CN113393076A - AHP-based construction method of novel smart city evaluation index cutting model - Google Patents
AHP-based construction method of novel smart city evaluation index cutting model Download PDFInfo
- Publication number
- CN113393076A CN113393076A CN202110412898.3A CN202110412898A CN113393076A CN 113393076 A CN113393076 A CN 113393076A CN 202110412898 A CN202110412898 A CN 202110412898A CN 113393076 A CN113393076 A CN 113393076A
- Authority
- CN
- China
- Prior art keywords
- cities
- city
- evaluation index
- evaluation
- indexes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Abstract
The invention belongs to the field of smart city evaluation, and particularly relates to a construction method of a novel smart city evaluation index cutting model based on AHP. The method is characterized by combining a smart city evaluation index system at home and abroad, firstly constructing an evaluation index database, selecting proper evaluation indexes from the database according to different city characteristics, dynamically setting importance weights of the evaluation indexes based on an Analytic Hierarchy Process (AHP) and expert assignment, and completing automatic cutting of the evaluation indexes, thereby constructing a novel smart city evaluation index system model facing the city characteristics.
Description
Technical Field
The invention belongs to the field of smart city evaluation, and particularly relates to a construction method of a novel smart city evaluation index cutting model based on AHP.
Background
Novel wisdom city evaluation is a complicated engineering, and the evaluation coverage is wide, third party citizen experiences survey scale big, networking platform uses extensively, examination data source is many, need establish one set of scientific and practical's novel wisdom city evaluation index system for this reason, makes clear and makes clear away novel wisdom city working direction to promote the city construction actual effect conscientiously. How to carry out comprehensive evaluation of the smart city is different from the starting point of each country, each province and city, each research institution and scientific research personnel, and the construction methods of the evaluation index systems are different.
The regional scientific center team of the university of vienna conducted intensive research into the intellectualization of 468 cities with over 10 ten thousand population in 28 countries of the european union, and determined 3 major elements (technology, system and people) and 6 topics (intelligent governance, intelligent economy, intelligent mobility, intelligent environment, intelligent public and intelligent life) for the development of smart cities. The 6 themes also include 31 secondary and 74 tertiary metrics. The city residents are more emphasized, people-oriented is the core, the smart city is relatively mature in development and construction, and the environment, society and economy sustainable development and the smart city co-construction development mechanism and method system are worthy of reference of other countries.
IBM, a proposed concept of smart cities, describes a smart city as a system consisting of seven major factors of organization, business, government affairs, traffic, communication, water and energy, each of which is refined from 4 primary indexes. The assessment of a smart city should be based on people, business, government, traffic, communications, water and energy of the city system. The IBM smart city evaluation standard focuses on the evaluation of the construction level and the optimal standard, focuses on the breakthrough of the technology, and the set indexes are both objective indexes and lack of indexes on the subjective experience of citizens.
Since 1999, the Intelligent Community Forum (ICF) will perform annual Intelligent Community selection every year, and has a great influence on the world. The selection criteria included 5 permanent selection subject indicators: broadband connectivity, knowledge and labor, innovation, elimination of digital gaps, marketing and publicity, and later addition of "sustainability" indicators. The method focuses on evaluating the effectiveness of the broadband infrastructure in the community from the view of the government, lacks of attention to citizen perception, and has more qualitative indexes and less quantitative indexes in an index system.
The precursor of the 'novel smart city evaluation index system 3.0' is 'smart city index system 1.0' and 'smart city index system 2.0' of the Chinese edition released by Pudong smart city development research institute, and is jointly released in 2016 by national development committee, central network letter office and the like, and is an index system which is set up at the first national level of China and is put into use formally. The index system is formulated by taking 'people-oriented, convenient for people, performance-oriented and objective quantification' as a principle, comprises three parts of objective indexes, subjective indexes and self-selection indexes, comprises 8 first-level indexes, 21 second-level indexes and 54 third-level indexes, highly attaches importance to 'people' and guides construction key points of cities of China to a certain extent. Later, relevant departments adjust the weight of the indexes to finally form a system of 8 first-level indexes, 24 second-level indexes and 52 third-level indexes, wherein the L6 network security does not occupy the weight any more, and the indexes are deducted. The L8 citizens show that the questionnaire weight is improved from 20% to 40%, and from the perspective of improving the acquisition feeling and satisfaction degree of the citizens, the construction of smart cities in various regions is guided to focus more on the fields closely related to the life of the citizens. Accordingly, the total weight of the other 6 indicators was reduced from 80% to 60%. The L7 'innovation' is adjusted to 'innovation development', and the L1 'E-commerce service' is deleted from the secondary index item of the Hui-Min service, because the index item cannot be obtained, the evaluability is poor.
