Decision-making method and system for reconstruction calculation and updating scheme based on city updating

Abstract

The invention discloses a decision-making method for a reconstruction calculation and updating scheme based on city updating, and the method comprises the following steps: constructing a decision-making index system which comprises a plurality of indexes and corresponding index weight values; evaluation data of a to-be-transformed cell are obtained, the evaluation data are grade evaluation corresponding to the indexes, and the grade evaluation comprises 1-5 grades; and based on the decision index system and the evaluation data, performing evaluation by adopting a fuzzy comprehensive evaluation method, and outputting a transformation decision result. According to the decision-making method, through scientific and systematic evaluation and decision-making processes, the following specific effects can be achieved: the scientificity and accuracy of reconstruction decision-making are improved: a to-be-reconstructed cell is evaluated by constructing a decision-making index system and combining a fuzzy comprehensive evaluation method. Different from traditional subjective judgment, the method can simplify a complex multi-factor decision problem into quantifiable scores and results, and improves scientificity and accuracy of decision.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a decision-making method and system for transformation estimation and renewal scheme based on urban renewal. Background Art

[0002] Urban renewal has become an important part of modern urban development, aiming to resolve the contradiction between old urban areas and modernization needs. As an important part of urban renewal, the renovation of old residential areas is related to people's livelihood, urban space optimization and land value enhancement. However, faced with the contradiction between the urgent need for renovation of a large number of old residential areas and limited funds and time, how to make renovation decisions scientifically and quantitatively has become a major challenge.

[0003] At present, there is a lack of effective quantitative decision-making methods to guide the priority renovation of old urban communities, and it is difficult to comprehensively consider multiple factors such as the current status, location, environment, and comprehensive benefits of the community. Traditional decision-making models are often limited to qualitative analysis and are difficult to adapt to the current needs of refined urban management. Summary of the invention

[0004] In order to overcome the above technical defects, the present invention provides a decision-making method and system for transformation estimation and renewal plan based on urban renewal.

[0005] In order to solve the above problems, the present invention is implemented according to the following technical solutions:

[0006] In a first aspect, the present invention provides a decision-making method for transformation estimation and renewal scheme based on urban renewal, the decision-making method comprising the following steps:

[0007] Constructing a decision-making indicator system, wherein the decision-making indicator system includes multiple indicators and corresponding indicator weight values;

[0008] Acquire evaluation data of the community to be transformed, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades;

[0009] Based on the decision-making index system and the evaluation data, a fuzzy comprehensive evaluation method is used to perform evaluation and output a transformation decision result.

[0010] In combination with the first aspect, the present invention further provides a first specific implementation manner of the first aspect, specifically, the decision-making method further includes:

[0011] Get the transformation potential score for each indicator;

[0012] Calculate the transformation potential of the community to be transformed based on the transformation potential score and the indicator weight value of each indicator;

[0013] The calculation formula of the transformation potential is: In the formula, n is the number of indicators, W i is the indicator weight value of the i-th indicator, Z i Score the transformation potential of the i-th indicator.

[0014] In combination with the first aspect, the present invention further provides a second specific implementation manner of the first aspect, specifically, the decision-making method further includes:

[0015] configuring a transformation potential evaluation, wherein the transformation potential evaluation includes low transformation potential, relatively low transformation potential, medium transformation potential, relatively high transformation potential, and high transformation potential;

[0016] Configuration renewal scheme, the renewal scheme including maintenance and preservation, transformation and upgrading, and demolition and reconstruction;

[0017] Acquire a decision indicator system, wherein the decision indicator system includes a plurality of primary indicators and secondary indicators, and one primary indicator corresponds to at least one secondary indicator;

[0018] Obtain the preference values ​​of the three update schemes corresponding to the transformation potential evaluation of each primary indicator, and construct a transformation potential evaluation-update scheme preference matrix, where the preference values ​​are 1 to 10;

[0019] Based on the indicator weight values ​​of the secondary indicators and the transformation potential evaluation-update scheme preference matrix, the total preference value of each update scheme is calculated;

[0020] The update plan with the largest total preference value is taken as the optimal update plan for the community to be transformed and output.

[0021] In combination with the first aspect, the present invention further provides a third specific implementation of the first aspect. Specifically, the calculation formula of the total preference value of the update scheme is:

[0022] Where P j is the total preference value of the update scheme, n is the number of secondary indicators, j represents the update scheme, j = 1, 2, 3, 1 is maintenance and retention, 2 is transformation and upgrading, 3 is demolition and reconstruction; W i is the indicator weight value of the i-th secondary indicator; H ij is the preference value of each update scheme of the first-level indicator corresponding to the i-th second-level indicator.

