A method and system for evaluating urban potential based on multi-index fusion

Abstract

The present invention relates to the technical field of urban management, and discloses a city potential assessment method and system based on multi-indicator fusion. The method comprises the following steps: deploying multiple data source collection points for a target potential assessment city, preprocessing initial environmental indicator data, and determining target environmental indicator data; extracting target environmental indicator data of the same type, constructing a target environmental indicator data series, and calculating environmental indicator data pointing coefficients; performing set division of environmental indicator data pointing coefficients based on a preset environmental indicator data pointing coefficient series, and calculating initial potential assessment factors; generating potential assessment identifiers for data source collection points; counting positive and negative quantities, setting a potential assessment optimization coefficient, optimizing the initial potential assessment factor, and obtaining a target potential assessment factor. The method evaluates the city potential based on the multiple environmental indicator data, thereby ensuring the accuracy and comprehensiveness of the city potential assessment and providing a basis for comprehensive urban development and key city selection by operators.

Description

Technical Field

[0001] The present invention relates to the field of urban management technology, and in particular to a method and system for evaluating urban potential based on multi-index fusion. Background Art

[0002] In today's era of globalization and rapid industrialization, the pace of urbanization is accelerating, leading to problems such as environmental pollution, traffic congestion, and exorbitant housing prices in major cities. This has led to a temporary phenomenon of counter-urbanization, hindering sustainable urban development. Environmental pollution not only affects the quality of a city's ecological environment but also has a direct impact on its comprehensive development. Therefore, accurately assessing the urban environment and identifying potential environmental risks and development bottlenecks are crucial for comprehensive urban development and promoting sustainable urban development.

[0003] Traditional urban assessment methods often focus on a single environmental parameter, ignoring the comprehensive impact of multiple environmental parameters on a city's overall potential. Furthermore, traditional urban assessment methods rely primarily on expert review, a process that is not only time-consuming and labor-intensive but also susceptible to subjective factors. Different experts may have different understandings of the same parameter, leading to inconsistent assessment results and failing to ensure the comprehensiveness and accuracy of urban potential assessments. Summary of the Invention

[0004] In view of this, the present invention proposes a city potential assessment method and system based on multi-indicator fusion, aiming to solve the problem in current technology that it is impossible to assess city potential based on multiple environmental indicators and cannot ensure the accuracy and comprehensiveness of city potential assessment.

[0005] The present invention proposes a city potential assessment method based on multi-index fusion, including:

[0006] Deploy multiple data source collection points for the target potential assessment city, obtain initial environmental indicator data corresponding to each data source collection point, preprocess the initial environmental indicator data, and determine target environmental indicator data based on the preprocessing results;

[0007] Extracting target environmental indicator data of the same type from each data source collection point and constructing a target environmental indicator data series, processing the target environmental indicator data series, and calculating an environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result;

[0008] Dividing all environmental indicator data pointing coefficients into sets based on a preset environmental indicator data pointing coefficient sequence, and calculating the initial potential assessment factor of the target potential assessment city based on the divided sets, wherein the preset environmental indicator data pointing coefficient sequence includes a first preset environmental indicator data pointing coefficient and a second preset environmental indicator data pointing coefficient;

[0009] Generating a potential assessment identifier for the corresponding data source collection point according to the target environmental indicator data, wherein the potential assessment identifier includes a positive potential assessment identifier, a negative potential assessment identifier, and a pending potential assessment identifier;

[0010] Counting the positive number of the positive potential assessment identifiers, counting the negative number of the negative potential assessment identifiers, and setting a potential assessment optimization coefficient for the target potential assessment city according to the positive number and the negative number;

[0011] Optimizing the initial potential assessment factor based on the potential assessment optimization coefficient to obtain a target potential assessment factor of the target potential assessment city, wherein the target potential assessment factor is the product value of the potential assessment optimization coefficient and the initial potential assessment factor;

[0012] When processing the target environmental indicator data series and calculating the environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result, the method includes:

[0013] Determine the same target environmental indicator data from the target environmental indicator data series, and construct a plurality of sub-target environmental indicator data series;

[0014] Count the number of initial data series of sub-goal environmental indicator data series;

[0015] Extract one target environmental indicator data from each of the sub-target environmental indicator data series, and calculate the initial environmental indicator data and value;

[0016] Obtaining a pre-calculated calculation data value, deleting all sub-target environmental indicator data series that are smaller than the calculation data value, and counting the number of final data series of the remaining sub-target environmental indicator data series;

[0017] Extract one target environmental indicator data from each of the remaining sub-target environmental indicator data series, and calculate the final environmental indicator data and value;

[0018] The environmental indicator data pointing coefficient of the target environmental indicator data sequence is calculated according to the number of the initial data sequence, the initial environmental indicator data and value, the number of the final data sequence and the final environmental indicator data and value.