Since 1998, Taiwan began to invest in the construction of the smart city, and Taipei area won the first prize of the world Commission on the world Smart City. The evaluation indexes comprise two series of work and benefit, 6 primary indexes and 7 secondary indexes, wherein each secondary index comprises a current 2008 state value, an expected 2012 value and an expected 2016 value.
The Nanjing city information center references a plurality of evaluation methods and a smart city evaluation standard of IBM, and constructs a smart Nanjing evaluation index system which comprises 4 primary indexes of network interconnection, smart industry, smart service and smart humanity and 21 secondary evaluation indexes.
The research shows that different evaluation index systems have different emphasis points, some systems are guided by hardware technology, and some systems are guided by social and economic life; some of them highlight subjective indexes, and some pay attention to objective indexes; some employ static evaluation and some employ dynamic evaluation.
For the evaluation result, on one hand, the evaluation is scientific and effective by adopting a uniform index system for evaluation or ranking, all the evaluated cities construct smart cities according to a uniform mode, and the smart cities are modeled; on the other hand, the user is unfair and allowed by neglecting different characteristics of the evaluated city, and further, the user cannot perform subsequent smart city construction based on the characteristics of the city.
The European Union takes 468 cities in the geographic range as evaluation objects to comprehensively rank the cities, and the initiator is a Vienna university regional science center team, which is not from a government application level, so that the urban characteristics are weakened; the IBM smart city project is developed globally, and does not reflect the characteristics of a certain city by comparing the smart level of a certain city with the current best level or average level. Although the evaluation index system is constructed based on cities, Shanghai, Taiwan, Nanjing and the like, the characteristics of history, culture, tourism, commerce and the like which are not integrated into the cities do not exist. For example, Shanghai is an important economic, traffic, scientific, industrial, financial, exhibitions and shipping center in China, and the current evaluation indexes do not highlight the characteristics; nanjing is taken as a ten-dynasty conference and an important scientific and educational center in China, and the characteristics of the Chong and religious characters, the thick history and the cultural tourism of Nanjing are not reflected in an evaluation index system. How to construct an evaluation index system that can embody characteristics of different cities, such as how to evaluate national smart tourist cities, smart education cities, smart agriculture cities, smart industry cities, smart business cities, and smart resource cities.
The method is combined with a smart city evaluation index system at home and abroad, firstly, an evaluation index database is built, appropriate evaluation indexes are selected from the database according to different city characteristics, the importance weight of the evaluation indexes is dynamically set based on an Analytic Hierarchy Process (AHP) and expert assignment, and the automatic cutting of the evaluation indexes is completed, so that a novel smart city evaluation index system model facing the city characteristics is built.
Disclosure of Invention
Aiming at the problems, the invention provides a construction method of a novel smart city evaluation index cutting model based on AHP.
In order to achieve the purpose, the invention adopts the following technical scheme:
the construction method of the novel smart city evaluation index cutting model based on the AHP comprises the following steps:
step 1, an evaluation index database is constructed, for each city, the starting line, the advantages, the characteristics, the development potential, the attention degree and the progress degree of government enterprises and the public are different, so that the evaluation work of the smart city should be carried out for multiple times and multiple time periods, and along with the construction of the smart city, an evaluation index system of the smart city needs to be adjusted, enriched, deleted and improved in time, so that the index database has better timeliness, and dynamic management is realized. The comprehensive smart city evaluation index system records all possible related first-level, second-level and third-level evaluation indexes into an evaluation index database, performs hierarchical, modular and tree-shaped management on all the indexes, describes each third-level evaluation index in detail to define the evaluation range of the evaluation index, and performs addition, deletion, modification and check operations on the first-level, second-level and third-level indexes, wherein the modification and deletion operations need to be confirmed again by a user to prevent misoperation;
step 2, constructing a city attribute management database, and inputting all cities into the city attribute management database according to administrative codes, city names and belonged provinces of the cities, wherein the attributes of the cities mainly comprise province meetings, direct administration cities, capital cities, first-line cities, second-line cities and third-line cities, and the attributes of all the cities can be increased or deleted;
step 3, selecting proper evaluation indexes from the evaluation index database according to different city attributes;
and 4, dynamically setting the importance weight of the evaluation index based on the AHP and expert assignment, and finishing automatic cutting of the evaluation index so as to construct a novel smart city evaluation index cutting model.
