CN113256083A - Evaluation method of power transmission line site selection and line selection model - Google Patents
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Abstract
The invention relates to an evaluation method of a power transmission line site selection line model, which overcomes the defect that no data analysis evaluation technology for the power transmission line site selection line model exists in the prior art. The invention comprises the following steps: constructing a hierarchical structure of influence factors of site selection and line selection of the power transmission line; constructing a judgment matrix based on the hierarchical structure; calculating the weight coefficient of each layer in the hierarchical structure based on the judgment matrix; calculating the evaluation score of the influence factor index data of the site selection and the line selection of the power transmission line based on the weight coefficient; and evaluating the power transmission line site selection and line selection model. The method comprises the steps of orderly constructing influence factors for site selection and line selection of the power transmission line by utilizing a hierarchical structure, constructing a judgment matrix based on the hierarchical structure, calculating weight coefficients of all layers in the hierarchical structure through the judgment matrix, calculating evaluation scores of influence factor index data based on the weight coefficients, and labeling the influence factor index data by utilizing the evaluation scores, thereby obtaining an evaluation result of a current model.
Description
Technical Field
The invention relates to the technical field of power transmission line site selection, in particular to an evaluation method of a power transmission line site selection model.
Background
With the rapid development of the current technology, the demand of people for electricity is higher and higher. The corresponding power grid planning is increasingly important, and the quality of the power grid planning determines whether the power grid can run efficiently, is stable and reliable, and has qualified power quality.
The core of the planning of the power grid is the site selection and the route selection of the power transmission line, which influences the power grid distribution, the economic development and the living standard of people in one place. The site selection and the line selection of the power transmission line are influenced by various factors, including external factors mainly including geographical terrain and climate temperature, and artificial factors such as social governments, human activities and the like.
The problem of site selection and line selection of the power transmission line can be considered to be complex and tedious, generally speaking, a site selection and line selection model of the power transmission line is established first, and then the layout of site selection and line selection of the power transmission line can be designed by combining the model and an algorithm. The algorithm is realized by a computer, and the design of the model is very important.
At present, evaluation research on a model for site selection and line selection of a power transmission line is less, and human factors play a leading role in most cases. Therefore, the reliability and the accuracy of the model cannot be guaranteed, and problems caused by site selection and line selection of the power transmission line in the later period can be caused.
Therefore, how to objectively evaluate the site selection and line selection model of the power transmission line based on the data analysis technology becomes a technical problem which needs to be solved urgently.
Disclosure of Invention
The invention aims to solve the defect that no data analysis and evaluation technology for a power transmission line site selection line model exists in the prior art, and provides an evaluation method for the power transmission line site selection line model to solve the problems.
In order to achieve the purpose, the technical scheme of the invention is as follows:
an evaluation method of a power transmission line site selection and line selection model comprises the following steps:
11) constructing a hierarchical structure of influence factors of site selection and line selection of the power transmission line: constructing a hierarchical structure according to influence factors of site selection and line selection of the power transmission line;
12) constructing a judgment matrix based on the hierarchical structure: constructing a judgment matrix based on an AHP scaling method;
13) calculating the weight coefficient of each layer in the hierarchical structure based on the judgment matrix;
14) calculating the evaluation score of the influence factor index data of the site selection and the line selection of the power transmission line based on the weight coefficient: weighting and summing the weight coefficients of each layer obtained by calculation and the index data scores of the corresponding influence factors, and calculating to obtain the evaluation score of the index data of the influence factors;
15) evaluating a power transmission line site selection and line selection model: and marking the influence factor index data based on the evaluation score to generate the evaluation of the power transmission line site selection and line selection model.
The construction of the hierarchical structure of the influence factors of site selection and line selection of the power transmission line comprises the following steps:
21) acquiring influence factors of site selection and line selection of the power transmission line;
22) the set hierarchical structure comprises a criterion layer and a sub-criterion layer, wherein the criterion layer comprises power grid distribution conditions, urban basic facilities, economic factors, environmental factors and social factors, and the sub-criterion layer is an influence factor of power transmission line site selection and line selection.