[0023] In combination with the first aspect, the present invention further provides a fourth specific implementation manner of the first aspect, specifically, the primary indicators include community status, community location, community environment and comprehensive benefits.

[0024] In combination with the first aspect, the present invention also provides a fifth specific implementation manner of the first aspect. Specifically, the indicator weight value is determined by calling Super Decisions software and using the hierarchical analysis method to determine the indicator weight value of each indicator.

[0025] In a second aspect, the present invention provides a decision-making system for transformation estimation and renewal scheme based on urban renewal, the decision-making system comprising:

[0026] A construction module, which is used to construct a decision-making indicator system, wherein the decision-making indicator system includes multiple indicators and corresponding indicator weight values;

[0027] A first acquisition module is used to acquire evaluation data of the community to be transformed, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades;

[0028] The evaluation module is used to evaluate based on the decision indicator system and the evaluation data using a fuzzy comprehensive evaluation method and output a transformation decision result.

[0029] In combination with the second aspect, the present invention further provides a first specific implementation of the second aspect, specifically, the decision system further includes:

[0030] A second acquisition module is used to obtain a transformation potential score of each indicator;

[0031] A first calculation module, which is used to calculate the transformation potential of the community to be transformed based on the transformation potential score of each indicator and the indicator weight value;

[0032] The calculation formula of the transformation potential is: In the formula, n is the number of indicators, W i is the indicator weight value of the i-th indicator, Z i Score the transformation potential of the i-th indicator.

[0033] In combination with the second aspect, the present invention further provides a second specific implementation of the second aspect, specifically, the decision system further includes:

[0034] A first configuration module, which is used to configure a transformation potential evaluation, wherein the transformation potential evaluation includes low transformation potential, relatively low transformation potential, medium transformation potential, relatively high transformation potential, and high transformation potential;

[0035] A second configuration module, which is used to configure an update plan, wherein the update plan includes maintenance and retention, transformation and upgrading, and demolition and reconstruction;

[0036] A third acquisition module is used to acquire a decision indicator system, wherein the decision indicator system includes a plurality of primary indicators and secondary indicators, and one primary indicator corresponds to at least one secondary indicator;

[0037] A fourth acquisition module is used to obtain the preference values ​​of the three update schemes corresponding to the transformation potential evaluation of each primary indicator, and to construct a transformation potential evaluation-update scheme preference matrix, wherein the preference values ​​are 1 to 10;

[0038] A second calculation module is used to calculate the total preference value of each update scheme based on the indicator weight value of the secondary indicator and the transformation potential evaluation-update scheme preference matrix;

[0039] The output module is used to output the update scheme with the largest total preference value as the optimal update scheme for the cell to be transformed.

[0040] In combination with the second aspect, the present invention further provides a third specific implementation of the second aspect. Specifically, the calculation formula of the total preference value of the update scheme is:

[0041] Where P j is the total preference value of the update scheme, n is the number of secondary indicators, j represents the update scheme, j = 1, 2, 3, 1 is maintenance and retention, 2 is transformation and upgrading, 3 is demolition and reconstruction; W i is the indicator weight value of the i-th secondary indicator; H ij is the preference value of each update scheme of the first-level indicator corresponding to the i-th second-level indicator.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention provides a decision-making method for transformation measurement and renewal scheme based on urban renewal, the decision-making method comprising the following steps: constructing a decision index system, the decision index system comprising multiple indicators and corresponding indicator weight values; obtaining evaluation data of a community to be transformed, the evaluation data being a grade evaluation corresponding to the indicator, the grade evaluation comprising 1 to 5 grades; based on the decision index system and the evaluation data, using a fuzzy comprehensive evaluation method for evaluation, and outputting a transformation decision result.

[0044] The decision-making method of the present invention can bring the following specific effects through scientific and systematic evaluation and decision-making process:

[0045] Improve the scientificity and accuracy of renovation decisions: By building a decision-making index system and combining it with the fuzzy comprehensive evaluation method, the community to be renovated is evaluated. Different from traditional subjective judgment, this method can simplify complex multi-factor decision-making problems into quantifiable scores and results, improving the scientificity and accuracy of decision-making.

[0046] Support multi-level decision-making: This method uses the analytic hierarchy process (AHP) to calculate weights and the fuzzy evaluation method to perform comprehensive scoring. It is suitable for multi-level and complex decision-making problems. This method can provide data support to help decision makers formulate reasonable transformation plans.