[0019] Furthermore, when calculating the environmental indicator data pointing coefficient of the target environmental indicator data sequence according to the number of the initial data sequence, the initial environmental indicator data and value, the number of the final data sequence, and the final environmental indicator data and value, the method includes:

[0020] The environmental indicator data pointing coefficient of the target environmental indicator data series is calculated according to the following formula:

[0021]

[0022] Among them, a is the environmental indicator data pointing coefficient of the target environmental indicator data series, r1 is the number of initial data series, r2 is the number of final data series, q1 is the initial environmental indicator data and value, and q2 is the final environmental indicator data and value.

[0023] Furthermore, when all environmental indicator data pointing coefficients are divided into sets based on a preset environmental indicator data pointing coefficient sequence, and the initial potential assessment factor of the target potential assessment city is calculated based on the divided sets, the method includes:

[0024] When the environmental indicator data pointing coefficient is less than or equal to the first preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a first pointing coefficient set;

[0025] When the environmental indicator data pointing coefficient is greater than the first preset environmental indicator data pointing coefficient and less than the second preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a second pointing coefficient set;

[0026] When the environmental indicator data pointing coefficient is greater than or equal to the second preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a third pointing coefficient set;

[0027] An initial potential assessment factor of the target potential assessment city is calculated based on the first direction coefficient set, the second direction coefficient set, and the third direction coefficient set.

[0028] Furthermore, when calculating the initial potential assessment factor of the target potential assessment city according to the first direction coefficient set, the second direction coefficient set, and the third direction coefficient set, the method includes:

[0029] Calculating a first directivity coefficient mean and a first directivity coefficient standard deviation of the first directivity coefficient set;

[0030] determining a first directivity coefficient range corresponding to the first directivity coefficient set according to the first directivity coefficient mean and the first directivity coefficient standard deviation;

[0031] Calculate the second directivity coefficient mean and the second directivity coefficient standard deviation of the second directivity coefficient set;

[0032] determining a second directivity coefficient range corresponding to the second directivity coefficient set according to the second directivity coefficient mean and the second directivity coefficient standard deviation;

[0033] Calculating a third directivity coefficient mean and a third directivity coefficient standard deviation of the third directivity coefficient set;

[0034] Determining a third directivity coefficient range corresponding to the third directivity coefficient set according to the third directivity coefficient mean and the third directivity coefficient standard deviation;

[0035] Comparing the environmental indicator data pointing coefficient in each pointing coefficient set with the corresponding pointing coefficient range, and generating a to-be-extracted mark for the environmental indicator data pointing coefficient if the environmental indicator data pointing coefficient is within the corresponding pointing coefficient range;

[0036] An initial potential assessment factor of the target potential assessment city is calculated based on all the to-be-extracted markers.

[0037] Further, when determining the first directivity coefficient range corresponding to the first directivity coefficient set according to the first directivity coefficient mean and the first directivity coefficient standard deviation, the method includes:

[0038] The first directivity coefficient range corresponding to the first directivity coefficient set is determined according to the following formula:

[0039] f(f1, f2)=(e1×g1)±(e2×g2);

[0040] Among them, f(f1, f2) is the first directional coefficient range corresponding to the first directional coefficient set, e1 is the first calculation coefficient, e2 is the second calculation coefficient, g1 is the first directional coefficient mean, g2 is the first directional coefficient standard deviation, and e1+e2=1, e1>e2.

[0041] Furthermore, when calculating the initial potential assessment factor of the target potential assessment city based on all the to-be-extracted markers, the following steps are included:

[0042] configuring a third calculation coefficient for the first directivity coefficient set, configuring a fourth calculation coefficient for the second directivity coefficient set, and configuring a fifth calculation coefficient for the third directivity coefficient set;

[0043] The initial potential assessment factor of the target potential assessment city is calculated according to the following formula:

[0044] k=h1×m1+h2×m2+h3×m3;

[0045] Among them, k is the initial potential assessment factor of the target potential assessment city, h1 is the third calculation coefficient, h2 is the fourth calculation coefficient, h3 is the fifth calculation coefficient, m1 is the number of markers to be extracted in the first pointing coefficient set, m2 is the number of markers to be extracted in the second pointing coefficient set, m3 is the number of markers to be extracted in the third pointing coefficient set, and h1>h2>h3, h1>0, h2>0, h3>0.