The step of constructing the judgment matrix based on the hierarchical structure comprises the following steps:
31) constructing an n criterion layer matrix A1And an index layer matrix A2–A6；
32) Alignment layer matrix A1And an index layer matrix A2–A6And assigning a specific gravity fraction.
The step of calculating the weight coefficient of each layer in the hierarchical structure based on the judgment matrix comprises the following steps:
41) for judgment matrix Al＝(aij)n×nPerforming evolution after continuous multiplication of elements in each line to obtain a feature vector
Namely:
42) for feature vector
Carrying out normalization operation to obtain a weight matrix Wl＝[w1,w2,…,wi,…,wn]TThe elements in the weight matrix are weight coefficients, wherein,
43) after the weight matrix is obtained, consistency check is carried out on the judgment matrix, and the method specifically comprises the following steps:
431) based on the decision matrix Al＝(aij)n×nAnd a weight matrix WlCalculating the maximum eigenvalue lambdalmax；
432) Based on the maximum eigenvalue lambdalmaxFor judgment matrix Al＝(aij)n×nPerforming a consistency check, namely:
RI is an average random consistency index, n is the order of a judgment matrix, and CR is a consistency ratio;
when n is 0 or 1, RI is 0; when n is 3, RI is 0.52; when n is 4, RI is 0.89; when n is 5, RI is 1.12; when n is 6, RI is 1.26; when n is 7, RI is 1.36; when n is 8, RI is 1.41;
44) when the judgment matrix does not meet the consistency test, the judgment matrix is adjusted, when CR is less than 0.1, the judgment matrix is considered to meet the consistency test, and the weight coefficient obtained by calculation is used for evaluating the score; otherwise, when the judgment matrix is not satisfied with the consistency check, the judgment matrix needs to be adjusted to obtain a new judgment matrix;
the judgment matrixes of the criterion layer and the sub-criterion layer constructed based on the 1-9 scale method are respectively shown as the following matrixes:
criterion layer matrix A1Comprises the following steps:
judgment matrix A of index layer2Comprises the following steps:
judgment matrix A of index layer3Comprises the following steps:
judgment matrix A of index layer4Comprises the following steps:
judgment matrix A of index layer5Comprises the following steps:
judgment matrix A of index layer6Comprises the following steps:
for decision matrix A1，
Calculating to obtain lambda1max＝5.6225，W1＝[0.1342 0.0894 0.0448 0.2236 0.5079]T；
For decision matrix A2Is calculated to obtain lambda2max＝3，W2＝[0.2 0.6 0.2]T；
For decision matrix A3Is calculated to obtain lambda3max＝3，W3＝[0.4286 0.4286 0.1428]T；
For decision matrix A4Is calculated to obtain lambda4max＝3.0536，W4＝[0.3325 0.5279 0.1396]T；
For decision matrix A5Is calculated to obtain lambda5max＝2，W5＝[0.3333 0.6667]T；
For decision matrix A6Is calculated to obtain lambda6max＝3，W6＝[0.2499 0.7501]T；
For decision matrix A1Is calculated to obtain
Thus judging the matrix A1Not meeting the consistency check, the judgment matrix A is needed1Adjusting;
for decision matrix A2Calculating to obtain CR2＝0<0.1, therefore, matrix A is judged2And the consistency test is satisfied.
The evaluation scoring step of calculating the index data of the influence factors of the site selection and the line selection of the power transmission line based on the weight coefficients comprises the following steps:
the formula for calculating the evaluation score of the influence factor index data based on the weight coefficient is as follows:
SR＝SA-SE；
in the formula, S is an evaluation score of each index, E is an expected value, and may be set in advance, or may be obtained by averaging the evaluation scores of each index, SA is a comprehensive evaluation value, SE is an overall expected value, and SR is a relative difference value.
The evaluation of the power transmission line site selection and line selection model comprises the following steps:
61) determining whether the influence factor index data is qualified according to the evaluation score of the influence factor index data, and then labeling the influence factor index data;
62) and comparing the evaluation score with a preset evaluation standard to determine whether the model is qualified, wherein the preset evaluation standard can refer to the following principles:
the evaluation score is in the range of 0-70, and SA is a difference;
the evaluation score is in the range of 70-80, and SA is medium;
the evaluation score is within the range of 80-90, and SA is good;
the evaluation score is in the range of 90-100, and SA is excellent;
SR is positive, the larger the numerical value is, the higher the data quality is; SR is negative, the larger the numerical value is, the lower the data quality is;
63) the values of SA are set to be between (80, 100) and the influencer indicator data with a positive SR is marked as pass, otherwise, the data is marked as fail.