[0047] Through a quantitative and data-based decision-making process, this method can better carry out the renovation of old communities and avoid decision-making errors caused by subjective judgment, greatly improving the efficiency and scientificity of decision-making. Through a scientific indicator system and evaluation method, it can rationally allocate urban resources and improve the living environment of residents, which has important social and economic significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings, wherein:

[0049] Figure 1 It is a flow chart of a decision-making method for transformation estimation and renewal scheme based on urban renewal of the present invention;

[0050] Figure 2 This is the calculation method of the index weight value of the present invention. DETAILED DESCRIPTION

[0051] The following specifically illustrates the implementation mode of the present invention in conjunction with the accompanying drawings. The embodiments are provided for illustrative purposes only and cannot be understood as limiting the present invention. The accompanying drawings are provided for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0052] At present, there is a lack of effective quantitative decision-making methods to guide the priority renovation of old urban communities, and it is difficult to comprehensively consider multiple factors such as the current status, location, environment, and comprehensive benefits of the community. Traditional decision-making models are often limited to qualitative analysis and are difficult to adapt to the current needs of refined urban management.

[0053] To this end, the embodiment of the present invention provides a decision-making method for transformation measurement and renewal plan based on urban renewal. The present invention mainly evaluates the community to be transformed by constructing a decision-making index system and combining a fuzzy comprehensive evaluation method. Different from traditional subjective judgment, this method can simplify complex multi-factor decision-making problems into quantifiable scores and results, thereby improving the scientificity and accuracy of decision-making.

[0054] refer to Figure 1 , an embodiment of the present invention provides a flow chart of a method for making a decision on a transformation estimation and renewal plan based on urban renewal. The method can be executed by a decision system for making a transformation estimation and renewal plan based on urban renewal, which can be implemented in the form of hardware and / or software, and which can be configured in an electronic device. Figure 1 As shown, the method includes:

[0055] S100: Constructing a decision indicator system, wherein the decision indicator system includes a plurality of indicators and corresponding indicator weight values.

[0056] S200: Acquire evaluation data of the community to be renovated, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades.

[0057] S300: Based on the decision indicator system and the evaluation data, a fuzzy comprehensive evaluation method is used to perform evaluation and output a transformation decision result.

[0058] This method can better carry out the renovation of old residential areas through a quantitative and data-based decision-making process, avoid decision-making errors caused by subjective judgment, greatly improve decision-making efficiency and scientificity, and rationally allocate urban resources and improve the living environment of residents through a scientific indicator system and evaluation method, which has important social and economic significance. Specifically, each step of the present invention is described in detail.

[0059] S100: Constructing a decision indicator system, wherein the decision indicator system includes a plurality of indicators and corresponding indicator weight values.

[0060] In the present invention, the decision indicator system includes a plurality of primary indicators and secondary indicators, and one primary indicator corresponds to at least one secondary indicator.

[0061] In a specific implementation, the first-level indicators include the current status of the community, the location of the community, the environment of the community and the comprehensive benefits. In one example, the current status of the community reflects the basic physical characteristics and structural conditions of the community, and is an important basis for evaluating whether the community needs to be renovated. The location of the community directly reflects the geographical location of the community and its correlation with the city center and the transportation system, which directly affects the economic and social benefits of its transformation. The community environment reflects the ecology and living environment of the community, embodies the comfort and livability of living, and is a direct factor affecting the quality of life of residents. Comprehensive benefits are to evaluate the possible benefits of transforming the community from the perspective of economic and social benefits, including contributions to community, urban and even regional development.

[0062] In the specific implementation, as shown in Table 1, it is the primary indicator, secondary indicator and the indicator weight value of the secondary indicator of the decision-making indicator system.

[0063] Table 1 Decision-making index system

[0064]

[0065] In the specific implementation, the determination of weights is the key to the study of the decision-making evaluation system for the renovation of old residential areas. The rationality of the weight composition directly affects the accuracy and scientificity of the evaluation results of the renovation of old residential areas. In order to obtain the weight values ​​of the indicators scientifically and effectively, the hierarchical analysis method is used to compare the indicators pairwise, and the judgment matrix is ​​constructed in combination with the 1-9 scale method to judge the relative importance of the indicators.

[0066] In the specific implementation, the indicator weight value is determined by calling Super Decisions software and using the hierarchical analysis method to determine the indicator weight value of each indicator. Figure 2 shown.

[0067] The steps to determine the weights using SD software for hierarchical analysis are as follows:

[0068] (1) Building a hierarchical structure

[0069] Classify the identified decision-making factors for the renovation of old residential areas, arrange them into several levels from high to low according to the affiliation of each factor, and establish the relationship between elements at different levels; start the SD software and enter the main window. Execute the menu command "Design→Cluster→New", and the dialog box for creating an element group will pop up. Type the element group name and its description in the "Name" and "Description" columns respectively. Repeat the above steps to continuously create all groups of the model.