[0046] Furthermore, when generating a potential assessment identifier for a corresponding data source collection point based on the target environmental indicator data, the method includes:

[0047] Determine the standard environmental indicator data corresponding to each data source collection point;

[0048] Comparing the target environmental indicator data with the standard environmental indicator data, and if the target environmental indicator data are both less than or equal to the standard environmental indicator data, generating the positive potential assessment identifier for the corresponding data source collection point;

[0049] If the target environmental indicator data are all greater than the standard environmental indicator data, generating the negative potential assessment mark for the corresponding data source collection point;

[0050] If one or more of the target environmental indicator data are greater than the standard environmental indicator data, and one or more of the target environmental indicator data are less than or equal to the standard environmental indicator data, the pending potential assessment identifier is generated for the corresponding data source collection point.

[0051] Furthermore, when setting the potential assessment optimization coefficient of the target potential assessment city according to the positive quantity and the negative quantity, it includes:

[0052] Determine a ratio n of the positive quantity to the negative quantity;

[0053] Presetting a first preset potential evaluation optimization coefficient, a second preset potential evaluation optimization coefficient, and a third preset potential evaluation optimization coefficient;

[0054] When n≤1, the first preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city;

[0055] When 1<n≤1.3, the second preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city;

[0056] When 1.3<n, the third preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] Deploy multiple data source collection points for target potential assessment cities, pre-process the initial environmental indicator data, and determine the target environmental indicator data; extract target environmental indicator data of the same type, construct a target environmental indicator data series, and calculate the environmental indicator data pointing coefficient; divide the environmental indicator data pointing coefficient into sets based on the preset environmental indicator data pointing coefficient sequence, and calculate the initial potential assessment factor; generate potential assessment identifiers for data source collection points; count the positive and negative numbers, set the potential assessment optimization coefficient, optimize the initial potential assessment factor, and obtain the target potential assessment factor. Evaluate the city's potential based on multiple environmental indicator data to ensure the accuracy and comprehensiveness of the city's potential assessment, and provide a basis for the comprehensive development of cities and the selection of key cities by operators.

[0059] On the other hand, this application also provides a city potential assessment system based on multi-indicator fusion, including:

[0060] A data determination module is used to deploy multiple data source collection points for the target potential assessment city, obtain initial environmental indicator data corresponding to each data source collection point, preprocess the initial environmental indicator data, and determine target environmental indicator data based on the preprocessing results;

[0061] A first calculation module is used to extract target environmental indicator data of the same type from each data source collection point, construct a target environmental indicator data series, process the target environmental indicator data series, and calculate the environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result;

[0062] a second calculation module, configured to divide all environmental indicator data pointing coefficients into sets based on a preset environmental indicator data pointing coefficient sequence, and calculate an initial potential assessment factor of the target potential assessment city based on the divided sets, wherein the preset environmental indicator data pointing coefficient sequence includes a first preset environmental indicator data pointing coefficient and a second preset environmental indicator data pointing coefficient;

[0063] An identifier generation module is used to generate a potential assessment identifier for the corresponding data source collection point according to the target environmental indicator data, wherein the potential assessment identifier includes a positive potential assessment identifier, a negative potential assessment identifier, and a pending potential assessment identifier;

[0064] an optimization setting module, configured to count the positive number of the positive potential assessment identifiers, count the negative number of the negative potential assessment identifiers, and set a potential assessment optimization coefficient for the target potential assessment city according to the positive number and the negative number;

[0065] A potential assessment module is used to optimize the initial potential assessment factor based on the potential assessment optimization coefficient to obtain the target potential assessment factor of the target potential assessment city, wherein the target potential assessment factor is the product value of the potential assessment optimization coefficient and the initial potential assessment factor.

[0066] It is understandable that the above-mentioned urban potential assessment system and method based on multi-index fusion have the same beneficial effects and will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0068] Figure 1 A schematic diagram of a flow chart of a method for evaluating urban potential based on multi-index fusion provided by an embodiment of the present invention;

[0069] Figure 2 This is a schematic diagram of the structure of a city potential assessment system based on multi-index fusion provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0070] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0071] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides a city potential assessment method based on multi-index fusion, including:

[0072] S110: Deploy multiple data source collection points for the target potential assessment city, obtain initial environmental indicator data corresponding to each data source collection point, preprocess the initial environmental indicator data, and determine target environmental indicator data based on the preprocessing results;

[0073] In this embodiment, the number of deployed data source collection points is preferably 30, which can be adjusted according to actual needs. When deploying the data source collection points, uniform deployment is sufficient.

[0074] In this embodiment, the initial environmental indicator data includes pollutants such as PM2.5, PM10, sulfur dioxide, and nitrogen oxides.

[0075] In this embodiment, the preprocessing includes removing duplicate data and erroneous data.

[0076] The beneficial effects of the above technical solution are: the present invention deploys multiple data source collection points for the target potential assessment city, obtains the initial environmental indicator data corresponding to each data source collection point, can meet the data diversity and comprehensiveness, pre-processes the initial environmental indicator data, and determines the target environmental indicator data based on the pre-processing results, which can ensure the accuracy of the target environmental indicator data and avoid potential assessment errors.