Advantageous effects
Compared with the prior art, the evaluation method of the power transmission line site selection and line selection model has the advantages that the influence factors of the power transmission line site selection and line selection are orderly constructed by utilizing the hierarchical structure, the judgment matrix is constructed based on the hierarchical structure, the weight coefficients of all layers in the hierarchical structure are calculated through the judgment matrix, the evaluation score of the influence factor index data is calculated based on the weight coefficients, and the evaluation score is utilized to label the influence factor index data, so that the evaluation result of the current model is obtained.
According to the evaluation method of the model for site selection and line selection of the power transmission line, the hierarchical structure and the judgment matrix of the influence factors for constructing the site selection and line selection of the power transmission line are calculated to obtain the weight coefficients of all layers in the hierarchical structure, the evaluation score of the index data of the influence factors is further calculated, the index data of the influence factors are labeled according to the evaluation score, the model for site selection and line selection of the power transmission line which is currently considered is evaluated, and the reliability and the accuracy of the model are improved. The method solves the problem that the subsequent result objectivity is poor due to the fact that the traditional model evaluation method for selecting the site and the line of the power transmission line is mainly caused by people and different people experience judgment differences are large.
Drawings
FIG. 1 is a sequence diagram of the method of the present invention.
Detailed Description
So that the manner in which the above recited features of the present invention can be understood and readily understood, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings, wherein:
as shown in fig. 1, the method for evaluating the power transmission line site selection and line selection model according to the present invention includes the following steps:
firstly, constructing a hierarchical structure of influence factors of site selection and line selection of the power transmission line: and constructing a hierarchical structure according to influence factors of site selection and line selection of the power transmission line. The system is taken as a whole by adopting a hierarchical structure, factors of each layer are comprehensively considered, data are quantized, mathematical operation can be carried out, and accurate indexes are obtained. However, the selection factors are proper, and the accuracy of the result is easily influenced by too many factors and too few factors.
The method comprises the following specific steps:
(1) and obtaining influence factors of the site selection and the line selection of the power transmission line.
(2) The set hierarchical structure comprises a criterion layer and a sub-criterion layer, the criterion layer comprises power grid distribution conditions, urban basic facilities, economic factors, environmental factors and social factors, the sub-criterion layer is an influence factor of power transmission line site selection and line selection, and in practical application, the sub-criterion layer can be obtained from related documents in the past.
Secondly, constructing a judgment matrix based on the hierarchical structure: and constructing a judgment matrix based on an AHP scaling method. Firstly, constructing an n multiplied by n standard layer matrix A by utilizing a traditional AHP scaling method1And an index layer matrix A2–A6(ii) a Realigning criterion layer matrix A1And an index layer matrix A2–A6And assigning the specific gravity fraction, wherein the assignment of the specific gravity fraction can be comprehensively considered according to expert experience and comprehensive consideration factors of all aspects.
And thirdly, calculating the weight coefficient of each layer in the hierarchical structure based on the judgment matrix. The eigenvector of the weight coefficient matrix is obtained through quantification, so that the subjective influence caused by artificial assignment is reduced.