[0070] Execute the menu command "Design→Node→New", and the "ClusterSelector" pops up to select the element group to which the element belongs. At this time, the "NewNodeDialog" dialog box pops up. Enter the element name, description text, font size, etc. in this dialog box to complete the Node creation. Repeat the above steps to create elements in each element group.

[0071] Execute "Design→Nodeconnections" to pop up the "NodeSelector" dialog box, determine the element to create the connection, and then select all affected elements in the next "NodeSelector" dialog box that pops up. Repeat the above steps to establish all connection relationships between elements.

[0072] The AHP model for priority evaluation of renovation of old residential areas was established in SD SuperDecisions software. The control layer of the model includes six decision criteria: the status of the residential area, the location of the residential area, the environment of the residential area, the renovation funds, the comprehensive benefits, and the institutional support. The network layer includes all sub-indicators (Node) in the six indicator groups (Cluster).

[0073] (2) Constructing the judgment matrix

[0074] The importance of each indicator is quantified using a 1-9 classification scale, where 1 to 9 indicates the increasing importance of the indicator compared to other indicators for a certain evaluation criterion, as shown in Table 2

[0075] Table 2 Relative importance scale

[0076]

[0077]

[0078] Establish a judgment matrix between element groups in SD Super Decisions software. Execute the menu command "Assess / Compare→Pairwise Comparisons" to pop up the "Comparisons for Super Decisions Main Window" window, and select the element group "Cluster" / element "Node" in "1.Choose". Enter the expert scores obtained in the preliminary survey into the judgment matrix.

[0079] (3)Consistency test

[0080] After entering the judgment matrix, the right side automatically generates the weight of each element set relative to the criterion element group / element, and gives the consistency test result. "Inconsistency: 0.03638" displayed in "3.Results" is the consistency test result, because 0.03638<0.1 passed the consistency test. All consistency ratios CR<0.1, then the errors are within the acceptable range.

[0081] (4) Solving the indicator weights

[0082] Use SD software to execute the menu command “Computations→Priorities” to solve and generate the weight values ​​of the decision-making indicators for the renovation of old communities, as shown in Table 1.

[0083] S200: Acquire evaluation data of the community to be renovated, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades.

[0084] In a specific implementation, the present invention defines evaluation levels as 1 to 5, where level 1 represents poor indicator evaluation; level 2 represents relatively poor indicator evaluation; level 3 represents average indicator evaluation; level 4 represents relatively good indicator evaluation; and level 5 represents very good indicator evaluation.

[0085] It should be noted that the evaluation level of the evaluation data is used for the fuzzy comprehensive evaluation method, specifically as the comment set Z. Specifically, the evaluation data can be obtained through field investigation, evaluation in combination with relevant national standards, historical data analysis, and surveys of residents in the community to be renovated. It is also possible to conduct in-depth investigations into the pre-renovation status information of the community to be renovated through data collection, field research, and interviews with government experts. For example, the evaluation of quantitative indicators such as volume ratio and building age is mainly based on the collection and collation of previous project information and on-site investigations, and then conduct evaluations.

[0086] It should be noted that the research data of the present invention mainly includes three categories: big data, standard data and small data. Big data includes LBS (Location Based Service) data, map data, GPS (Global Positioning System) data, etc., which can be obtained by querying open maps on the Internet, crawling related software to obtain POI points of interest, etc.; standard data includes statistical data, industry data, etc., which can be downloaded from the website of the National Bureau of Statistics and the website of the Ministry of Housing and Urban-Rural Planning; small data includes interview data, sample survey data, etc., which can be obtained through questionnaires, visits to the communities to be renovated, etc.

[0087] S300: Based on the decision indicator system and the evaluation data, a fuzzy comprehensive evaluation method is used to perform evaluation and output a transformation decision result.

[0088] In specific implementation, the fuzzy evaluation method can solve the different indicator dimensions and fuzziness and uncertainty in the evaluation of the priority of urban old residential reconstruction. In order to improve the accuracy and operability of the evaluation, the evaluation standard of this indicator is established based on literature research, relevant national laws and regulations, and standards. Due to different construction standards in various regions, the specific standards and requirements of the implementing cities shall prevail.

[0089] Specifically, the main steps of the fuzzy comprehensive evaluation method are:

[0090] ①First, establish a set of evaluation indicators:

[0091] Let R = {r1, r2, ... r m} is the m evaluation index of the evaluated object, and m is the number of evaluation indexes. Specifically, the evaluation index is the index of the decision index system.

[0092] ② Determine the evaluation level standard

[0093] Set Z = {z1, z2, ... z n} are n evaluation levels for each evaluation indicator, which are divided into 5 levels, namely the relevant evaluation levels in step S200.