[0077] S120: extracting target environmental indicator data of the same type from each data source collection point, and constructing a target environmental indicator data series, processing the target environmental indicator data series, and calculating an environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result;

[0078] In some embodiments of the present application, when processing the target environmental indicator data series and calculating the environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result, the process includes:

[0079] Determine the same target environmental indicator data from the target environmental indicator data series, and construct a plurality of sub-target environmental indicator data series;

[0080] Count the number of initial data series of sub-goal environmental indicator data series;

[0081] Extract one target environmental indicator data from each of the sub-target environmental indicator data series, and calculate the initial environmental indicator data and value;

[0082] Obtaining a pre-calculated calculation data value, deleting all sub-target environmental indicator data series that are smaller than the calculation data value, and counting the number of final data series of the remaining sub-target environmental indicator data series;

[0083] Extract one target environmental indicator data from each of the remaining sub-target environmental indicator data series, and calculate the final environmental indicator data and value;

[0084] The environmental indicator data pointing coefficient of the target environmental indicator data sequence is calculated according to the number of the initial data sequence, the initial environmental indicator data and value, the number of the final data sequence and the final environmental indicator data and value.

[0085] In this embodiment, if a target environmental indicator data series is constructed based on the sulfur dioxide corresponding to each data source collection point, the sulfur dioxide here is the same type of target environmental indicator data; if a target environmental indicator data series is constructed based on PM2.5, the PM2.5 here is the same type of target environmental indicator data.

[0086] In this embodiment, if the target environmental indicator data series is sulfur dioxide, the same sulfur dioxide is extracted to construct multiple sub-target environmental indicator data series, such as {80 mg / m3, 80 mg / m3}, {85 mg / m3, 85 mg / m3, 85 mg / m3}, {100 mg / m3, 100 mg / m3}, then the number of initial data series is 3, and one target environmental indicator data, namely 80 mg / m3, 85 mg / m3, 100 mg / m3, is extracted respectively. 0 mg / m3, the calculated data value is the mean of the target environmental indicator data series. For example, if it is 84 mg / m3, the remaining sub-target environmental indicator data series are {85 mg / m3, 85 mg / m3, 85 mg / m3}, {100 mg / m3, 100 mg / m3}, and the number of final data series is 2. One target environmental indicator data is extracted respectively, that is, 85 mg / m3 and 100 mg / m3. The above is shown as an example, and the specific details shall be subject to actual conditions.

[0087] The beneficial effect of the above technical solution is: the present invention calculates the environmental indicator data pointing coefficient of the target environmental indicator data series based on the number of initial data series, the initial environmental indicator data and value, the number of final data series and the final environmental indicator data and value, which can ensure the calculation accuracy of the environmental indicator data pointing coefficient and lay the foundation for the calculation of the initial potential assessment factor of the target potential assessment city.

[0088] In some embodiments of the present application, when calculating the environmental indicator data pointing coefficient of the target environmental indicator data series based on the number of the initial data series, the initial environmental indicator data and value, the number of the final data series, and the final environmental indicator data and value, the calculation includes:

[0089] The environmental indicator data pointing coefficient of the target environmental indicator data series is calculated according to the following formula:

[0090]

[0091] Among them, a is the environmental indicator data pointing coefficient of the target environmental indicator data series, r1 is the number of initial data series, r2 is the number of final data series, q1 is the initial environmental indicator data and value, and q2 is the final environmental indicator data and value.

[0092] S130: Dividing all environmental indicator data pointing coefficients into sets based on a preset environmental indicator data pointing coefficient sequence, and calculating an initial potential assessment factor of the target potential assessment city based on the divided sets, wherein the preset environmental indicator data pointing coefficient sequence includes a first preset environmental indicator data pointing coefficient and a second preset environmental indicator data pointing coefficient;

[0093] In this embodiment, the preset environmental indicator data pointing coefficient sequence is pre-set, the first preset environmental indicator data pointing coefficient is preferably 4, and the second preset environmental indicator data pointing coefficient is preferably 7, which can be adaptively adjusted according to actual needs.

[0094] In some embodiments of the present application, when all environmental indicator data pointing coefficients are divided into sets based on a preset preset environmental indicator data pointing coefficient sequence, and the initial potential assessment factor of the target potential assessment city is calculated based on the divided sets, the method includes:

[0095] When the environmental indicator data pointing coefficient is less than or equal to the first preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a first pointing coefficient set;

[0096] When the environmental indicator data pointing coefficient is greater than the first preset environmental indicator data pointing coefficient and less than the second preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a second pointing coefficient set;

[0097] When the environmental indicator data pointing coefficient is greater than or equal to the second preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a third pointing coefficient set;

[0098] An initial potential assessment factor of the target potential assessment city is calculated based on the first direction coefficient set, the second direction coefficient set, and the third direction coefficient set.