Further, the city attribute management database in the step 2 is displayed in a visualization mode, and there are two query modes: tables and maps; in the form mode, all cities are arranged from small to large according to administrative codes, a user can quickly position the cities by inputting provinces or city names or position the cities by dragging a scroll bar on the right side of the form, and then the administrative codes, the provinces and the city attributes of the cities are displayed; in the map mode, a national map is displayed by default, a province is clicked, the map is switched to the province range, all cities and attribute information in the province are displayed on the right side of the window, and the cities and the attribute information are displayed according to the sequence of the administrative codes from small to large.
Further, in the step 4, based on AHP and expert assignment, the importance weight is dynamically set, and automatic cutting of the evaluation index is completed, so that a novel smart city evaluation index cutting model is constructed, and the specific steps are as follows:
and 4.1, constructing a hierarchical structure model, dividing a decision target, considered factors and a decision object into a target layer, a criterion layer and a scheme layer according to the mutual relation, drawing the hierarchical structure model, wherein the target layer corresponds to the selection of the novel smart city, the criterion layer corresponds to the evaluation index, the evaluation index database constructed in the step 1 is selected, the scheme layer corresponds to the selectable city, and different cities have the evaluation indexes after the step 3 is completed, so that the selectable cities exist under the evaluation index of the criterion layer.
4.2, constructing a pair comparison matrix, on the basis of the constructed hierarchical structure model, comparing the importance of a plurality of evaluation indexes of the smart city pairwise according to cities with different attributes and combining a mutual smart city evaluation index system under the suggestion of an expert, and setting a judgment comparison matrix;
step 4.3, calculating and judging the maximum eigenvalue lambda of the comparison matrixmaxThe corresponding feature vector is used as the weight of each evaluation index;
step 4.4, calculating a consistency index CI as shown in the formula (1), then calculating a consistency ratio CR as shown in the formula (2), comparing the consistency ratio CR with 0.1, and if the consistency ratio CR is less than 0.1, passing consistency check, namely using the weight for automatic cutting of the evaluation index;
wherein n is the order of the judgment matrix and is consistent with the number of the evaluation indexes, and RI is the random consistency of the n-order matrix.
Compared with the prior art, the invention has the following advantages:
the existing research cannot reflect the characteristics of different cities for the construction of a smart city evaluation index system. The invention dynamically sets the importance weight of the evaluation index based on an AHP method and expert assignment, and finishes automatic cutting of the evaluation index, thereby constructing a set of novel smart city evaluation index system model facing city characteristics, providing guidance and reference for building smart cities, and promoting the comprehensive development of the smart cities to a certain extent.
The model constructed by the method is basically consistent with the experience of experts, and the intelligent construction level of cities with different characteristics (attributes) can be objectively evaluated.
Drawings
FIG. 1 is an evaluation index database constructed according to the present invention;
FIG. 2 is a schematic diagram of a table schema of the present invention;
FIG. 3 is a schematic diagram of a map mode according to the present invention;
FIG. 4 is a hierarchical construction model constructed by the present invention.
Detailed Description
Example 1
AHP is a decision-making method suitable for multi-level and multi-target, can decompose the complicated problem into each individual component factor, then form hierarchical hierarchy structure with these individual factors, confirm the relative importance (weight) of the factor in each level through the way of comparing each other, form the decision-making method importance rank order finally. The AHP method usually requires that the consideration factors in the intermediate decision layer cannot exceed 9, and the wisdom city evaluation index is at most 8, so the wisdom city evaluation index meets the requirement.
