CN117251492A - Intelligent park industry cluster data comparison analysis system and method - Google Patents
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Abstract
The invention relates to the technical field of industrial cluster data analysis, and provides a system and a method for comparing and analyzing industrial cluster data of an intelligent park, wherein the system comprises a data extraction subsystem, the data extraction subsystem is connected with a data analysis and comparison subsystem and a risk assessment subsystem through a data transmission technology, the risk assessment subsystem is used for establishing an intelligent park industrial cluster risk assessment model, and the data analysis and comparison subsystem and the risk assessment subsystem are connected with a data sorting module through the data transmission technology. The ratio of the industry occupation share of a specific area industry in the intelligent park to the industry occupation share of the whole intelligent park is obtained, so that the concept and recognition efficiency of the intelligent park industry cluster are improved, the occurrence of the concept and recognition confusion of the intelligent park industry cluster is avoided, the comprehensive evaluation value of the risk F is calculated, the structural adjustment lag or aging of the industry cluster is avoided, and the occurrence of the risk increase of the industry cluster is avoided.
Description
Technical Field
The invention relates to the technical field of industrial cluster data analysis, in particular to an intelligent park industrial cluster data comparison analysis system and method.
Background
An intelligent park refers to a standard building or building group which is generally planned and built by government (civil enterprises and government cooperations), has complete water supply, power supply, air supply, communication, road, storage and other supporting facilities, is reasonably distributed and can meet the requirements of production and scientific experiments in a specific industry, and comprises an industrial park, a logistics park, an urban industrial park, a scientific park, a creative park and the like. With the advent of economic globalization and knowledge economic age, successful industry clusters can generally maintain the prosperity for decades, and even make the economy of a smart park in a place become very natural for decades, and the industry clusters are determining factors for improving regional competitiveness and innovation and productivity environment, and are essentially the concept of innovation clusters, promoting enterprise innovation and upgrading and improving the competitiveness of the smart park.
However, the concept and the identification method of the industrial cluster of the smart park are more confusing at present, and the important reason is that the identification standard is lacking in operability, strong in practicability and high in reliability, and when the degree of dependence inside the industrial cluster is high and innovation is lacking, the industrial structure is regulated to be lagged or aged, the risk of the industrial cluster will appear, and the occurrence of the risk of the industrial cluster will not only affect the sustainable development of the industrial cluster, but also cause long-term fading of the economy of the smart park.
Therefore, we improve on this and propose a system and a method for comparing and analyzing industrial cluster data of intelligent parks.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the intelligent park industrial cluster concept and recognition efficiency are improved, the intelligent park industrial cluster concept and recognition confusion are avoided, through risk assessment and construction of a risk model, industrial structure adjustment lag or aging is reduced, and intelligent park economy degradation is avoided.
(II) technical scheme
In order to achieve the above object, the invention provides a smart park industrial cluster data comparison analysis system, which comprises a data extraction subsystem, wherein the data extraction subsystem is connected with a data analysis comparison subsystem and a risk assessment subsystem through a data transmission technology, and is used for acquiring basic data of a smart park industrial cluster and uploading the basic data to the data analysis comparison subsystem and the risk assessment subsystem, the data analysis comparison subsystem is used for calculating a location quotient LQ value, the risk assessment subsystem is used for establishing a smart park industrial cluster risk assessment model, the data analysis comparison subsystem and the risk assessment subsystem are both connected with a data arrangement module through a data transmission technology, and used for arranging the calculated result and the established model, the data arrangement module is connected with a database through the data transmission technology, and is used for storing the arranged data, and the database is also connected with a data inquiry subsystem through an internet technology and is used for rapidly inquiring data information arranged in the database by a user;
the data analysis and comparison subsystem comprises a data receiving module I, a data transmission technology and an industry cluster identification module I, wherein the data receiving module I is used for extracting key data of regions and industries in data, the industry cluster identification module is connected with an industry cluster calculation module through the data transmission module and used for calculating the LQ value of a location quotient, and the industry cluster calculation module is connected with a data uploading module II through the data transmission technology and used for uploading original data and calculation results;
the risk evaluation subsystem comprises a data receiving module II, wherein the data receiving module II is connected with a data component extraction module through a data transmission module and is used for extracting risk characteristics in data, the data component extraction module is connected with a risk evaluation calculation module through a data transmission technology and is used for calculating the risk characteristics to obtain a risk F comprehensive evaluation value and building a risk model, and the risk evaluation calculation module is connected with a data uploading module III through the data transmission technology and is used for uploading original data and the built risk model.