[0094] ③Construct the evaluation matrix B

[0095] First, for the i-th indicator r in the indicator set i (i=1,2,…m) are judged separately by i Self-evaluation phrases: b i =(b i1 , b i2 , …b in ), the evaluation set of m indicators generates a total evaluation matrix B, and the evaluation object determines the fuzzy relationship B from R to Z.

[0096]

[0097] Among them, b ij Represents the i-th index r i Frequency distribution of the jth comment zj.

[0098] ④ Perform fuzzy synthesis and make decisions

[0099] The corresponding multiplication of each single factor's own comment set and evaluation level results in the fuzzy evaluation set of the evaluation object, and then the fuzzy evaluation vectors of each evaluation factor are added to obtain the final score of each evaluation factor. By introducing a weight set, the weight values ​​of m evaluation factors are set to reflect the importance of the single factor to the evaluation object. Then, the weight set and the fuzzy evaluation score of each single factor are combined to obtain the scoring result of each evaluation factor relative to the entire evaluation system.

[0100] Specifically, this technology provides the following examples:

[0101] The fuzzy comprehensive evaluation method is used in the evaluation system of the priority of renovation of old residential areas. There are 34 evaluation indicators under the five criterion level indicators. These indicator factors constitute the factor set in the fuzzy evaluation method. Then, by evaluating the indicator set, a fuzzy relationship is established between the indicator set and the comment set, and the membership of each evaluation indicator is calculated. Then, an overall evaluation is performed based on the membership calculation. The specific evaluation steps are:

[0102] S310: Setting the evaluation target layer set X = old residential area renovation priority evaluation.

[0103] S320: Set the evaluation criteria layer set R = {r1, r2, r3, r4, r5} = {community status, community location, community environment, renovation funds, comprehensive benefits}, and each sub-criteria layer set is represented by Ri (i = 1, 2, 3, 4, 5, 6, 7), which are respectively:

[0104] R1={r 11 , r 12 , r 13 , r 14, r 15 , r 16 , r 17 , r 18 , r 19 , r 110 , r 111} = {construction age, plot ratio, floor area, property structure, safety, illegal construction, building appearance, durability, municipal facilities, complete facilities, public service facilities};

[0105] R2={r 21 , r 22 , r 23 , r 24 , r 25 , r 26 , r 27 = {distance from the community to the core area, road accessibility, public transportation convenience, location and industrial structure, consistency between regional development and overall planning, coordinated promotion of community renovation and district renewal, and integration of community renovation with key projects};

[0106] R3={r 31 , r 32 , r 33} = {green area ratio, air quality, acoustic environment quality};

[0107] R4={r 41 , r 42 , r 43 , r 44 , r 45 , r 46 = {Expected payback period, planned total investment, financial service intensity and quality, national budget support, social capital support, residents' investment}

[0108] R5={r 51 , r 52 , r 53 , r 54 , r 55 , r 56 , r 57 = {Improve social welfare, improve urban appearance, protect historical culture, revitalize culture, expected market value increase, expected use value increase, expected reduction in maintenance costs}

[0109] S330: The evaluation results of each indicator are divided into 5 levels, and the comment set is Z = {z1, z2, z3, z4, z5} = {very good, good, average, poor, bad} = {5, 4, 3, 2, 1}; i It is the score value of each indicator of the community to be renovated.

[0110] S340: Introduce the criterion layer index weight set W = {w1, w2, w3, w4, w5} and the absolute weight set Wi (i = 1, 2, 3, 4, 5) of each sub-criterion layer, which are respectively:

[0111] W1={w11, w12, w13, w14, w15, w16, w17, w18, w19, w110, w111};

[0112] W2={w21, w22, w23, w24, w25, w26, w27};

[0113] W3 = {w31, w32, w33};

[0114] W4={w41, w42, w43, w44, w45, w46};

[0115] W5={w51, w52, w53, w54, w55, w56, w57}.

[0116] It can be understood that the criterion layer indicator weight set is the set of indicator weight values ​​of the secondary indicators.

[0117] S350: The weight of each factor is W n ={n 11 , n 12 ,…n aj}, then the fuzzy evaluation model is: T = W n OR n , where O represents a composite operator. This paper uses the ordinary matrix multiplication method for calculation.

[0118] S360: Then, through the fuzzy coincidence operation formula T=WOR, the final evaluation value is obtained according to the maximum membership function principle.

[0119] S370: The higher the T value, the higher the urgency and importance of the renovation of the community to be renovated, the higher the priority, and the more priority should be given to renovation.

[0120] Evaluation value T Decision results T＞3.5 Priority transformation 2.5＜T＜3.5 Can be transformed T＜2.5 Postponement of renovation

[0121] Based on the above steps, the present invention together constitutes a decision-making method for the renovation of old residential areas based on urban renewal, which ensures the scientificity and accuracy of the decision-making from the construction of the indicator system to data collection and comprehensive evaluation.