[0099] The beneficial effect of the above technical solution is: the present invention divides the first pointing coefficient set, the second pointing coefficient set and the third pointing coefficient set according to the environmental indicator data pointing coefficient, the first preset environmental indicator data pointing coefficient and the second preset environmental indicator data pointing coefficient, thereby ensuring the accuracy of the set division and providing a basis for the calculation of the initial potential assessment factor of the target potential assessment city.

[0100] In some embodiments of the present application, when calculating the initial potential assessment factor of the target potential assessment city according to the first direction coefficient set, the second direction coefficient set, and the third direction coefficient set, the calculation includes:

[0101] Calculating a first directivity coefficient mean and a first directivity coefficient standard deviation of the first directivity coefficient set;

[0102] determining a first directivity coefficient range corresponding to the first directivity coefficient set according to the first directivity coefficient mean and the first directivity coefficient standard deviation;

[0103] Calculate the second directivity coefficient mean and the second directivity coefficient standard deviation of the second directivity coefficient set;

[0104] determining a second directivity coefficient range corresponding to the second directivity coefficient set according to the second directivity coefficient mean and the second directivity coefficient standard deviation;

[0105] Calculating a third directivity coefficient mean and a third directivity coefficient standard deviation of the third directivity coefficient set;

[0106] Determining a third directivity coefficient range corresponding to the third directivity coefficient set according to the third directivity coefficient mean and the third directivity coefficient standard deviation;

[0107] Comparing the environmental indicator data pointing coefficient in each pointing coefficient set with the corresponding pointing coefficient range, and generating a to-be-extracted mark for the environmental indicator data pointing coefficient if the environmental indicator data pointing coefficient is within the corresponding pointing coefficient range;

[0108] An initial potential assessment factor of the target potential assessment city is calculated based on all the to-be-extracted markers.

[0109] In this embodiment, each directional coefficient set corresponds to a directional coefficient range, and each directional coefficient range includes a left boundary value and a right boundary value. The left boundary value is smaller than the right boundary value. When the environmental indicator data directional coefficient is greater than or equal to the left boundary value and less than or equal to the right boundary value, it is judged that the environmental indicator data directional coefficient is within the corresponding directional coefficient range.

[0110] In some embodiments of the present application, when determining the first directivity coefficient range corresponding to the first directivity coefficient set according to the first directivity coefficient mean and the first directivity coefficient standard deviation, the method includes:

[0111] The first directivity coefficient range corresponding to the first directivity coefficient set is determined according to the following formula:

[0112] f(f1, f2)=(e1×g1)±(e2×g2);

[0113] Among them, f(f1, f2) is the first directional coefficient range corresponding to the first directional coefficient set, e1 is the first calculation coefficient, e2 is the second calculation coefficient, g1 is the first directional coefficient mean, g2 is the first directional coefficient standard deviation, and e1+e2=1, e1>e2.

[0114] In this embodiment, f1 is the left boundary value, and f2 is the right boundary value.

[0115] In this embodiment, the second directivity coefficient range and the third directivity coefficient range are determined in the same manner as the first directivity coefficient range, and are not described again here.

[0116] In some embodiments of the present application, when calculating the initial potential assessment factor of the target potential assessment city according to all the to-be-extracted markers, the method includes:

[0117] configuring a third calculation coefficient for the first directivity coefficient set, configuring a fourth calculation coefficient for the second directivity coefficient set, and configuring a fifth calculation coefficient for the third directivity coefficient set;

[0118] The initial potential assessment factor of the target potential assessment city is calculated according to the following formula:

[0119] k=h1×m1+h2×m2+h3×m3;

[0120] Among them, k is the initial potential assessment factor of the target potential assessment city, h1 is the third calculation coefficient, h2 is the fourth calculation coefficient, h3 is the fifth calculation coefficient, m1 is the number of markers to be extracted in the first pointing coefficient set, m2 is the number of markers to be extracted in the second pointing coefficient set, m3 is the number of markers to be extracted in the third pointing coefficient set, and h1>h2>h3, h1>0, h2>0, h3>0.

[0121] The beneficial effect of the above technical solution is that the present invention calculates the initial potential assessment factor of the target potential assessment city based on all the marks to be extracted, ensures the calculation accuracy of the initial potential assessment factor, and realizes the initial potential assessment of the target potential assessment city without human participation, avoiding subjectivity and one-sidedness.