The method comprises the following specific steps:
(1) for judgment matrix Al＝(aij)n×nPerforming evolution after continuous multiplication of elements in each line to obtain a feature vector
Namely:
(2) for feature vector
Carrying out normalization operation to obtain a weight matrix Wl＝[w1,w2,…,wi,…,wn]TThe elements in the weight matrix are weight coefficients, wherein,
(3) after the weight matrix is obtained, consistency check is carried out on the judgment matrix, and the method specifically comprises the following steps:
A1) based on the decision matrix Al＝(aij)n×nAnd a weight matrix WlCalculating the maximum eigenvalue lambdalmax；
A2) Based on the maximum eigenvalue lambdalmaxFor judgment matrix Al＝(aij)n×nPerforming a consistency check, namely:
RI is an average random consistency index, n is the order of a judgment matrix, and CR is a consistency ratio;
when n is 0 or 1, RI is 0; when n is 3, RI is 0.52; when n is 4, RI is 0.89; when n is 5, RI is 1.12; when n is 6, RI is 1.26; when n is 7, RI is 1.36; when n is 8, RI is 1.41;
(4) when the judgment matrix does not meet the consistency test, the judgment matrix is adjusted, when CR is less than 0.1, the judgment matrix is considered to meet the consistency test, and the weight coefficient obtained by calculation is used for evaluating the score; otherwise, when the judgment matrix is not satisfied with the consistency check, the judgment matrix needs to be adjusted to obtain a new judgment matrix;
the judgment matrixes of the criterion layer and the sub-criterion layer constructed based on the 1-9 scale method are respectively shown as the following matrixes:
criterion layer matrix A1Comprises the following steps:
judgment matrix A of index layer2Comprises the following steps:
judgment matrix A of index layer3Comprises the following steps:
judgment matrix A of index layer4Comprises the following steps:
judgment matrix A of index layer5Comprises the following steps:
judgment matrix A of index layer6Comprises the following steps:
for decision matrix A1，
Calculating to obtain lambda1max＝5.6225，W1＝[0.1342 0.0894 0.0448 0.2236 0.5079]T；
For decision matrix A2Is calculated to obtain lambda2max＝3，W2＝[0.2 0.6 0.2]T；
For decision matrix A3Is calculated to obtain lambda3max＝3，W3＝[0.4286 0.4286 0.1428]T；
For decision matrix A4Is calculated to obtain lambda4max＝3.0536，W4＝[0.3325 0.5279 0.1396]T；
For decision matrix A5Is calculated to obtain lambda5max＝2，W5＝[0.3333 0.6667]T；
For decision matrix A6Is calculated to obtain lambda6max＝3，W6＝[0.2499 0.7501]T；
For decision matrix A1Is calculated to obtain
Thus judging the matrix A1Not meeting the consistency check, the judgment matrix A is needed1Adjusting;
for decision matrix A2Calculating to obtain CR2＝0<0.1, therefore, matrix A is judged2And the consistency test is satisfied.
Fourthly, calculating the evaluation score of the influence factor index data of the site selection and the line selection of the power transmission line based on the weight coefficient: and carrying out weighted summation on the weight coefficient of each layer obtained by calculation and the index data score of each corresponding influence factor, and calculating to obtain the evaluation score of the index data of the influence factors.
The formula for calculating the evaluation score of the influence factor index data based on the weight coefficient is as follows:
SR＝SA-SE；
in the formula, S is an evaluation score of each index, E is an expected value, and may be set in advance, or may be obtained by averaging the evaluation scores of each index, SA is a comprehensive evaluation value, SE is an overall expected value, and SR is a relative difference value.
And fifthly, evaluating the site selection and line selection model of the power transmission line: and marking the influence factor index data based on the evaluation score to generate the evaluation of the power transmission line site selection and line selection model. The method comprises the following specific steps:
(1) determining whether the influence factor index data is qualified according to the evaluation score of the influence factor index data, and then labeling the influence factor index data;
(2) and comparing the evaluation score with a preset evaluation standard to determine whether the model is qualified, wherein the preset evaluation standard can refer to the following principles:
the evaluation score is in the range of 0-70, and SA is a difference;
the evaluation score is in the range of 70-80, and SA is medium;
the evaluation score is within the range of 80-90, and SA is good;
the evaluation score is in the range of 90-100, and SA is excellent;
SR is positive, the larger the numerical value is, the higher the data quality is; SR is negative, the larger the numerical value is, the lower the data quality is;
(3) the values of SA are set to be between (80, 100) and the influencer indicator data with a positive SR is marked as pass, otherwise, the data is marked as fail.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. An evaluation method of a power transmission line site selection and line selection model is characterized by comprising the following steps:
11) constructing a hierarchical structure of influence factors of site selection and line selection of the power transmission line: constructing a hierarchical structure according to influence factors of site selection and line selection of the power transmission line;
12) constructing a judgment matrix based on the hierarchical structure: constructing a judgment matrix based on an AHP scaling method;
13) calculating the weight coefficient of each layer in the hierarchical structure based on the judgment matrix;
14) calculating the evaluation score of the influence factor index data of the site selection and the line selection of the power transmission line based on the weight coefficient: weighting and summing the weight coefficients of each layer obtained by calculation and the index data scores of the corresponding influence factors, and calculating to obtain the evaluation score of the index data of the influence factors;
15) evaluating a power transmission line site selection and line selection model: and marking the influence factor index data based on the evaluation score to generate the evaluation of the power transmission line site selection and line selection model.