[0122] In a preferred implementation, the decision-making method further includes:

[0123] S10: Obtain a transformation potential score for each indicator.

[0124] In the specific implementation, the transformation potential score Zi of the indicator takes values ​​in the range of [0, 10]. When Zi belongs to [0, 2], the transformation potential is low; when Zi belongs to (2, 4], the transformation potential is low; when Zi belongs to (4, 6], the transformation potential is medium; when Zi belongs to (6, 8], the transformation potential is high; when Zi belongs to (8, 10], the transformation potential is high.

[0125] In specific implementation, the transformation potential score of each indicator can be obtained through expert scoring method, investigation, multi-indicator comprehensive evaluation method, etc., and the transformation potential score of each indicator is obtained and stored for later use.

[0126] S20: Calculating the transformation potential of the community to be transformed based on the transformation potential score of each indicator and the indicator weight value;

[0127] The calculation formula of the transformation potential is: In the formula, n is the number of indicators, W i is the indicator weight value of the i-th indicator, Z i Score the transformation potential of the i-th indicator.

[0128] In the specific implementation, the sum of the products of the renovation potential scores Zi of multiple secondary indicators and the corresponding weights Wi is the output value of the renovation potential value of the community to be renovated. In order to better distinguish the differences in renovation potential between different communities, the output value of the potential value is amplified 100 times to obtain QRP (quarters Renovation Potential), which is called the renovation potential of the community to be renovated.

[0129] In a preferred implementation, the decision-making method further includes:

[0130] S1000: Configure transformation potential evaluation, where the transformation potential evaluation includes low transformation potential, relatively low transformation potential, medium transformation potential, relatively high transformation potential and high transformation potential.

[0131] S2000: Configure an update plan, which includes maintenance and retention, transformation and upgrading, and demolition and reconstruction.

[0132] In the present invention, "renewal plan" refers to three plans divided by scale: maintenance and preservation, renovation and upgrading, and demolition and reconstruction. Maintenance and preservation refers to maintenance and repair that does not change the original attributes of the community, such as external optimization projects such as environmental improvement and facade painting; renovation and upgrading refers to partial demolition and expansion, residential interior space renovation, public supporting facilities improvement, etc., which involve substantial changes to the components or devices of the community; demolition and reconstruction refers to the demolition of the original old community with a long construction period and seriously degraded living performance, and the redesign and planning on the original site in accordance with the latest national standards to rebuild the entire new community.

[0133] S3000: Acquire a decision indicator system, wherein the decision indicator system includes multiple first-level indicators and second-level indicators, and one first-level indicator corresponds to only one second-level indicator.

[0134] In the specific implementation, the decision indicator system is shown in Table 1.

[0135] S4000: Obtain the preference values ​​of the three update schemes corresponding to the transformation potential evaluation of each primary indicator, and construct a transformation potential evaluation-update scheme preference matrix, where the preference values ​​are 1 to 10.

[0136] In a specific implementation, experts score the preference values ​​(1-10) of the three renewal schemes corresponding to the transformation potential evaluation (low transformation potential, low transformation potential, medium transformation potential, high transformation potential, and high transformation potential) based on the four aspects of the community status, community location, community environment, and comprehensive benefits. 1 represents no preference, while 10 represents strong preference, and the sum of the preference values ​​of the three schemes corresponding to each evaluation result is 10. The transformation potential evaluation-renewal scheme preference matrix is ​​shown in Table 3 below.

[0137] Table 3 Transformation potential evaluation-renewal scheme preference matrix

[0138]

[0139]

[0140] Where: H i(m,j) It indicates the preference value assigned to the j scheme according to the evaluation result of the first-level indicator i (i=1, 2, 3 and 4; m=1, 2, 3, 4 and 5; j=1, 2 and 3). m refers to the first-level indicator, 1 is the current situation of the community, 2 is the location of the community, 3 is the environment of the community, and 4 is the comprehensive benefit. The j scheme refers to the renewal scheme, 1 is maintenance and preservation, 2 is transformation and upgrading, and 3 is demolition and reconstruction.

[0141] S5000: Based on the indicator weight values ​​of the secondary indicators and the transformation potential evaluation-update scheme preference matrix, the total preference value of each update scheme is calculated.

[0142] In a specific implementation, the calculation formula for the total preference value of the update scheme is:

[0143] Where P j is the total preference value of the update scheme, n is the number of secondary indicators, j represents the update scheme, j = 1, 2, 3, 1 is maintenance and retention, 2 is transformation and upgrading, 3 is demolition and reconstruction; W i is the indicator weight value of the i-th secondary indicator; H ij It is the solution preference value of the first-level indicator corresponding to the i-th second-level indicator in the corresponding update solution.