The construction method of the novel smart city evaluation index cutting model based on the AHP comprises the following steps:
step 1, constructing an evaluation index database, integrating an evaluation index system of a smart city, inputting all possibly related first-level, second-level and third-level evaluation indexes into the evaluation index database, performing hierarchical, componentization and tree-shaped management on all the indexes, describing each third-level evaluation index in detail to define the evaluation range of the index, and performing addition, deletion, modification and check operations on the first-level, second-level and third-level indexes, wherein the modification and deletion operations need to be confirmed again by a user to prevent misoperation;
step 2, constructing a city attribute management database, and inputting all cities into the city attribute management database according to administrative codes, city names and belonged provinces of the cities, wherein the attributes of the cities mainly comprise province meetings, direct administration cities, capital cities, first-line cities, second-line cities and third-line cities, and the attributes of all the cities can be increased or deleted; the city attribute management database is displayed in a visual mode, and has two query modes: tables and maps; in the form mode (as shown in fig. 2), all cities are arranged from small to large according to the administrative codes, and a user quickly positions by inputting provinces or city names or positions by dragging a scroll bar on the right side of the form, so that the administrative codes, the provinces and the city attributes are displayed; in the map mode (as shown in fig. 3), a national map is displayed by default, a province is clicked, the map is switched to the province range, all cities and attribute information in the province are displayed on the right side of the window, and the cities and the attribute information are displayed according to the order of the administrative codes from small to large.
Step 3, selecting proper evaluation indexes from the evaluation index database according to different city attributes;
and 4, dynamically setting the importance weight of the evaluation index based on AHP and expert assignment, and finishing automatic cutting of the evaluation index, thereby constructing a novel smart city evaluation index cutting model, which comprises the following specific steps:
step 4.1, constructing a hierarchical structure model, dividing a decision target, considered factors and a decision object into a target layer, a criterion layer and a scheme layer according to the mutual relation, and drawing the hierarchical structure model (as shown in figure 4);
4.2, constructing a pair comparison matrix, on the basis of the constructed hierarchical structure model, comparing the importance of a plurality of evaluation indexes of the smart city pairwise according to cities with different attributes and combining a mutual smart city evaluation index system under the suggestion of an expert, and setting a judgment comparison matrix;
step 4.3, calculating and judging the maximum eigenvalue lambda of the comparison matrixmaxThe corresponding feature vector is used as the weight of each evaluation index;
step 4.4, calculating a consistency index CI as shown in the formula (1), then calculating a consistency ratio CR as shown in the formula (2), comparing the consistency ratio CR with 0.1, and if the consistency ratio CR is less than 0.1, passing consistency check, namely using the weight for automatic cutting of the evaluation index;
wherein n is the order of the judgment matrix and is consistent with the number of the evaluation indexes, and RI is the random consistency of the n-order matrix.
Example 2
The required data are all from data provided by the government, and the reliability and the scientificity of the smart city algorithm demonstration are guaranteed to the maximum extent. Six experts are selected from the expert library to carry out importance judgment on the indexes, the six experts come from governments, universities and enterprises respectively, and the six experts either directly participate in construction management of the smart city or have certain research on planning management of the smart city to understand the connotation of the smart city more, so that the reliability of the index weight is higher.
1) Smart tourist city evaluation
The smart tourism utilizes new technologies such as cloud computing and internet of things, achieves the purpose that information in the aspects of tourism resources, tourism economy, tourism activities and the like can be actively sensed before, during and after the tourism by means of a portable internet access terminal through the internet and the mobile internet, and improves the added value of tourists in each tourism link of eating, living, going, traveling, purchasing and entertaining. According to the definition of the smart tourist city, the information about the smart tourism in the global smart tourist city report and the Chinese city statistics yearbook, the importance of 7 evaluation indexes of the smart city is compared pairwise under the suggestion of six experts by combining 5 primary evaluation indexes (safety, integrity, service, intelligence and pleasure) in the Chinese smart tourist city and town construction index system, and a judgment matrix A is set as shown in a formula 3.