2. The evaluation method of the power transmission line site selection and route selection model according to claim 1, wherein the step of constructing the hierarchical structure of the power transmission line site selection and route selection influence factors comprises the following steps:
21) acquiring influence factors of site selection and line selection of the power transmission line;
22) the set hierarchical structure comprises a criterion layer and a sub-criterion layer, wherein the criterion layer comprises power grid distribution conditions, urban basic facilities, economic factors, environmental factors and social factors, and the sub-criterion layer is an influence factor of power transmission line site selection and line selection.
3. The evaluation method of the power transmission line site selection and line selection model according to claim 1, wherein the step of constructing the judgment matrix based on the hierarchical structure comprises the following steps:
31) constructing an n criterion layer matrix A1And an index layer matrix A2–A6；
32) Alignment layer matrix A1And an index layer matrix A2–A6And assigning a specific gravity fraction.
4. The evaluation method of the power transmission line site selection and line selection model according to claim 1, wherein the step of calculating the weight coefficient of each layer in the hierarchical structure based on the judgment matrix comprises the following steps:
41) for judgment matrix Al＝(aij)n×nPerforming evolution after continuous multiplication of elements in each line to obtain a feature vector
Namely:
42) for feature vector Wl *Carrying out normalization operation to obtain a weight matrix Wl＝[w1,w2,…,wi,…,wn]TThe elements in the weight matrix are weight coefficients, wherein,
43) after the weight matrix is obtained, consistency check is carried out on the judgment matrix, and the method specifically comprises the following steps:
431) based on the decision matrix Al＝(aij)n×nAnd a weight matrix WlCalculating the maximum eigenvalue lambdalmax；
432) Based on the maximum eigenvalue lambdalmaxFor judgment matrix Al＝(aij)n×nPerforming a consistency check, namely:
RI is an average random consistency index, n is the order of a judgment matrix, and CR is a consistency ratio;
when n is 0 or 1, RI is 0; when n is 3, RI is 0.52; when n is 4, RI is 0.89; when n is 5, RI is 1.12;
when n is 6, RI is 1.26; when n is 7, RI is 1.36; when n is 8, RI is 1.41;
44) when the judgment matrix does not meet the consistency test, the judgment matrix is adjusted, when CR is less than 0.1, the judgment matrix is considered to meet the consistency test, and the weight coefficient obtained by calculation is used for evaluating the score; otherwise, when the judgment matrix is not satisfied with the consistency check, the judgment matrix needs to be adjusted to obtain a new judgment matrix;
the judgment matrixes of the criterion layer and the sub-criterion layer constructed based on the 1-9 scale method are respectively shown as the following matrixes:
criterion layer matrix A1Comprises the following steps:
judgment matrix A of index layer2Comprises the following steps:
judgment matrix A of index layer3Comprises the following steps:
judgment matrix A of index layer4Comprises the following steps:
judgment matrix A of index layer5Comprises the following steps:
judgment matrix A of index layer6Comprises the following steps:
for decision matrix A1，
Calculating to obtain lambda1max＝5.6225，W1＝[0.13420.08940.04480.22360.5079]T；
For decision matrix A2Is calculated to obtain lambda2max＝3，W2＝[0.20.60.2]T；
For decision matrix A3Is calculated to obtain lambda3max＝3，W3＝[0.42860.42860.1428]T；
For decision matrix A4Is calculated to obtain lambda4max＝3.0536，W4＝[0.33250.52790.1396]T；
For decision matrix A5Is calculated to obtain lambda5max＝2，W5＝[0.33330.6667]T；
For decision matrix A6Is calculated to obtain lambda6max＝3，W6＝[0.24990.7501]T；
For decision matrix A1Is calculated to obtain
Thus judging the matrix A1Not meeting the consistency check, the judgment matrix A is needed1Adjusting;
for decision matrix A2Calculating to obtain CR2＝0<0.1, therefore, matrix A is judged2And the consistency test is satisfied.