[0144] It is understandable that the solution preference value H of all secondary indicators ij and indicator weight W i The sum of the products of is the preference value output value of each update scheme. ij According to the transformation potential score of each secondary indicator in step S10, the transformation potential evaluation of the secondary indicator is determined, and then based on the transformation potential evaluation of the secondary indicator, the corresponding H is determined in the transformation potential evaluation-update scheme preference matrix. i(m,j) . H of three updating schemes ij The values ​​are all taken at H i(m,j) .

[0145] In one example, the transformation potential of the secondary indicator [Building Age] of the primary indicator [Current Status of the Community] is evaluated as high. ij The values ​​of correspond to H1(4,1)=1.931, H1(4,2)=4.685, and H1(4,3)=3.384 in the transformation potential evaluation-renewal scheme preference matrix.

[0146] S6000: The update plan with the largest total preference value is taken as the optimal update plan for the cell to be transformed and outputted.

[0147] The present invention also provides a decision-making system for transformation estimation and renewal scheme based on urban renewal, the decision-making system comprising:

[0148] A construction module, which is used to construct a decision-making indicator system, wherein the decision-making indicator system includes multiple indicators and corresponding indicator weight values;

[0149] A first acquisition module is used to acquire evaluation data of the community to be transformed, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades;

[0150] The evaluation module is used to evaluate based on the decision indicator system and the evaluation data using a fuzzy comprehensive evaluation method and output a transformation decision result.

[0151] Preferably, the decision-making system further includes:

[0152] A second acquisition module is used to obtain a transformation potential score of each indicator;

[0153] A first calculation module, which is used to calculate the transformation potential of the community to be transformed based on the transformation potential score of each indicator and the indicator weight value;

[0154] The calculation formula of the transformation potential is: In the formula, n is the number of indicators, W iis the indicator weight value of the i-th indicator, Z i Score the transformation potential of the i-th indicator.

[0155] Preferably, the decision-making system further includes:

[0156] A first configuration module, which is used to configure a transformation potential evaluation, wherein the transformation potential evaluation includes low transformation potential, relatively low transformation potential, medium transformation potential, relatively high transformation potential, and high transformation potential;

[0157] A second configuration module is used to configure an update plan, wherein the update plan includes maintenance and retention, transformation and upgrading, and demolition and reconstruction;

[0158] A third acquisition module is used to acquire a decision indicator system, wherein the decision indicator system includes a plurality of primary indicators and secondary indicators, and one primary indicator corresponds to only one secondary indicator;

[0159] A fourth acquisition module is used to obtain the preference values ​​of the three update schemes corresponding to the transformation potential evaluation of each primary indicator, and to construct a transformation potential evaluation-update scheme preference matrix, wherein the preference values ​​are 1 to 10;

[0160] A second calculation module is used to calculate the total preference value of each update scheme based on the indicator weight value of the secondary indicator and the transformation potential evaluation-update scheme preference matrix;

[0161] The output module is used to output the update scheme with the largest total preference value as the optimal update scheme for the cell to be transformed.

[0162] Preferably, the calculation formula for the total preference value of the update scheme is:

[0163] Where P j0 is the total preference value of the update scheme, n is the number of secondary indicators, j represents the update scheme, j = 1, 2, 3, 1 is maintenance and retention, 2 is transformation and upgrading, 3 is demolition and reconstruction; W i is the indicator weight value of the i-th secondary indicator; H ij is the preference value of each update scheme of the first-level indicator corresponding to the i-th second-level indicator.

[0164] For other structures of the decision-making method and system for transformation estimation and renewal plan based on urban renewal described in this embodiment, refer to the prior art.

[0165] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Therefore, any modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A decision-making method for transformation measurement and renewal plan based on urban renewal, characterized in that: The decision-making method comprises the following steps: Constructing a decision-making indicator system, wherein the decision-making indicator system includes multiple indicators and corresponding indicator weight values; Acquire evaluation data of the community to be transformed, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades; Based on the decision-making index system and the evaluation data, a fuzzy comprehensive evaluation method is used to perform evaluation and output a transformation decision result.

2. A decision-making method for transformation measurement and renewal plan based on urban renewal according to claim 1, characterized in that: The decision-making method further comprises: Get the transformation potential score for each indicator; Calculate the transformation potential of the community to be transformed based on the transformation potential score and the indicator weight value of each indicator; The calculation formula of the transformation potential is: In the formula, n is the number of indicators, W i is the indicator weight value of the i-th indicator, Z i Score the transformation potential of the i-th indicator.