Preferably, the data extraction subsystem comprises a data input module, the data input module is connected with the abstract extraction module through a data transmission technology and is used for extracting key data in data to form an abstract, the abstract extraction module is connected with the keyword extraction module through the data transmission technology and is used for extracting keywords in the abstract, and the keyword extraction module is connected with the first data uploading module through the data transmission technology and is used for uploading the extracted abstract, keywords and original data.
Preferably, the data query subsystem comprises a keyword retrieval module, a summary retrieval module, a classification retrieval module and a semantic retrieval module, and is used for retrieving data description through the classification of keywords and partial content of the summary and data.
The intelligent park industry cluster data comparison analysis method is applied to the intelligent park industry cluster data comparison analysis system of any one of the above steps, and comprises the following steps
Step one: uploading original data, extracting key data in the original data through a data extraction subsystem to form a abstract, extracting keywords for retrieval from the abstract, and uploading the keywords to a data analysis comparison subsystem and a risk assessment subsystem;
step two: the data analysis and comparison subsystem extracts key information of regions and industries in the extracted data, and calculates the key information to obtain the location quotient LQ value;
step three: the risk evaluation subsystem extracts risk characteristics in the data, calculates the risk characteristics to obtain a comprehensive evaluation value of the risk F, and builds a risk model;
step four: and uploading the abstracts, the keywords and the calculated location quotient LQ values extracted by the original data connection and the constructed risk model to a data arrangement module, merging and arranging the data, and classifying and uploading the data to a database for storage.
Preferably, the third step and the fourth step are operated synchronously.
Preferably, in the third step, the location quotient LQ value is calculated as follows
Wherein LQ is ij For the locators of the i region j industry in the intelligent park, the ratio of the industry share of a specific region industry in the intelligent park to the industry share of the whole intelligent park is calculated.
Preferably, in the fourth step, the risk F comprehensive evaluation value is calculated as follows
F 1 ＝l 11 Z 1 +l 12 Z 2 +…+l 1g Z g
F 2 ＝l 21 Z 1 +l 22 Z 2 +…+l 2g Z g
……
F g ＝l g1 Z 1 +l g2 Z 2 +…+l gg Z g
Then
Wherein Z is g To study various index variables, F g For each main component extracted, l gg For factor load, a g Andand F is the comprehensive evaluation value, wherein the contribution rate is the h main component.
(III) beneficial effects
The intelligent park industry cluster data comparison analysis system and method provided by the invention have the beneficial effects that:
1. the ratio of the industry occupation share of a specific area industry in the intelligent park to the industry occupation share of the whole intelligent park is obtained by calculating the LQ value of the location quotient, so that the industrial specialization degree and dominant industry of the area can be determined, the concept and recognition efficiency of the intelligent park industry cluster are improved, and the occurrence of the concept and recognition confusion of the intelligent park industry cluster is avoided.
2. Through calculating the comprehensive evaluation value of the risk F, the risk assessment is carried out on the industrial cluster data of the intelligent park, a risk model is built, the situation that the industrial cluster is delayed in structural adjustment or aged, the industrial cluster risk is increased, the sustainable development of the industrial cluster of the intelligent park is affected, and the economic long-term decline of the intelligent park is caused is avoided.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a general system diagram of a system and method for comparing and analyzing industrial cluster data of an intelligent park provided by the present application;
FIG. 2 is a schematic diagram of a data extraction subsystem of the system and method for comparing and analyzing industrial cluster data of intelligent parks provided by the present application;
FIG. 3 is a schematic diagram of a data analysis and comparison subsystem of the intelligent park industry cluster data comparison analysis system and method provided in the present application;
FIG. 4 is a schematic diagram of a risk assessment subsystem of the intelligent campus industry cluster data comparison analysis system and method provided herein;
fig. 5 is a schematic diagram of a data query subsystem of the system and method for comparing and analyzing industrial cluster data of an intelligent park provided by the present application.
Detailed Description
The following detailed description of specific embodiments of the invention is provided in connection with the accompanying drawings and examples. The following examples are only illustrative of the present invention and are not intended to limit the scope of the invention.
As shown in fig. 1-5, the embodiment provides a smart park industrial cluster data comparison analysis system, which comprises a data extraction subsystem, wherein the data extraction subsystem is connected with a data analysis comparison subsystem and a risk assessment subsystem through a data transmission technology, and is used for acquiring basic data of the smart park industrial cluster and uploading the basic data to the data analysis comparison subsystem and the risk assessment subsystem, the data analysis comparison subsystem is used for calculating a regional quotient LQ value, the risk assessment subsystem is used for establishing a smart park industrial cluster risk assessment model, the data analysis comparison subsystem and the risk assessment subsystem are both connected with a data arrangement module through a data transmission technology, and used for arranging the calculated result and the established model, the data arrangement module is connected with a database through the data transmission technology, and is used for storing the arranged data, and the database is also connected with a data inquiry subsystem through an internet technology and is used for rapidly inquiring data information arranged in the database by a user;
the data analysis and comparison subsystem comprises a data receiving module I, a data transmission technology and an industry cluster identification module I, wherein the data receiving module I is used for extracting key data of regions and industries in data, the industry cluster identification module is connected with an industry cluster calculation module through the data transmission module and used for calculating the LQ value of a location quotient, and the industry cluster calculation module is connected with a data uploading module II through the data transmission technology and used for uploading original data and calculation results;
the ratio of the industry occupation share of a specific area industry in the intelligent park to the industry occupation share of the whole intelligent park is obtained by calculating the LQ value of the location quotient, so that the industrial specialization degree and dominant industry of the area can be determined, the concept and recognition efficiency of the intelligent park industry cluster are improved, and the occurrence of the concept and recognition confusion of the intelligent park industry cluster is avoided.
The risk evaluation subsystem comprises a data receiving module II, wherein the data receiving module II is connected with a data component extraction module through a data transmission module and is used for extracting risk characteristics in data, the data component extraction module is connected with a risk evaluation calculation module through a data transmission technology and is used for calculating the risk characteristics to obtain a risk F comprehensive evaluation value and building a risk model, and the risk evaluation calculation module is connected with a data uploading module III through the data transmission technology and is used for uploading original data and the built risk model.
Through calculating the comprehensive evaluation value of the risk F, the risk assessment is carried out on the industrial cluster data of the intelligent park, a risk model is built, the situation that the industrial cluster is delayed in structural adjustment or aged, the industrial cluster risk is increased, the sustainable development of the industrial cluster of the intelligent park is affected, and the economic long-term decline of the intelligent park is caused is avoided.
The data extraction subsystem comprises a data input module, the data input module is connected with a summary extraction module through a data transmission technology and is used for extracting key data in data to form a summary, the summary extraction module is connected with a keyword extraction module through the data transmission technology and is used for extracting keywords in the summary, and the keyword extraction module is connected with a data uploading module I through the data transmission technology and is used for uploading the extracted summary, keywords and original data.
The data query subsystem comprises a keyword retrieval module, a summary retrieval module, a classification retrieval module and a semantic retrieval module, and is used for classifying and retrieving data description through keywords and partial summary contents.
The key data in the original data is extracted to form the abstract, and the key words are extracted from the abstract, so that later-stage management personnel and users can conveniently search the sorted data and the original data, and the search efficiency is improved.
The intelligent park industry cluster data comparison analysis method is applied to the intelligent park industry cluster data comparison analysis system of any one of the above steps, and comprises the following steps
Step one: uploading original data, extracting key data in the original data through a data extraction subsystem to form a abstract, extracting keywords for retrieval from the abstract, and uploading the keywords to a data analysis comparison subsystem and a risk assessment subsystem;
step two: the data analysis and comparison subsystem extracts key information of regions and industries in the extracted data, and calculates the key information to obtain the location quotient LQ value;
step three: the risk evaluation subsystem extracts risk characteristics in the data, calculates the risk characteristics to obtain a comprehensive evaluation value of the risk F, and builds a risk model;
step four: and uploading the abstracts, the keywords and the calculated location quotient LQ values extracted by the original data connection and the constructed risk model to a data arrangement module, merging and arranging the data, and classifying and uploading the data to a database for storage.
And the third step and the fourth step are synchronously operated, so that the calculation efficiency of the comprehensive evaluation value of the interval quotient LQ value and the risk F is improved.
In the third step, the location quotient LQ value is calculated as follows
Wherein LQ is ij For the locators of the i region j industry in the intelligent park, the ratio of the industry share of a specific region industry in the intelligent park to the industry share of the whole intelligent park is calculated, and the regional industry specialization degree and dominant industry can be determined through LQ, when LQ>1, the j industry in the i area has a relatively advantage, and shows that the industry has stronger competitiveness to a certain extent, and the greater the LQ value is, the higher the specialization level of the industry is; when lq=1, it means that the j industry supply in region i happens to meet the local demand; when LQ<1, the i region j industry has a lower specialized level than the full intelligent park, and needs to import j industry products from outside the intelligent park to meet the needs in the intelligent park.
In the fourth step, the risk F comprehensive evaluation value is calculated as follows
F 1 ＝l 11 Z 1 +l 12 Z 2 +…+l 1g Z g
F 2 ＝l 21 Z 1 +l 22 Z 2 +…+l 2g Z g
……
F g ＝l g1 Z 1 +l g2 Z 2 +…+l gg Z g
Then
Wherein Z is g To study various index variables, F g For each main component extracted, l gg For factor load, a g Andfor the contribution rate of the h-th principal component, F is the comprehensive evaluation value, principal component analysis is to recombine a plurality of original indexes with certain correlation into a new independent comprehensive index to replace the information of the original indexes, wherein the variance of the first linear combination is usually used for expression, and the larger the variance is, the more information is contained, so that the first comprehensive index F selected in all linear combinations 1 Should be the largest variance, so is called F 1 If the first principal component is insufficient to represent the original index information, a second linear combination is selected to effectively reflect the original index information, F 1 Existing information need not be present in F 2 In a mathematical language, is expressed as the requirement Cov (F 1 ，F 2 ) =0, then call F 2 For the second principal component, a third, fourth, and so on can be constructed, up to the g-th principal component.
The above embodiments are only for illustrating the present invention, and are not limiting of the present invention. While the invention has been described in detail with reference to the embodiments, those skilled in the art will appreciate that various combinations, modifications, and substitutions can be made thereto without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (7)
1. The intelligent park industry cluster data comparison analysis system comprises a data extraction subsystem and is characterized in that: the data extraction subsystem is connected with the data analysis comparison subsystem and the risk assessment subsystem through data transmission technology, and is used for acquiring and uploading basic data of the intelligent park industrial cluster to the data analysis comparison subsystem and the risk assessment subsystem, the data analysis comparison subsystem is used for calculating the LQ value of the location quotient, the risk assessment subsystem is used for establishing an intelligent park industrial cluster risk assessment model, the data analysis comparison subsystem and the risk assessment subsystem are connected with the data arrangement module through data transmission technology, and used for arranging the calculated result and the established model, the data arrangement module is connected with the database through data transmission technology, and is used for storing the arranged data, and the database is further connected with the data inquiry subsystem through internet technology and is used for rapidly inquiring the arranged data information in the database by a user;
the data analysis and comparison subsystem comprises a data receiving module I, a data transmission technology and an industry cluster identification module I, wherein the data receiving module I is used for extracting key data of regions and industries in data, the industry cluster identification module is connected with an industry cluster calculation module through the data transmission module and used for calculating the LQ value of a location quotient, and the industry cluster calculation module is connected with a data uploading module II through the data transmission technology and used for uploading original data and calculation results;
the risk evaluation subsystem comprises a data receiving module II, wherein the data receiving module II is connected with a data component extraction module through a data transmission module and is used for extracting risk characteristics in data, the data component extraction module is connected with a risk evaluation calculation module through a data transmission technology and is used for calculating the risk characteristics to obtain a risk F comprehensive evaluation value and building a risk model, and the risk evaluation calculation module is connected with a data uploading module III through the data transmission technology and is used for uploading original data and the built risk model.
2. The intelligent campus industry cluster data comparison analysis system of claim 1, wherein: the data extraction subsystem comprises a data input module, the data input module is connected with a summary extraction module through a data transmission technology and is used for extracting key data in data to form a summary, the summary extraction module is connected with a keyword extraction module through the data transmission technology and is used for extracting keywords in the summary, and the keyword extraction module is connected with a data uploading module I through the data transmission technology and is used for uploading the extracted summary, keywords and original data.
3. The intelligent campus industry cluster data comparison analysis system of claim 1, wherein: the data query subsystem comprises a keyword retrieval module, a summary retrieval module, a classification retrieval module and a semantic retrieval module, and is used for classifying and retrieving data description through keywords and partial summary contents.
4. The comparison and analysis method for intelligent park industrial cluster data, applied to the comparison and analysis system for intelligent park industrial cluster data of any one of claims 1-3, is characterized in that: comprises the following steps
Step one: uploading original data, extracting key data in the original data through a data extraction subsystem to form a abstract, extracting keywords for retrieval from the abstract, and uploading the keywords to a data analysis comparison subsystem and a risk assessment subsystem;
step two: the data analysis and comparison subsystem extracts key information of regions and industries in the extracted data, and calculates the key information to obtain the location quotient LQ value;
step three: the risk evaluation subsystem extracts risk characteristics in the data, calculates the risk characteristics to obtain a comprehensive evaluation value of the risk F, and builds a risk model;
step four: and uploading the abstracts, the keywords and the calculated location quotient LQ values extracted by the original data connection and the constructed risk model to a data arrangement module, merging and arranging the data, and classifying and uploading the data to a database for storage.
5. The intelligent campus industry cluster data comparison analysis method according to claim 4, wherein: and the third step and the fourth step are synchronously operated.
6. The intelligent campus industry cluster data comparison analysis method according to claim 4, wherein: in the third step, the location quotient LQ value is calculated as follows
Wherein LQ is ij For the locators of the i region j industry in the intelligent park, the ratio of the industry share of a specific region industry in the intelligent park to the industry share of the whole intelligent park is calculated.
7. The intelligent campus industry cluster data comparison analysis method according to claim 4, wherein: in the fourth step, the risk F comprehensive evaluation value is calculated as follows
F 1 ＝l 11 Z 1 +l 12 Z 2 +…+l 1g Z g
F 2 ＝l 21 Z 1 +l 22 Z 2 +…+l 2g Z g
……
F g ＝l g1 Z 1 +l g2 Z 2 +…+l gg Z g
Then
Wherein Z is g To study various index variables, F g For each main component extracted, l gg For factor load, a g Andand F is the comprehensive evaluation value, wherein the contribution rate is the h main component.
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