The maximum eigenvalue of the calculation matrix a is: lambda [ alpha ]max7.033, the eigenvector (weight vector) corresponding to the eigenvalue is: w ═ (0.0778, 0.0778,0.1980,0.0862,0.1649,0.0778,0.3176)TThe consistency index CI is 0.0055, the consistency ratio CR is 0.0048, and since 0.0048 is less than 0.1, the weight is used for the smart tourism evaluation of six province cities in the middle of China by consistency test, wherein the score condition of each primary index refers to 2016 version smart city evaluation results, as shown in table 1. As can be seen from the table, the intelligent tourism evaluation ranking of Wuhan, Hefei, Changsha and Nanchang is consistent with the ranking of the intelligent city, so that the intelligent tourism is emphasized during the construction of the intelligent city, and the Wuhan city with the first ranking is once honored by the name of the intelligent tourism city in China. In addition, the names of the Taiyuan city and the Zhengzhou city are interchanged, although the comprehensive ranking of the intelligent city of the Taiyuan city lags behind the Zhengzhou city and the Changsha, the intelligent tourism name exceeds the two cities, the reason is exactly because the Taiyuan city belongs to the temperate monsoon climate, the winter is not severe cold, the summer is not severe summer heat, the four seasons are bright, the city government is always dedicated to controlling mountains, water, gas and city, and the livable city is created by inclinationAnd the calling of creating smart cities can be actively responded, and overall planning, management and operation mechanisms are appointed, so that the ecological livable and innovation points are higher, and the smart tourism characteristics of the smart city are more obvious than those of the two cities.
TABLE 1 middle 6 province City Intelligent Tourism evaluation
2) City evaluation for intelligent education
According to '2019 white paper for intelligent education', intelligent education is an important component of a smart city, and based on key features of education services, new technologies such as internet of things, big data, artificial intelligence and cloud computing are fully utilized to be deeply integrated with education and teaching, so that intellectualization of education is promoted, and informatization construction of the education field in the smart city is promoted. The intelligent education establishes a borderless learning ecological environment through technical fusion, optimizes and configures education resources, matches the urbanization level with education development, forms a new education and teaching state, promotes education fairness, improves education quality, meets the lifelong learning requirement of citizens, and drives social progress. The two-level index education service most closely related to the intelligent education belongs to the L1 first-level index of the citizen-benefitting service, and meanwhile, the intelligent education needs the powerful support of L4 intelligent facilities and L5 information resources, so that the weights of the three first-level indexes are improved, under the suggestion of six experts, the importance of 7 evaluation indexes of the intelligent education city is compared pairwise, and a judgment matrix A is set, wherein the judgment matrix A is shown in a formula 4.
The maximum eigenvalue of the calculation matrix a is: lambda [ alpha ]max7.054, the eigenvector (weight vector) corresponding to the eigenvalue is: w ═ (0.3950, 0.0850,0.0850,0.1034,0.1662,0.0777,0.0878)TThe consistency index CI is 0.0116, the consistency ratio CR is 0.0088, and the consistency check is performed because 0.0088 is less than 0.1The weight is used for the intelligent education evaluation of the cities of six provinces in the middle of China, and the evaluation result is shown in a table 2 (the scores of the primary indexes of all cities are shown in a table 1). As can be seen from the table, the intelligent education ranking of Wuhan and Hefei and the intelligent city ranking are kept unchanged, which shows that the intelligent education can be grasped when the intelligent city is established; the number of the Huiming service scores of the Taiyuan city is slightly higher than that of the Zheng city, so the name is slightly more advanced than that of the Zheng city, but the information resource score of the Taiyuan is 0, and the first-level index accounts for a larger amount (15%), so the whole name of the Taiyuan is more advanced; although the innovation of the Changsha city is 0, the information resource score is 1.31, the scores of other first-level indexes are higher, particularly the score of the maximum number-of-people-benefit service (40%) is 21.3, so that the whole name is ranked at the 3 rd position; the benefits to the citizen of Nanchang are low in score, but the accurate management, information resources and citizen experience are high in score, so that the comprehensive ranking is centered and ranked at 4 th; comprehensive table and table 2, wuhan and do all can stably live in 1 and 2 regardless of wisdom city comprehensive ranking, wisdom tourism or wisdom education ranking.