3. The decision-making method for transformation measurement and renewal plan based on urban renewal according to claim 2 is characterized in that: The decision-making method further comprises: configuring a transformation potential evaluation, wherein the transformation potential evaluation includes low transformation potential, relatively low transformation potential, medium transformation potential, relatively high transformation potential, and high transformation potential; Configuration renewal scheme, the renewal scheme including maintenance and preservation, transformation and upgrading, and demolition and reconstruction; Acquire a decision indicator system, wherein the decision indicator system includes a plurality of primary indicators and secondary indicators, and one primary indicator corresponds to at least one secondary indicator; Obtain the preference values ​​of the three update schemes corresponding to the transformation potential evaluation of each primary indicator, and construct a transformation potential evaluation-update scheme preference matrix, where the preference values ​​are 1 to 10; Based on the indicator weight values ​​of the secondary indicators and the transformation potential evaluation-update scheme preference matrix, the total preference value of each update scheme is calculated; The update plan with the largest total preference value is taken as the optimal update plan for the community to be transformed and output.

4. The decision-making method for transformation measurement and renewal plan based on urban renewal according to claim 3 is characterized by: The calculation formula for the total preference value of the update scheme is: Where P j is the total preference value of the update scheme, n is the number of secondary indicators, j represents the update scheme, j = 1, 2, 3, 1 is maintenance and retention, 2 is transformation and upgrading, 3 is demolition and reconstruction; W i is the indicator weight value of the i-th secondary indicator; H ij is the preference value of each update scheme of the first-level indicator corresponding to the i-th second-level indicator.

5. The decision-making method for transformation calculation and renewal plan based on urban renewal according to claim 4 is characterized by: The first-level indicators include the current status of the community, the location of the community, the environment of the community and the comprehensive benefits.

6. The decision-making method for transformation calculation and renewal plan based on urban renewal according to claim 1 is characterized by: The indicator weight value is determined by calling Super Decisions software and using the hierarchical analysis method to determine the indicator weight value of each indicator.

7. A decision-making system for transformation calculation and renewal plan based on urban renewal, characterized in that: The decision-making system comprises: A construction module, which is used to construct a decision-making indicator system, wherein the decision-making indicator system includes multiple indicators and corresponding indicator weight values; A first acquisition module is used to acquire evaluation data of the community to be transformed, wherein the evaluation data is a grade evaluation corresponding to the indicator, and the grade evaluation includes 1 to 5 grades; The evaluation module is used to evaluate based on the decision indicator system and the evaluation data using a fuzzy comprehensive evaluation method and output a transformation decision result.

8. The decision-making system for transformation calculation and renewal plan based on urban renewal according to claim 7 is characterized in that: The decision-making system also includes: A second acquisition module is used to obtain a transformation potential score of each indicator; A first calculation module, which is used to calculate the transformation potential of the community to be transformed based on the transformation potential score of each indicator and the indicator weight value; The calculation formula of the transformation potential is: In the formula, n is the number of indicators, W i is the indicator weight value of the i-th indicator, Z i Score the transformation potential of the i-th indicator.

9. The decision-making system for transformation calculation and renewal plan based on urban renewal according to claim 8 is characterized in that: The decision-making system also includes: A first configuration module, which is used to configure a transformation potential evaluation, wherein the transformation potential evaluation includes low transformation potential, relatively low transformation potential, medium transformation potential, relatively high transformation potential, and high transformation potential; A second configuration module is used to configure an update plan, wherein the update plan includes maintenance and retention, transformation and upgrading, and demolition and reconstruction; A third acquisition module is used to acquire a decision indicator system, wherein the decision indicator system includes a plurality of primary indicators and secondary indicators, and one primary indicator corresponds to at least one secondary indicator; A fourth acquisition module is used to obtain the preference values ​​of the three update schemes corresponding to the transformation potential evaluation of each primary indicator, and to construct a transformation potential evaluation-update scheme preference matrix, wherein the preference values ​​are 1 to 10; A second calculation module is used to calculate the total preference value of each update scheme based on the indicator weight value of the secondary indicator and the transformation potential evaluation-update scheme preference matrix; The output module is used to output the update scheme with the largest total preference value as the optimal update scheme for the cell to be transformed.

10. The decision-making system for transformation calculation and renewal plan based on urban renewal according to claim 9 is characterized by: The calculation formula for the total preference value of the update scheme is: Where P j is the total preference value of the update scheme, n is the number of secondary indicators, j represents the update scheme, j = 1, 2, 3, 1 is maintenance and retention, 2 is transformation and upgrading, 3 is demolition and reconstruction; W i is the indicator weight value of the i-th secondary indicator; H ij is the preference value of each update scheme of the first-level indicator corresponding to the i-th second-level indicator.

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