5. The method for evaluating the power transmission line site selection and route selection model according to claim 1, wherein the step of calculating the evaluation score of the power transmission line site selection and route selection influence factor index data based on the weight coefficient comprises the following steps:
the formula for calculating the evaluation score of the influence factor index data based on the weight coefficient is as follows:
SR＝SA-SE；
in the formula, S is an evaluation score of each index, E is an expected value, and may be set in advance, or may be obtained by averaging the evaluation scores of each index, SA is a comprehensive evaluation value, SE is an overall expected value, and SR is a relative difference value.
6. The method for evaluating the addressing and route selection model of the power transmission line according to claim 1, wherein the evaluation of the addressing and route selection model of the power transmission line comprises the following steps:
61) determining whether the influence factor index data is qualified according to the evaluation score of the influence factor index data, and then labeling the influence factor index data;
62) and comparing the evaluation score with a preset evaluation standard to determine whether the model is qualified, wherein the preset evaluation standard can refer to the following principles:
the evaluation score is in the range of 0-70, and SA is a difference;
the evaluation score is in the range of 70-80, and SA is medium;
the evaluation score is within the range of 80-90, and SA is good;
the evaluation score is in the range of 90-100, and SA is excellent;
SR is positive, the larger the numerical value is, the higher the data quality is; SR is negative, the larger the numerical value is, the lower the data quality is;
63) the values of SA are set to be between (80, 100) and the influencer indicator data with a positive SR is marked as pass, otherwise, the data is marked as fail.
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|---|---|---|---|---|
| CN116957414A (en) * | 2023-08-03 | 2023-10-27 | 武汉洪房房地产土地估价有限公司 | Village planning analysis method and device based on artificial intelligence |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016180127A1 (en) * | 2015-09-16 | 2016-11-17 | 中兴通讯股份有限公司 | Network performance evaluation method and system |
| CN106447205A (en) * | 2016-09-30 | 2017-02-22 | 国家电网公司 | Method for evaluating state of distribution automation terminal based on analytic hierarchy process |
| CN107609730A (en) * | 2017-07-27 | 2018-01-19 | 广西电网有限责任公司电力科学研究院 | A kind of method being classified based on AHP Fuzzy Evaluation Methods to sale of electricity company |
| CN111553396A (en) * | 2020-04-21 | 2020-08-18 | 广东电网有限责任公司电力科学研究院 | Online detection method and device for distribution automation terminal |
| CN112101700A (en) * | 2020-07-24 | 2020-12-18 | 国网上海市电力公司 | Evaluation method of multi-station fusion site selection index system |
-
2021
- 2021-05-08 CN CN202110499947.1A patent/CN113256083A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016180127A1 (en) * | 2015-09-16 | 2016-11-17 | 中兴通讯股份有限公司 | Network performance evaluation method and system |
| CN106447205A (en) * | 2016-09-30 | 2017-02-22 | 国家电网公司 | Method for evaluating state of distribution automation terminal based on analytic hierarchy process |
| CN107609730A (en) * | 2017-07-27 | 2018-01-19 | 广西电网有限责任公司电力科学研究院 | A kind of method being classified based on AHP Fuzzy Evaluation Methods to sale of electricity company |
| CN111553396A (en) * | 2020-04-21 | 2020-08-18 | 广东电网有限责任公司电力科学研究院 | Online detection method and device for distribution automation terminal |
| CN112101700A (en) * | 2020-07-24 | 2020-12-18 | 国网上海市电力公司 | Evaluation method of multi-station fusion site selection index system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116957414A (en) * | 2023-08-03 | 2023-10-27 | 武汉洪房房地产土地估价有限公司 | Village planning analysis method and device based on artificial intelligence |
| CN116957414B (en) * | 2023-08-03 | 2024-05-10 | 武汉洪房房地产土地估价有限公司 | Village planning analysis method and device based on artificial intelligence |
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