Table 2 middle 6 province city intelligent education evaluation
The invention provides an evaluation index cutting model based on AHP (advanced high performance process) for smart cities with different characteristics. Firstly, a first-level index is selected, then a decision layer, an intermediate layer (index layer) and a scheme layer of a model are designed based on an AHP method, an importance matrix (judgment matrix) of pairwise comparison between indexes is set according to relevant information and experts in the field, and a feature vector corresponding to the maximum feature value of the matrix is calculated to serve as the weight of each index, so that dynamic cutting of the indexes is realized. The model is applied to a 2018-version novel smart city evaluation system and smart tourism and smart education evaluation of a 6-province city in the middle, and experimental results show that the model can be matched with the 2018-version expert experience, is suitable for smart city evaluation, can provide guidance and reference for building a smart city, and can promote the comprehensive development of the smart city to a certain extent.
Claims (3)
1. A construction method of a novel smart city evaluation index cutting model based on AHP is characterized by comprising the following steps:
step 1, constructing an evaluation index database, integrating an evaluation index system of a smart city, inputting all possibly related first-level, second-level and third-level evaluation indexes into the evaluation index database, performing hierarchical, componentization and tree-shaped management on all the indexes, describing each third-level evaluation index in detail to define the evaluation range of the index, and performing addition, deletion, modification and check operations on the first-level, second-level and third-level indexes, wherein the modification and deletion operations need to be confirmed again by a user to prevent misoperation;
step 2, constructing a city attribute management database, and inputting all cities into the city attribute management database according to administrative codes, city names and belonged provinces of the cities, wherein the attributes of the cities mainly comprise province meetings, direct administration cities, capital cities, first-line cities, second-line cities and third-line cities, and the attributes of all the cities can be increased or deleted;
step 3, selecting proper evaluation indexes from the evaluation index database according to different city attributes;
and 4, dynamically setting the importance weight of the evaluation index based on the AHP and expert assignment, and finishing automatic cutting of the evaluation index so as to construct a novel smart city evaluation index cutting model.
2. The method as claimed in claim 1, wherein the city attribute management database in step 2 is presented in a visual form, and there are two query modes: tables and maps; in the form mode, all cities are arranged from small to large according to administrative codes, a user can quickly position the cities by inputting provinces or city names or position the cities by dragging a scroll bar on the right side of the form, and then the administrative codes, the provinces and the city attributes of the cities are displayed; in the map mode, a national map is displayed by default, a province is clicked, the map is switched to the province range, all cities and attribute information in the province are displayed on the right side of the window, and the cities and the attribute information are displayed according to the sequence of the administrative codes from small to large.
3. The method for constructing the novel smart city evaluation index cutting model based on the AHP as claimed in claim 1, wherein in the step 4, the importance weight is dynamically set based on the AHP and the assignment of experts, and the automatic cutting of the evaluation index is completed, so as to construct the novel smart city evaluation index cutting model, specifically comprising the following steps:
step 4.1, constructing a hierarchical structure model, dividing a decision target, considered factors and a decision object into a target layer, a criterion layer and a scheme layer according to the mutual relation, and drawing the hierarchical structure model;
step 4.2, a pair comparison matrix is constructed, according to cities with different attributes, a mutual smart city evaluation index system is combined, under the suggestion of experts, the importance of a plurality of evaluation indexes of a smart city is compared pairwise, and a judgment comparison matrix is set;