[0122] S140: generating a potential assessment identifier for the corresponding data source collection point according to the target environmental indicator data, wherein the potential assessment identifier includes a positive potential assessment identifier, a negative potential assessment identifier, and a pending potential assessment identifier;

[0123] In some embodiments of the present application, when generating a potential assessment identifier for a corresponding data source collection point based on the target environmental indicator data, the process includes:

[0124] Determine the standard environmental indicator data corresponding to each data source collection point;

[0125] Comparing the target environmental indicator data with the standard environmental indicator data, and if the target environmental indicator data are both less than or equal to the standard environmental indicator data, generating the positive potential assessment identifier for the corresponding data source collection point;

[0126] If the target environmental indicator data are all greater than the standard environmental indicator data, generating the negative potential assessment mark for the corresponding data source collection point;

[0127] If one or more of the target environmental indicator data are greater than the standard environmental indicator data, and one or more of the target environmental indicator data are less than or equal to the standard environmental indicator data, the pending potential assessment identifier is generated for the corresponding data source collection point.

[0128] In this embodiment, the standard environmental indicator data corresponds to the target environmental indicator data one-to-one, and the standard environmental indicator data can be specifically set according to the data source collection point.

[0129] S150: Counting the positive number of the positive potential assessment identifiers, counting the negative number of the negative potential assessment identifiers, and setting a potential assessment optimization coefficient for the target potential assessment city according to the positive number and the negative number;

[0130] In some embodiments of the present application, when setting the potential assessment optimization coefficient of the target potential assessment city according to the positive quantity and the negative quantity, it includes:

[0131] Determine a ratio n of the positive quantity to the negative quantity;

[0132] Presetting a first preset potential evaluation optimization coefficient, a second preset potential evaluation optimization coefficient, and a third preset potential evaluation optimization coefficient;

[0133] When n≤1, the first preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city;

[0134] When 1<n≤1.3, the second preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city;

[0135] When 1.3<n, the third preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city.

[0136] In this embodiment, the first preset potential evaluation optimization coefficient is preferably 0.9, the second preset potential evaluation optimization coefficient is preferably 1.1, and the third preset potential evaluation optimization coefficient is preferably 1.2.

[0137] The beneficial effect of the above technical solution is that the present invention selects the corresponding preset potential assessment optimization coefficient according to the quantity ratio, thereby realizing the dynamic optimization of the initial potential assessment factor, ensuring the optimization accuracy, and further ensuring the accuracy of the urban potential assessment.

[0138] S160: Optimizing the initial potential assessment factor based on the potential assessment optimization coefficient to obtain a target potential assessment factor of the target potential assessment city, wherein the target potential assessment factor is the product value of the potential assessment optimization coefficient and the initial potential assessment factor.

[0139] The beneficial effect of the above technical solution is: the present invention ensures the accuracy and comprehensiveness of urban potential assessment by determining the target potential assessment factor of the target potential assessment city. The larger the target potential assessment factor, the greater the potential of the target potential assessment city, which provides a basis for urban comprehensive development and operator enterprise key city selection.

[0140] like Figure 2 As shown, in another preferred embodiment based on the above embodiment, this embodiment provides a city potential assessment system based on multi-index fusion, including:

[0141] A data determination module is used to deploy multiple data source collection points for the target potential assessment city, obtain initial environmental indicator data corresponding to each data source collection point, preprocess the initial environmental indicator data, and determine target environmental indicator data based on the preprocessing results;

[0142] A first calculation module is used to extract target environmental indicator data of the same type from each data source collection point, construct a target environmental indicator data series, process the target environmental indicator data series, and calculate the environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result;

[0143] a second calculation module, configured to divide all environmental indicator data pointing coefficients into sets based on a preset environmental indicator data pointing coefficient sequence, and calculate an initial potential assessment factor of the target potential assessment city based on the divided sets, wherein the preset environmental indicator data pointing coefficient sequence includes a first preset environmental indicator data pointing coefficient and a second preset environmental indicator data pointing coefficient;

[0144] An identifier generation module is used to generate a potential assessment identifier for the corresponding data source collection point according to the target environmental indicator data, wherein the potential assessment identifier includes a positive potential assessment identifier, a negative potential assessment identifier, and a pending potential assessment identifier;

[0145] an optimization setting module, configured to count the positive number of the positive potential assessment identifiers, count the negative number of the negative potential assessment identifiers, and set a potential assessment optimization coefficient for the target potential assessment city according to the positive number and the negative number;

[0146] A potential assessment module is used to optimize the initial potential assessment factor based on the potential assessment optimization coefficient to obtain the target potential assessment factor of the target potential assessment city, wherein the target potential assessment factor is the product value of the potential assessment optimization coefficient and the initial potential assessment factor.

[0147] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0148] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0149] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating urban potential based on multi-index fusion, characterized in that: include: Deploy multiple data source collection points for the target potential assessment city, obtain initial environmental indicator data corresponding to each data source collection point, preprocess the initial environmental indicator data, and determine target environmental indicator data based on the preprocessing results; Extracting target environmental indicator data of the same type from each data source collection point and constructing a target environmental indicator data series, processing the target environmental indicator data series, and calculating an environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result; Dividing all environmental indicator data pointing coefficients into sets based on a preset environmental indicator data pointing coefficient sequence, and calculating the initial potential assessment factor of the target potential assessment city based on the divided sets, wherein the preset environmental indicator data pointing coefficient sequence includes a first preset environmental indicator data pointing coefficient and a second preset environmental indicator data pointing coefficient; Generating a potential assessment identifier for the corresponding data source collection point according to the target environmental indicator data, wherein the potential assessment identifier includes a positive potential assessment identifier, a negative potential assessment identifier, and a pending potential assessment identifier; Counting the positive number of the positive potential assessment identifiers, counting the negative number of the negative potential assessment identifiers, and setting a potential assessment optimization coefficient for the target potential assessment city according to the positive number and the negative number; Optimizing the initial potential assessment factor based on the potential assessment optimization coefficient to obtain a target potential assessment factor of the target potential assessment city, wherein the target potential assessment factor is the product value of the potential assessment optimization coefficient and the initial potential assessment factor; When processing the target environmental indicator data series and calculating the environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result, the method includes: Determine the same target environmental indicator data from the target environmental indicator data series, and construct a plurality of sub-target environmental indicator data series; Count the number of initial data series of sub-goal environmental indicator data series; Extract one target environmental indicator data from each of the sub-target environmental indicator data series, and calculate the initial environmental indicator data and value; Obtaining a pre-calculated calculation data value, deleting all sub-target environmental indicator data series that are smaller than the calculation data value, and counting the number of final data series of the remaining sub-target environmental indicator data series; Extract one target environmental indicator data from each of the remaining sub-target environmental indicator data series, and calculate the final environmental indicator data and value; The environmental indicator data pointing coefficient of the target environmental indicator data sequence is calculated according to the number of the initial data sequence, the initial environmental indicator data and value, the number of the final data sequence and the final environmental indicator data and value.

2. The urban potential assessment method based on multi-index fusion according to claim 1 is characterized in that: When calculating the environmental indicator data pointing coefficient of the target environmental indicator data sequence according to the number of the initial data sequence, the initial environmental indicator data and value, the number of the final data sequence, and the final environmental indicator data and value, the method includes: The environmental indicator data pointing coefficient of the target environmental indicator data series is calculated according to the following formula: Among them, a is the environmental indicator data pointing coefficient of the target environmental indicator data series, r1 is the number of initial data series, r2 is the number of final data series, q1 is the initial environmental indicator data and value, and q2 is the final environmental indicator data and value.

3. The urban potential assessment method based on multi-index fusion according to claim 1 is characterized in that: When all environmental indicator data pointing coefficients are divided into sets based on a preset environmental indicator data pointing coefficient sequence, and an initial potential assessment factor of the target potential assessment city is calculated based on the divided sets, the method includes: When the environmental indicator data pointing coefficient is less than or equal to the first preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a first pointing coefficient set; When the environmental indicator data pointing coefficient is greater than the first preset environmental indicator data pointing coefficient and less than the second preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a second pointing coefficient set; When the environmental indicator data pointing coefficient is greater than or equal to the second preset environmental indicator data pointing coefficient, the corresponding environmental indicator data pointing coefficient is divided into a third pointing coefficient set; An initial potential assessment factor of the target potential assessment city is calculated based on the first direction coefficient set, the second direction coefficient set, and the third direction coefficient set.

4. The urban potential assessment method based on multi-index fusion according to claim 3 is characterized in that: When calculating the initial potential assessment factor of the target potential assessment city according to the first direction coefficient set, the second direction coefficient set, and the third direction coefficient set, the method includes: Calculating a first directivity coefficient mean and a first directivity coefficient standard deviation of the first directivity coefficient set; determining a first directivity coefficient range corresponding to the first directivity coefficient set according to the first directivity coefficient mean and the first directivity coefficient standard deviation; Calculate the second directivity coefficient mean and the second directivity coefficient standard deviation of the second directivity coefficient set; determining a second directivity coefficient range corresponding to the second directivity coefficient set according to the second directivity coefficient mean and the second directivity coefficient standard deviation; Calculating a third directivity coefficient mean and a third directivity coefficient standard deviation of the third directivity coefficient set; Determining a third directivity coefficient range corresponding to the third directivity coefficient set according to the third directivity coefficient mean and the third directivity coefficient standard deviation; Comparing the environmental indicator data pointing coefficient in each pointing coefficient set with the corresponding pointing coefficient range, and generating a to-be-extracted mark for the environmental indicator data pointing coefficient if the environmental indicator data pointing coefficient is within the corresponding pointing coefficient range; An initial potential assessment factor of the target potential assessment city is calculated based on all the to-be-extracted markers.

