon reduction technology paths and their parameters are shown in Table 4:

[0150] Table 4 Carbon reduction technology pathways and parameters

[0151]

[0152]

[0153] The population capacity of the NSGA-II algorithm is set to 100, the number of iterations is set to 150, and the mode of the 100 calculation results is selected as the optimal solution M of the carbon reduction technology path. best, because the algorithm maintains a diversified solution set in the solution process, the calculated value M best It is not unique. Users can reduce the fluctuation between output results by increasing the group capacity and the number of iterations. The carbon reduction technology path and parameters can be calculated based on the parameters in Table 4 as shown in Table 5. ij , sort the carbon reduction technology paths of each industrial type (details are shown in Table 5 below, this example only shows the top 20 carbon reduction technology paths), and get the encouraged category B of the leading industry 11 The optimal carbon reduction technology path is carbon reduction technology path 33, which outputs the optimal carbon reduction technology path for each industrial type, and ultimately forms the optimal industrial carbon reduction technology path for urban construction.

[0154] Table 5 Carbon reduction technology pathways and parameters

[0155]

[0156]

[0157] In summary, decision makers evaluate and judge whether the preferred carbon reduction technology path is applicable based on their own energy structure, technology level and economic conditions. If the preferred path is not applicable, the decision makers will further select appropriate alternative paths based on the ranking of the carbon reduction technology paths. Secondly, after determining the final carbon reduction technology path, it will be implemented in the corresponding manufacturing industry category, and the carbon reduction effect will be continuously monitored and evaluated in real time, and optimized and adjusted based on the feedback results. At the same time, each manufacturing industry category should ensure the continuous improvement of carbon reduction measures through measures such as equipment transformation, process optimization and carbon emission monitoring. Finally, each manufacturing industry category needs to strengthen employee training, promote the concept of green production, and enhance social responsibility and brand image through transparent carbon emission reports and green certification, so as to achieve sustainable development goals. This method can flexibly respond to the actual needs of different manufacturing industries and ensure the effectiveness and long-term sustainability of carbon reduction measures.

[0158] It will be appreciated by those skilled in the art that the above-described embodiment system is accomplished by instructing the relevant hardware through a computer program, and the computer program may be stored in a non-volatile computer-readable storage medium, and the computer program includes the system of the above-described embodiment. Any reference to memory, storage, database, or other medium used may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. As an illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0159] The present invention classifies industrial categories except the mining industry in combination with the characteristics of urban industrial development, formulates differentiated carbon reduction technology paths based on each industrial type, and conducts path optimization work for each industrial type based on the economic benefits and carbon reduction effects of the path combined with the urban development goals, and finally obtains the optimal carbon reduction path for urban construction industry based on the environmental and economic coupling benefits. The implementation of the present invention can combine the local industrial development characteristics and carbon reduction goals, effectively solve the problem of unclear industrial carbon reduction paths in the current urban construction process, and provide cities with urban construction industrial carbon reduction paths that are in line with urban development policies while ensuring urban economic development.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A system for optimizing and determining carbon reduction paths for urban construction industries, characterized in that: It includes the industrial carbon reduction object evaluation index acquisition module, the industrial carbon reduction object classification module, the industrial carbon reduction technology path generation module and the carbon reduction technology path optimization module; The optimization system selects the comprehensive evaluation score to maximize MAX{M ij } and the difference between economic efficiency and carbon reduction effect is minimized MIN{D ij } is the optimization target, and the result that appears most frequently in the 100 calculation results of the NSGA-II algorithm is taken as the optimal solution M with the comprehensive evaluation score. best By calculating the carbon reduction technology path and optimal solution M for each industrial type best The relative closeness F ij , and its calculation formula is: Where: F ij M is the relative closeness between j carbon reduction technology paths of type i industry and the optimal solution; best is the optimal solution for the comprehensive evaluation score of type i of industry; M ij is the comprehensive evaluation score of j carbon reduction technology pathways for type i industry; According to the relative closeness F ij , sort the carbon reduction technology paths of each industrial type, output the top industrial carbon reduction technology paths under each industrial type, and finally form the optimal industrial carbon reduction technology path for urban construction; in, The industrial carbon reduction object evaluation index acquisition module is used to obtain evaluation indicators that can reflect the future development benefits of urban industry and transmit them to the industrial carbon reduction object classification module; The industrial carbon reduction object classification module is used to establish a classification model to classify urban construction industrial carbon reduction objects, match classification labels for each urban construction industrial carbon reduction object, and transmit them to the specific industrial carbon reduction technology path generation module; The industrial carbon reduction technology path generation module is used to match carbon reduction strategies and carbon reduction technologies according to the classification labels of industrial carbon reduction objects in low-carbon city construction through a decision tree model, obtain a set of carbon reduction technology paths for the classification results of industrial carbon reduction objects in low-carbon city construction, and transmit it to the carbon reduction technology path selection and optimization module; The carbon reduction technology path optimization module is used to combine the background characteristics of the carbon reduction path with the city's low-carbon development goals, so as to obtain the optimal carbon reduction technology path under each industrial type, and finally form the optimal urban construction industrial carbon reduction technology path.

2. According to claim 1, the system for optimizing and determining carbon reduction paths for urban construction industry is characterized in that: The industrial carbon reduction object evaluation index acquisition module uses CiteSpace software to perform keyword analysis on the literature related to current industrial development research, removes keywords with a frequency of less than q, and combines the context information of the remaining keywords to obtain the corresponding word vectors and evaluation indicators For keywords that cannot directly obtain evaluation indicators in the text, the missing evaluation indicators are supplemented through literature search The industrial development basic word set T1 is formed, and the word set T1 is matched with the three dimensions of industrial foundation, economic proportion and environmental impact for similarity, and the evaluation index of each keyword is calculated according to the matching results. Classify into corresponding sections and give labels P(A ij )={A 1j -Industrial Base-Indicator Name, A 2j -Economic proportion-Indicator name, A 3j - environmental impact - indicator name}, forming the industrial evaluation indicator set T2, and transmitting it to the industrial carbon reduction object classification module. The calculation method is: Among them, R(x) is the similarity matching value, is the text embedding vector extracted from the i-th keyword in T1 after training; B j The text embedding vectors are extracted after training for industrial base, economic share and environmental impact respectively.

3. According to claim 1, the system for optimizing and determining carbon reduction paths for urban construction industry is characterized in that: In the industrial carbon reduction object classification module, combined with the urban land types classified in the "Urban and Rural Land Classification and Planning and Construction Land Standards" GB50137, the urban construction industrial carbon reduction objects are locked into the manufacturing category. According to the corresponding evaluation indicators in the industrial evaluation indicator set T2, the ranking of urban construction industrial categories is obtained by establishing an entropy weight TOPSIS model. Based on the ranking, each category is divided into leading industries and non-leading industries in urban construction industrial development, and corresponding industrial type labels are assigned. According to the carbon benefit scores of each industrial category, the industry is further divided into encouraged, restricted and eliminated categories, forming an urban construction industrial category set T3 with industrial classification labels, and transmitted to the industrial carbon reduction technology path generation module.

4. According to claim 3, the urban construction industry carbon reduction path optimization system is characterized in that: The specific steps of establishing the entropy weight TOPSIS model to obtain the ranking of urban construction industrial categories and form an urban construction industrial category set T3 with industrial classification labels include: 1) Build a decision matrix A decision matrix is ​​constructed for m objects in the manufacturing industry category and n evaluation indicators in the industrial development evaluation indicator set T2 of each city. The evaluation object set is A = (A1, A2, ..., A m ), the evaluation index set is T2 = (T1, T2, ..., T n ), A i The corresponding value of each indicator in T2 is X ij (i=1,2,…,m;j=1,2,…,n), forming a decision matrix: 2) Standardization of evaluation indicators The evaluation indicators include positive indicators and negative indicators. For negative indicators, take X mn The reciprocal of the negative indicator is converted into a positive indicator and substituted into the decision matrix to replace X mn , obtain the standardized matrix; 3) Determine the weight of evaluation indicators using entropy weight method 3.1) Use the power coefficient method to make the standardized matrix dimensionless: 3.2) Calculate the entropy value based on the proportion of m evaluation objects under n evaluation indicators in the dimensionless data: Where: E j is the entropy value of evaluation index j, d ij is the proportion of the i-th evaluation object under the j-th evaluation index; 3.3) Calculate the index weight W based on the dimensionless processing results and entropy value j : 4) Establishing TOPSIS model based on entropy weight 4.1) Construct a weighted matrix based on the dimensionless processed data and entropy value. The calculation formula of the weighted matrix Z is as follows: WITH ij =In j ×D ij (6) From=[From ij ] m×n (7) 4.2) Determine the optimal solution Z in the weighted matrix for each evaluation index + and the worst solution Z - : Where: Z + is the optimal solution, is the maximum value of each column, Z - is the optimal solution, is the minimum value of each column, j = 1, 2, ..., n; 4.3) Obtain the distance between each evaluation object and the optimal solution and the worst solution. The distance calculation formula between the evaluation object and the optimal solution and the worst solution is as follows: Where: is the distance between the evaluation object and the optimal solution, is the distance between the evaluation object and the worst solution; 4.4) The relative closeness is calculated based on the distance between each evaluation object and the optimal solution and the worst solution. The closer each evaluation object is to the optimal solution, the higher the development potential of the industrial category. The closer each evaluation object is to the worst solution, the worse the development potential of the industrial category. i The calculation formula is as follows: 5) Obtain the city construction industry development industry type According to K i Different evaluation objects are ranked according to the size of the values, and the industrial categories in the first half of the ranking constitute the dominant industries in urban construction industrial development, and the industrial categories in the second half constitute the non-dominant industries. The carbon benefits of the leading and non-leading industries in the urban construction industry are calculated respectively. The carbon benefit score calculation formula is as follows: C i =And i ×EF j (14) Where: CE i is the carbon efficiency score of the ith industrial sector, ICE i is the carbon benefit of the i-th industrial sector, W i is the revenue of the ith industrial category, C i is the carbon emissions of the ith industrial sector, E i is the comprehensive energy consumption value of the i-th industrial sector, EF j ICE is the carbon emission factor corresponding to the converted energy in the industry's comprehensive energy consumption value. i0 is the median carbon benefit of the ith industrial sector in cities across the country, ICE imax is the optimal carbon benefit value of the i-th industrial category in cities across the country. i When the calculation structure is less than zero, it is directly assigned to 0; Industries with carbon efficiency scores below 40 are classified as eliminated, industries with carbon efficiency scores above 80 are classified as encouraged, and industries with carbon efficiency scores between 40 and 80 are classified as restricted. According to the structure of "industry dominance-industry category", each industry is given a label P(B ij )={B 11 -Leading Industry-Encouraged Category, B 12 - Dominant Industry - Restricted Category, B 13 -Leading Industry-Elimination Category, B 21 -Non-dominant industry-encouraged category, B 22 - Non-dominant industry - Restricted category, B 23 - non-dominant industries-elimination categories}, forming an urban construction industrial category set T3 with industrial classification labels, which is transmitted to the industrial carbon reduction technology path generation module.

5. According to claim 1, the system for optimizing and determining carbon reduction paths for urban construction industry is characterized in that: The industrial carbon reduction technology path generation module, by searching policy documents, sorts out six major industrial carbon reduction measures and their corresponding carbon reduction technology types, namely, green product substitution production, industrial infrastructure construction carbon reduction, industrial production process carbon reduction path design, resource recycling, industrial substitution and exit policy, to form an industrial carbon reduction measures set T4, and constructs a decision tree model based on the industrial classification labels in set T3 and the carbon reduction measures descriptions in the industrial carbon reduction measures set T4, thereby matching industrial carbon reduction measures and forming various types of industrial carbon reduction measures for low-carbon city construction; Select carbon reduction technologies suitable for each carbon reduction measure from the carbon reduction technology library for traversal combination, and assign labels P(B) to the carbon reduction technology paths of each industrial type based on the economic cost and carbon reduction effect of each carbon reduction technology path. ij C ijk )={B 11 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 12 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 13 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 21 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 22 -C ijk -Serial number-Carbon reduction cost-Carbon reduction amount, B 23 -C ijk -serial number-carbon reduction cost-carbon reduction amount}, forming a carbon reduction technology path set T5 of various types of industries with labels, and transmitting it to the carbon reduction technology path optimization module.

6. According to claim 1, the system for optimizing and determining the carbon reduction path of urban construction industry is characterized in that: The carbon reduction technology path optimization module classifies the paths according to the labels of the paths in the carbon reduction technology path set T5 of the above-mentioned various types of industries according to the industrial type, and then optimizes the carbon reduction technology path for each industrial type respectively, and obtains the comprehensive evaluation score M of the carbon reduction path of the urban construction industry according to the expected weight coefficient of the carbon reduction cost and carbon reduction effect set by the decision maker's own needs. ij The difference between economic efficiency and carbon reduction effect D ij , the comprehensive evaluation score calculation formula is: M ij =X EF IS' ij +(1-X EF )C′ ij (18) D ij =C′ ij -IS' ij (19) Where: M ij is the comprehensive evaluation score of j carbon reduction technology pathways for type i industry; D ij is the difference between the economic efficiency and carbon reduction effect of j carbon reduction technology paths of type i industry; ER′ ij C′ is the amount of carbon dioxide reduced by the j carbon reduction technology pathways of the i-type industry within the applicable range after normalization, with a value range of 0-1; ij is the normalized carbon reduction cost of the j carbon reduction technology pathways of the i-type industry within the applicable range, with a value range of 0-1; ER ij C is the amount of carbon dioxide reduced by j carbon reduction technology pathways of type i industry within the applicable range; ij is the carbon reduction cost of j carbon reduction technology paths of type i industry within the applicable range; X EF ER is the expected weight coefficient of carbon reduction determined by decision makers based on their own needs, with a value range of 0-1; i,max and ER i,min C is the maximum and minimum value of the amount of carbon dioxide reduced by the carbon reduction technology path of type i industry within the applicable range; i,max and C i,min The maximum and minimum carbon reduction costs of the carbon reduction technology path for type i industry within the available range.

7. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, a system for optimizing the carbon reduction path of urban construction industry according to any one of claims 1 to 6 is implemented.

8. A computer device, characterized in that: A memory, a processor, and a device stored in the memory and available on the processor A computer program running on a processor, wherein when the processor executes the program, the system for optimizing and determining the carbon reduction path for urban construction industry as claimed in any one of claims 1 to 6 is implemented.

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