step 4.3, calculating and judging the maximum eigenvalue lambda of the comparison matrixmaxThe corresponding feature vector is used as the weight of each evaluation index;
step 4.4, calculating a consistency index CI as shown in the formula (1), then calculating a consistency ratio CR as shown in the formula (2), comparing the consistency ratio CR with 0.1, and if the consistency ratio CR is less than 0.1, passing consistency check, namely using the weight for automatic cutting of the evaluation index;
wherein n is the order of the judgment matrix and is consistent with the number of the evaluation indexes, and RI is the random consistency of the n-order matrix.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110412898.3A CN113393076B (en) | 2021-04-16 | 2021-04-16 | AHP-based construction method of novel smart city evaluation index cutting model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110412898.3A CN113393076B (en) | 2021-04-16 | 2021-04-16 | AHP-based construction method of novel smart city evaluation index cutting model |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113393076A true CN113393076A (en) | 2021-09-14 |
| CN113393076B CN113393076B (en) | 2022-11-25 |
Family
ID=77617734
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110412898.3A Active CN113393076B (en) | 2021-04-16 | 2021-04-16 | AHP-based construction method of novel smart city evaluation index cutting model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113393076B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115456343A (en) * | 2022-08-11 | 2022-12-09 | 中国电子科技集团公司第二十八研究所 | Intelligent airport evaluation index system construction and evaluation method |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103345478A (en) * | 2013-06-17 | 2013-10-09 | 武汉天罡信息技术有限公司 | Universal identification coding system for smart city construction |
| CN107274061A (en) * | 2017-05-11 | 2017-10-20 | 安徽四创电子股份有限公司 | A kind of smart city evaluation method based on entropy assessment |
| CN107730112A (en) * | 2017-10-13 | 2018-02-23 | 常州工学院 | Livable City evaluation model based on analytic hierarchy process (AHP) |
| CN107742188A (en) * | 2017-11-06 | 2018-02-27 | 承德医学院 | A kind of College Teachers teaching and scientific research feedback on performance management system |
| CN107846409A (en) * | 2017-11-17 | 2018-03-27 | 广州葵翼信息科技有限公司 | A kind of smart city network integration and safety management system |
| CN108182650A (en) * | 2017-12-22 | 2018-06-19 | 王金刚 | A kind of city space Big Dipper Marking the cell and simplation visualizing system |
| CN109241077A (en) * | 2018-08-30 | 2019-01-18 | 东北大学 | Production target variation tendency visual query system and method based on similitude |
| CN109636132A (en) * | 2018-11-21 | 2019-04-16 | 武汉邮电科学研究院有限公司 | Evaluate AI analysis system and smart city evaluation method in smart city |
| CN109636150A (en) * | 2018-11-30 | 2019-04-16 | 南京市城市规划编制研究中心 | A kind of method for building up and its system of smart city " more rule unifications " appraisement system |
| CN109840768A (en) * | 2019-01-04 | 2019-06-04 | 烽火通信科技股份有限公司 | A kind of smart city evaluation index data managing method and system |
| CN111475545A (en) * | 2020-04-02 | 2020-07-31 | 湖南赛吉智慧城市建设管理有限公司 | City base database system for smart city |
| CN112101699A (en) * | 2020-07-24 | 2020-12-18 | 国网上海市电力公司 | Construction method of multi-station fusion site selection evaluation index system |
| CN112463797A (en) * | 2020-12-08 | 2021-03-09 | 航天信息股份有限公司 | Report generation method, system, storage medium and electronic equipment |
| CN112651667A (en) * | 2021-01-18 | 2021-04-13 | 长沙迅易信息科技有限公司 | Smart city analysis and evaluation method |
-
2021
- 2021-04-16 CN CN202110412898.3A patent/CN113393076B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103345478A (en) * | 2013-06-17 | 2013-10-09 | 武汉天罡信息技术有限公司 | Universal identification coding system for smart city construction |
| CN107274061A (en) * | 2017-05-11 | 2017-10-20 | 安徽四创电子股份有限公司 | A kind of smart city evaluation method based on entropy assessment |
| CN107730112A (en) * | 2017-10-13 | 2018-02-23 | 常州工学院 | Livable City evaluation model based on analytic hierarchy process (AHP) |
| CN107742188A (en) * | 2017-11-06 | 2018-02-27 | 承德医学院 | A kind of College Teachers teaching and scientific research feedback on performance management system |
| CN107846409A (en) * | 2017-11-17 | 2018-03-27 | 广州葵翼信息科技有限公司 | A kind of smart city network integration and safety management system |
| CN108182650A (en) * | 2017-12-22 | 2018-06-19 | 王金刚 | A kind of city space Big Dipper Marking the cell and simplation visualizing system |