5. The urban potential assessment method based on multi-index fusion according to claim 4 is characterized in that: When determining a first directivity coefficient range corresponding to the first directivity coefficient set according to the first directivity coefficient mean and the first directivity coefficient standard deviation, the method includes: The first directivity coefficient range corresponding to the first directivity coefficient set is determined according to the following formula: f(f1, f2)=(e1×g1)±(e2×g2); Among them, f(f1, f2) is the first directional coefficient range corresponding to the first directional coefficient set, e1 is the first calculation coefficient, e2 is the second calculation coefficient, g1 is the first directional coefficient mean, g2 is the first directional coefficient standard deviation, and e1+e2=1, e1>e2.

6. The urban potential assessment method based on multi-index fusion according to claim 5 is characterized in that: When calculating the initial potential assessment factor of the target potential assessment city based on all the to-be-extracted markers, it includes: configuring a third calculation coefficient for the first directivity coefficient set, configuring a fourth calculation coefficient for the second directivity coefficient set, and configuring a fifth calculation coefficient for the third directivity coefficient set; The initial potential assessment factor of the target potential assessment city is calculated according to the following formula: k=h1×m1+h2×m2+h3×m3; Among them, k is the initial potential assessment factor of the target potential assessment city, h1 is the third calculation coefficient, h2 is the fourth calculation coefficient, h3 is the fifth calculation coefficient, m1 is the number of markers to be extracted in the first pointing coefficient set, m2 is the number of markers to be extracted in the second pointing coefficient set, m3 is the number of markers to be extracted in the third pointing coefficient set, and h1>h2>h3, h1>0, h2>0, h3>0.

7. The urban potential assessment method based on multi-index fusion according to claim 1 is characterized in that: When generating a potential assessment identifier for a corresponding data source collection point based on the target environmental indicator data, it includes: Determine the standard environmental indicator data corresponding to each data source collection point; Comparing the target environmental indicator data with the standard environmental indicator data, and if the target environmental indicator data are both less than or equal to the standard environmental indicator data, generating the positive potential assessment identifier for the corresponding data source collection point; If the target environmental indicator data are all greater than the standard environmental indicator data, generating the negative potential assessment mark for the corresponding data source collection point; If one or more of the target environmental indicator data are greater than the standard environmental indicator data, and one or more of the target environmental indicator data are less than or equal to the standard environmental indicator data, the pending potential assessment identifier is generated for the corresponding data source collection point.

8. The urban potential assessment method based on multi-index fusion according to claim 1 is characterized in that: When setting the potential assessment optimization coefficient of the target potential assessment city according to the positive quantity and the negative quantity, it includes: Determine a ratio n of the positive quantity to the negative quantity; Presetting a first preset potential evaluation optimization coefficient, a second preset potential evaluation optimization coefficient, and a third preset potential evaluation optimization coefficient; When n≤1, the first preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city; When 1<n≤1.3, the second preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city; When 1.3<n, the third preset potential assessment optimization coefficient is used as the potential assessment optimization coefficient of the target potential assessment city.

9. A city potential assessment system based on multi-index fusion, applied to the city potential assessment method based on multi-index fusion according to any one of claims 1 to 8, characterized in that: include: A data determination module is used to deploy multiple data source collection points for the target potential assessment city, obtain initial environmental indicator data corresponding to each data source collection point, preprocess the initial environmental indicator data, and determine target environmental indicator data based on the preprocessing results; A first calculation module is used to extract target environmental indicator data of the same type from each data source collection point, construct a target environmental indicator data series, process the target environmental indicator data series, and calculate the environmental indicator data pointing coefficient of the target environmental indicator data series based on the processing result; a second calculation module, configured to divide all environmental indicator data pointing coefficients into sets based on a preset environmental indicator data pointing coefficient sequence, and calculate an initial potential assessment factor of the target potential assessment city based on the divided sets, wherein the preset environmental indicator data pointing coefficient sequence includes a first preset environmental indicator data pointing coefficient and a second preset environmental indicator data pointing coefficient; An identifier generation module is used to generate a potential assessment identifier for the corresponding data source collection point according to the target environmental indicator data, wherein the potential assessment identifier includes a positive potential assessment identifier, a negative potential assessment identifier, and a pending potential assessment identifier; an optimization setting module, configured to count the positive number of the positive potential assessment identifiers, count the negative number of the negative potential assessment identifiers, and set a potential assessment optimization coefficient for the target potential assessment city according to the positive number and the negative number; A potential assessment module is used to optimize the initial potential assessment factor based on the potential assessment optimization coefficient to obtain the target potential assessment factor of the target potential assessment city, wherein the target potential assessment factor is the product value of the potential assessment optimization coefficient and the initial potential assessment factor.

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