| CN109241077A (en) * | 2018-08-30 | 2019-01-18 | 东北大学 | Production target variation tendency visual query system and method based on similitude |
| CN109636132A (en) * | 2018-11-21 | 2019-04-16 | 武汉邮电科学研究院有限公司 | Evaluate AI analysis system and smart city evaluation method in smart city |
| CN109636150A (en) * | 2018-11-30 | 2019-04-16 | 南京市城市规划编制研究中心 | A kind of method for building up and its system of smart city " more rule unifications " appraisement system |
| CN109840768A (en) * | 2019-01-04 | 2019-06-04 | 烽火通信科技股份有限公司 | A kind of smart city evaluation index data managing method and system |
| CN111475545A (en) * | 2020-04-02 | 2020-07-31 | 湖南赛吉智慧城市建设管理有限公司 | City base database system for smart city |
| CN112101699A (en) * | 2020-07-24 | 2020-12-18 | 国网上海市电力公司 | Construction method of multi-station fusion site selection evaluation index system |
| CN112463797A (en) * | 2020-12-08 | 2021-03-09 | 航天信息股份有限公司 | Report generation method, system, storage medium and electronic equipment |
| CN112651667A (en) * | 2021-01-18 | 2021-04-13 | 长沙迅易信息科技有限公司 | Smart city analysis and evaluation method |
Non-Patent Citations (3)
| Title |
|---|
| 何琴: "基于AHP的智慧城市建设水平评价模型及实证", 《统计与决策》 * |
| 赵勇等: "新型城镇化背景下智慧城市建设实践的思考――以河北省智慧城市试点为例", 《现代城市研究》 * |
| 韩清莹: "智慧城市管理共享系统的设计与实现", 《测绘通报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115456343A (en) * | 2022-08-11 | 2022-12-09 | 中国电子科技集团公司第二十八研究所 | Intelligent airport evaluation index system construction and evaluation method |
| CN115456343B (en) * | 2022-08-11 | 2023-11-10 | 中国电子科技集团公司第二十八研究所 | Intelligent airport evaluation index system construction and evaluation method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113393076B (en) | 2022-11-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Shen et al. | A holistic evaluation of smart city performance in the context of China | |
| Liu | Research on the teaching quality evaluation of physical education with intuitionistic fuzzy TOPSIS method | |
| Dikmen et al. | Strategic use of quality function deployment (QFD) in the construction industry | |
| Salvesen et al. | The importance of quality of life in the location decisions of new economy firms | |
| Zhang et al. | Research on smart city evaluation based on hierarchy of needs | |
| Ran et al. | Combining grey relational analysis and TOPSIS concepts for evaluating the technical innovation capability of high technology enterprises with fuzzy information | |
| CN113393076B (en) | AHP-based construction method of novel smart city evaluation index cutting model | |
| Wang et al. | Model construction of urban public sports service system under the background of information technology | |
| Kartika et al. | Management Effectiveness of Rinjani-Lombok Geopark on Geotourism Track | |
| Wan | Behavior of sports tourism consumers based on cloud computing and mobile big data | |
| Shi et al. | The Centre of City: Urban Central Structure | |
| Xu et al. | Analysis of The MICE Tourism Research in China in the Last Twenty Years | |
| Zhu | RETRACTED: Construction of ecological environment landscape evaluation system of small towns along the Huaihe River area based on fuzzy cloud model | |
| Shi et al. | Research on the construction of analytic hierarchy process of cultural tourism competitiveness | |
| Felbermaira et al. | Generation of a synthetic population for agent-based transport modelling with small sample travel survey data using statistical raster census data | |
| Ismail et al. | A fuzzy multi-criteria framework for the development of sustainable community-based tourism in Malaysia | |
| Zhang et al. | Evaluation System of Scientific Research Performance for Teachers of Humanities in American Colleges and Universities and Its Enlightenment | |
| Liu et al. | Establishment of Evaluation Index for Creative Cities: Application in Chengdu, China | |
| Zheng et al. | Construction of Evaluation Index System for the Ecological Civilization in Rural Tourism Destinations | |
| Wu et al. | Research on the evaluation and optimization model of community public space during the epidemic prevention period based on TOPSIS | |
| He et al. | Evaluation Index System of Urban Identity. | |
| He | Social Sustainability of Buildings Evaluation System Analysis & Development | |
| Xuebing et al. | Comparative Study on the Vitality of Typical Historical Districts in Beijing from the Perspective of Scene Theory | |
| Zhang et al. | Study on the Development Path of Mass Organizations in Henan Province: Based on the Empirical Analysis of Beijing, Shanghai, and Chongqing | |
| Solosina et al. | Analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of Voronezh region in Russia) |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |