CN110751508B - Agricultural product market price early warning management system based on big data analysis - Google Patents
Agricultural product market price early warning management system based on big data analysis Download PDFInfo
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Abstract
The invention discloses an agricultural product market price early warning management system based on big data analysis, which relates to the technical field of big data analysis; the user unit, the service unit, the application supporting unit, the information resource unit and the infrastructure unit are mutually associated; the user unit is matched with an Internet user, a scientific research institution and a department service window; the service unit is internally provided with a data acquisition unit; the data acquisition unit is mutually associated with the scientific research institution management system, the department service management subsystem, the agricultural data acquisition subsystem, the object monitoring subsystem, the big data model, the mobile APP and the project management subsystem; the application supporting unit is provided with a portal service platform and a mobile terminal service platform; the method realizes the carding and classifying of various data assets of agricultural operation and transaction, and solves the problem of inconsistent data statistics and analysis caliber. The centralized prediction and early warning of the market price of the agricultural products are realized for the first time, and the agricultural product price prediction table can be provided for market reference.
Description
Technical Field
The invention belongs to the technical field of big data analysis, and particularly relates to an agricultural product market price early warning management system based on big data analysis.
Background
Colloquially speaking, people take food as the day; even if the technology is provided with a re-center, people can not support agricultural products in production and life. In the existing social situation of China, the development of agricultural products is indispensable due to numerous population, the planting industry and the animal husbandry are continuously developed, enlarged and perfected in China, but natural disasters, increased resource consumption, increased labor cost, increased transportation logistics cost caused by rain and snow weather, weaker organization operation capability and other factors occur in the agricultural product production process, and moreover, departments perform macroscopic regulation and control according to market conditions and the local supply quantity of agricultural products generates yield fluctuation along with the influx of the agricultural products entering the body from the outside, so that the planting industry, the animal husbandry and the produced agricultural products are precious and even have supply shortage phenomena, and therefore, frequent price fluctuation is caused in the agricultural product market. And thus there is a greater concern about changes in the market price of agricultural products. In the field of early warning and prediction of the price of agricultural products, the existing patent materials are mainly used for extracting price data of single agricultural products, monitoring production prices and the like, but natural conditions, production cost, transportation cost, human factors and the like are not involved, and the price of the agricultural products is not affected.
Therefore, development of a system related to early-warning, prediction and management of agricultural product prices with multi-azimuth statistical probability big data is needed.
Disclosure of Invention
To solve the problems existing in the prior art; the invention aims to provide an agricultural product market price early warning management system based on big data analysis.
The invention relates to an agricultural product market price early warning management system based on big data analysis, which comprises a user unit, a service unit, an application supporting unit, an information resource unit and an infrastructure unit; the user unit, the service unit, the application supporting unit, the information resource unit and the infrastructure unit are mutually associated;
the user unit is matched with an Internet user, a scientific research institution and a department service window;
the service unit is internally provided with a data acquisition unit; the data acquisition unit is mutually associated with the scientific research institution management system, the department service management subsystem, the agricultural data acquisition subsystem, the object monitoring subsystem, the big data model, the mobile APP and the project management subsystem;
the application supporting unit is provided with a portal service platform and a mobile terminal service platform;
the information resource unit comprises an agricultural product market price historical data module, a production data cost historical data module, a resident average dominant income historical data module, a resident consumption situation historical statistical data module, a seasonal price fluctuation historical data module, an on-season agricultural product market supply and demand statistical data module and an agricultural product transaction department macroscopic regulation and control module;
the infrastructure unit 5 comprises a department electronic cloud platform, a department network platform and a department disaster recovery center; the department electronic cloud platform, the department network platform and the department disaster recovery center are mutually associated with the portal service platform and the mobile terminal service platform; the infrastructure element is interrelated with the subsystem in the service element.
Preferably, the information resource unit is provided with a big data analysis system, a big data analysis model and a data visualization module; the big data analysis system, the big data analysis model and the agricultural product price index comprehensive model are related to each other; the data visualization module is mutually related to the agricultural product price early warning remote comprehensive billboard; the agricultural product price index comprehensive model is associated with a theoretical analysis result module; and the agricultural product price early warning remote comprehensive billboard is associated with the auxiliary decision-making module.
Preferably, the information resource unit is provided with a distributed storage module, i.e. all data are stored in a distributed manner according to the category.
Preferably, the data acquisition unit is mutually related with an agricultural product market price historical data module, a production data cost historical data module, a resident average dominant income historical data module, a resident consumption situation historical statistical data module, a seasonal price fluctuation historical data module, an agricultural product market supply and demand statistical data module in the current season and an agricultural product transaction department macroscopic regulation and control module.
Preferably, the application supporting unit is provided with a user management module, a role management module, a unit management module, a resource management module and an index management module; the user management module, the role management module, the unit management module, the resource management module and the index management module are mutually related with the portal service platform and the mobile terminal service platform, and the application support unit is provided with a form module, an instant message module, a short message module, a log management module and a system monitoring module; the form module, the instant message module, the short message module, the log management module, the system monitoring module, the user management module, the role management module, the unit management module, the resource management module and the index management module are mutually related.
Preferably, the big data analysis system and the big data analysis model are mutually related with a trend analysis module, a behavior analysis module and a price prediction module.
Preferably, the operation steps of the agricultural product market price early warning management system based on big data analysis are as follows:
s1, collecting production information and logistics transaction information of main agricultural varieties of grain crops, vegetables, fruits and livestock and poultry through the Internet, an agricultural scientific research institution and a department service window channel by a system; uploading to a central database server through an acquisition system;
s2, presetting matched monitoring data information in a system by a background manager, and managing all the monitoring data information by the manager;
s3, extracting main agricultural product market price historical data, main production data cost historical data, resident average dominant income historical data, resident consumption situation historical statistical data, main seasonal price fluctuation historical data, current season agricultural product market supply and demand statistical data, agricultural product transaction department macro regulation and control and the like of the whole market in an agricultural large data processing center agricultural operation transaction data warehouse according to a matching rule, constructing an agricultural product market distribution model and an agricultural product price prediction model according to regional, industry, carrier and space-time relationship dimensions, and forming an agricultural product market price early warning prediction analysis model information resource table;
s4, starting a big data analysis engine according to a preset task, calculating a standard sample and a label sample through an Apriori algorithm and a regression analysis algorithm through manually set sampling and analysis indexes, and enabling a calculation result to provide data analysis results such as a total value, a fractional item value, an interval value and a target value for a user, wherein a linear regression algorithm is required to be established for fractional item calculation and is stored on an analysis result server;
s5, building a set of agricultural product market price early warning prediction analysis model, providing an analysis result of building an agricultural product price fluctuation trend model by using a billboard, giving analysis reference comments, department response comments, industry development promotion comments and scientific production guidance comments for department related departments for regulating and controlling the price fluctuation of the agricultural product, providing model index analysis and big data analysis visual result display contents for each class of department supervision departments through data association, trend analysis, early warning prediction and data statistics provided by the data mining application billboard, and checking big data portrait analysis results of price trends of each class of agricultural products by department related users in the visual display result to assist department scientific supervision and accurate decision;
s6, comprehensively analyzing and early warning predicting the price of the agricultural products and related indexes in a data mining application billboard of the agricultural product market price early warning predicting analysis model, so that a main agricultural product market supervision department can timely master the agricultural production performance dynamics, timely adjust the agricultural production and agricultural supply side structural reform propulsion plan according to the change of the indexes, and improve the predicting, judging and executing capacity of the department;
s7, aiming at analysis results, a set of agricultural product price trend, price fluctuation, price distribution, price acquisition place and price and yield linkage trend graph guidance model is arranged, so that a user can select unused analysis indexes to predict the development dynamics of the agricultural product market price.
Compared with the prior art, the invention has the beneficial effects that:
1. in the data acquisition link, the data (grain crops, vegetables, fruits and livestock) can be acquired in various business systems, localized files (Excel), the Internet, agricultural scientific research institutions, department service windows and other channels, so that the diversity of acquisition channels is realized.
2. The method realizes the carding and classifying of various data assets of agricultural operation and transaction, breaks through the mutual conflict and contradiction of data seen at different user levels, and solves the problem of inconsistent data statistics and analysis caliber.
3. The centralized prediction and early warning of the market price of the agricultural products are realized for the first time, the occurrence of roller coaster type rising and falling of various agricultural product prices is reduced, and an agricultural product price prediction table can be provided for market reference.
4. In the supervision link, agricultural product price early warning and prediction functions are provided for departments of all levels, and data of all channels are used for: seven types of data such as production data cost historical data, resident average available income historical data, resident consumption condition historical statistical data, main seasonal price fluctuation historical data, current agricultural product market supply and demand statistical data, agricultural product transaction department macroscopic regulation and control information and the like are summarized and data association, trend analysis, early warning prediction, data statistics and other functions are realized, and the data indexes such as agricultural product price trend, price fluctuation, price distribution, price acquisition place, price and yield linkage trend graph and the like are used for carrying out index evaluation and prediction analysis on agricultural product price and related production information conditions.
Drawings
For ease of illustration, the invention is described in detail by the following detailed description and the accompanying drawings.
FIG. 1 is a schematic diagram of a system framework of the present invention;
FIG. 2 is a schematic diagram of a frame structure of a data acquisition unit according to the present invention;
fig. 3 is a schematic view of a frame structure to which the supporting unit 3 is applied in the present invention.
In the figure: a user unit 1, a service unit 2, an application support unit 3, an information resource unit 4, an infrastructure unit 5;
internet user 11, scientific research institution 12, department service window 13, and data acquisition unit 21
A scientific research institution management system 201, a department service management subsystem 202, an agricultural data collection subsystem 203, an object monitoring subsystem 204, a big data model 205, a mobile APP 206 and a project management subsystem 207;
portal service platform 31 and mobile terminal service platform 32
A user management module 301, a role management module 302, a unit management module 303, a resource management module 304, an index management module 305, a form module 306, an instant message module 307, a short message module 308, a log management module 309, and a system monitoring module 310;
the agricultural product market price historical data module 41, the production data cost price historical data module 42, the resident average dominant income historical data module 43, the resident consumption situation historical statistics data module 44, the seasonal price fluctuation historical data module 45, the on-season agricultural product market supply and demand statistics data module 46 and the agricultural product transaction department macroscopic regulation and control module 47;
department electronic cloud platform 51, department network platform 52 and department disaster recovery center 53
A big data analysis system 401, a big data analysis model 402, and a data visualization module 403.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention is described below by means of specific embodiments shown in the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.
It should be noted here that, in order to avoid obscuring the present invention due to unnecessary details, only structures and/or processing steps closely related to the solution according to the present invention are shown in the drawings, while other details not greatly related to the present invention are omitted.
As shown in fig. 1-3, the following technical solutions are adopted in this embodiment: it comprises a subscriber unit 1, a service unit 2, an application support unit 3, an information resource unit 4 and an infrastructure unit 5; the user units 1, the service units 2, the application support units 3, the information resource units 4 and the infrastructure units 5 are associated with each other; the user unit 1 is matched with an Internet user 11, a scientific research institution 12 and a department service window 13; the service unit 2 is provided with a data acquisition unit 21; the data acquisition unit 21 is mutually associated with a scientific research institution management system 201, a department service management subsystem 202, an agricultural data collection subsystem 203, an object monitoring subsystem 204, a big data model 205, a mobile APP 206 and a project management subsystem 207; a portal service platform 31 and a mobile terminal service platform 32 are arranged in the application supporting unit 3;
the information resource unit 4 comprises an agricultural product market price historical data module 41, a production data cost historical data module 42, a resident average dominant income historical data module 43, a resident consumption situation historical statistics data module 44, a seasonal price fluctuation historical data module 45, an on-season agricultural product market supply and demand statistics data module 46 and an agricultural product transaction department macro regulation and control module 47; the information resource unit 4 is provided with a big data analysis system 401, a big data analysis model 402 and a data visualization module 403; the big data analysis system, the big data analysis model and the agricultural product price index comprehensive model are related to each other; the data visualization module is mutually related to the agricultural product price early warning remote comprehensive billboard; the agricultural product price index comprehensive model is associated with a theoretical analysis result module; and the agricultural product price early warning remote comprehensive billboard is associated with the auxiliary decision-making module.
Further, a distributed storage module is disposed in the information resource unit 4, that is, all data are stored in a distributed manner according to the category.
Further, the data collection unit 21 is associated with an agricultural product market price historical data module 41, a production data cost historical data module 42, a resident average dominant income historical data module 43, a resident consumption situation historical statistics data module 44, a seasonal price fluctuation historical data module 45, an on-season agricultural product market supply and demand statistics data module 46 and an agricultural product transaction department macro regulation module 47.
The infrastructure unit 5 comprises a department electronic cloud platform 51, a department network platform 52 and a department disaster recovery center 53; the department electronic cloud platform 51, the department network platform 52 and the department disaster recovery center 53 are mutually associated with the portal service platform 31 and the mobile terminal service platform 32; the infrastructure element 5 is interrelated with the subsystems in the service element 2.
Wherein, the application supporting unit 3 is provided with a user management module 301, a role management module 302, a unit management module 303, a resource management module 304 and an index management module 305; the user management module 301, the role management module 302, the unit management module 303, the resource management module 304, the index management module 305 are associated with the portal service platform 31 and the mobile terminal service platform 32, and the application support unit 3 is provided with a form module 306, an instant message module 307, a short message module 308, a log management module 309 and a system monitoring module 310; the form module 306, the instant message module 307, the short message module 308, the log management module 309, the system monitoring module 310 are mutually associated with the user management module 301, the role management module 302, the unit management module 303, the resource management module 304 and the index management module 305.
In addition, the big data analysis system 401 and the big data analysis model 402 are associated with a trend analysis module, a behavior analysis module, and a price prediction module.
The operation steps of the agricultural product market price early warning management system based on big data analysis in the specific embodiment are as follows:
s1, the system collects production information and logistics transaction information of main agricultural varieties such as grain crops, vegetables, fruits, livestock and poultry and the like through channels such as the Internet, agricultural scientific research institutions and department service windows. And uploading the data to a central database server through the acquisition system.
S2, a background manager presets and matches monitoring data information (agricultural product market price historical data, main production data cost price historical data, resident average dominant income historical data, resident consumption situation historical statistical data, main seasonal price fluctuation historical data, current season agricultural product market supply and demand statistical data and agricultural product transaction department macroscopic regulation) in the system, and the manager can manage all monitoring data information.
And S3, extracting main agricultural product market price historical data, main production data cost historical data, resident average dominant income historical data, resident consumption situation historical statistical data, main seasonal price fluctuation historical data, current season agricultural product market supply and demand statistical data, agricultural product transaction department macroscopic regulation and control and the like of the whole market in an agricultural large data processing center agricultural operation and transaction data warehouse according to a matching rule, and constructing an agricultural product market distribution model and an agricultural product price prediction model according to the dimensions of regions, industries, carriers, space-time relations and the like to form an agricultural product market price early warning prediction analysis model information resource table.
S4, the system starts a big data analysis engine (timing task) according to a preset task, calculates standard samples and label samples through an Apriori algorithm and a regression analysis algorithm through manually set sampling and analysis indexes (regions, industries, carriers and time and space), and can provide data analysis results such as a total value, a component value, a section value, a target value and the like for a user through calculation results, wherein a linear regression algorithm is required to be established for component calculation and is stored on an analysis result server
S5, a set of agricultural product market price early warning prediction analysis model is built, an analysis result of an agricultural product price fluctuation trend model is built by applying a billboard, analysis reference comments for regulating and controlling the abnormal fluctuation of the agricultural product price, department response comments, industry development promotion comments and scientific production guidance comments are given to department related departments, the contents such as model index analysis, big data analysis visual result display and the like are provided for each department supervision department through the functions such as data association, trend analysis, early warning prediction and data statistics and the like provided in the data mining application billboard, and department related users can check the big data image analysis result of each type of agricultural product price trend in the visual display result, so that department scientific supervision and accurate decision are assisted.
S6, comprehensively analyzing and early warning predicting main agricultural product prices and related indexes in Tianjin all cities in a data mining application billboard of the agricultural product market price early warning predicting analysis model, so that main agricultural product market supervision departments can timely master agricultural production performance dynamics, timely adjust agricultural production and agricultural supply side structural reform propulsion plans according to index changes, and improve prediction prejudging and executing capacity of departments.
S7, aiming at analysis results, a set of agricultural product price trend, price fluctuation, price distribution, price acquisition place and price and yield linkage trend graph guidance model can be arranged, so that a user can select unused analysis indexes to predict the development dynamics of the agricultural product market price.
The system of the invention performs data mining and image analysis on the price trend and trend of the agricultural products by integrating the contents of the agricultural product market price historical data, the main production data cost historical data, the resident average available income historical data, the resident consumption situation historical statistical data, the main seasonal price fluctuation historical data, the current agricultural product market supply and demand statistical data, the agricultural product transaction department macroscopic regulation and control and the like, and performs early warning on future fluctuation factors and generation reasons of the price of the agricultural products according to the data association analysis and prediction results.
The big data analysis technology adopts a Hadoop+spark technical framework; the big data analysis model adopts a time-region-agricultural product-risk monitoring linear regression model (logistic regression) model) and an Apriori algorithm; big data visualization display adopts visualization tool zepplin/dataV; the framework system implementation language is Java+python; the system server comprises an application server and a database server.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (8)
1. An agricultural product market price early warning management system based on big data analysis is characterized in that: it comprises a user unit, a service unit, an application support unit, an information resource unit and an infrastructure unit; the user unit, the service unit, the application supporting unit, the information resource unit and the infrastructure unit are mutually associated;
the user unit is matched with an Internet user, a scientific research institution and a department service window;
the service unit is internally provided with a data acquisition unit; the data acquisition unit is mutually associated with the scientific research institution management system, the department service management subsystem, the agricultural data acquisition subsystem, the object monitoring subsystem, the big data model, the mobile APP and the project management subsystem;
the application supporting unit is provided with a portal service platform and a mobile terminal service platform;
the information resource unit comprises an agricultural product market price historical data module, a production data cost historical data module, a resident average dominant income historical data module, a resident consumption situation historical statistical data module, a seasonal price fluctuation historical data module, an on-season agricultural product market supply and demand statistical data module and an agricultural product transaction department macroscopic regulation and control module;
the infrastructure unit comprises a department electronic cloud platform, a department network platform and a department disaster recovery center; the department electronic cloud platform, the department network platform and the department disaster recovery center are mutually associated with the portal service platform and the mobile terminal service platform; the infrastructure element is interrelated with the subsystem in the service element;
the operation steps are as follows:
(S1) collecting production information and logistics transaction information of main agricultural varieties of grain crops, vegetables, fruits and livestock and poultry through the Internet, agricultural scientific research institutions and department service window channels by a system; uploading to a central database server through an acquisition system;
(S2) presetting matched monitoring data information in a system by a background manager, and managing all the monitoring data information by the manager;
(S3) extracting main agricultural product market price historical data, main production data cost historical data, resident average dominant income historical data, resident consumption situation historical statistics data, main seasonal price fluctuation historical data, current season agricultural product market supply and demand statistics data and agricultural product transaction department macroscopic regulation and control content of the whole market in an agricultural big data processing center agricultural operation and transaction data warehouse according to a matching rule, and constructing an agricultural product market distribution model and an agricultural product price prediction model according to regional, industry, carrier and space-time relationship dimensions to form an agricultural product market price early warning prediction analysis model information resource table;
(S4) starting a big data analysis engine according to a preset task, calculating a standard sample and a label sample through an Apriori algorithm and a regression analysis algorithm through manually set sampling and analysis indexes, and enabling a calculation result to provide a total value, a fractional value, an interval value and a target value data analysis result for a user, wherein a linear regression algorithm is required to be established for fractional calculation and is stored in an analysis result server;
(S5) a set of agricultural product market price early warning prediction analysis model is built, a set of agricultural product market price early warning prediction analysis model application billboard is used for providing analysis results for building an agricultural product price fluctuation trend model, analysis reference opinions for regulating and controlling the price fluctuation of agricultural products, department response opinions, industry development promotion opinions and scientific production guidance opinions are given to department related departments, model index analysis and big data analysis visual result display contents are provided for each class of department supervision departments through data association, trend analysis, early warning prediction and data statistics provided in the data mining application billboard, and department related users check big data portrait analysis results of price trends of each class of agricultural products in the visual display results, so that department scientific supervision and accurate decision are assisted;
(S6) comprehensively analyzing and early warning predicting the price of the agricultural products and related indexes in a data mining application billboard of the agricultural product market price early warning predicting analysis model, so that a main agricultural product market supervision department can timely master the dynamic performance of the agricultural production, timely adjust the structural reform propulsion plan of the agricultural production and the agricultural supply side according to the change of the indexes, and improve the predicting, judging and executing capacity of the department;
and S7, aiming at analysis results, a set of agricultural product price trend, price fluctuation, price distribution, price acquisition place and price and yield linkage trend graph guidance model is arranged, so that a user can select unused analysis indexes to predict the development dynamics of the agricultural product market price.
2. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: the information resource unit is provided with a big data analysis system, a big data analysis model and a data visualization module; the big data analysis system, the big data analysis model and the agricultural product price index comprehensive model are related to each other; the data visualization module is mutually related to the agricultural product price early warning remote comprehensive billboard; the agricultural product price index comprehensive model is associated with a theoretical analysis result module; and the agricultural product price early warning remote comprehensive billboard is associated with the auxiliary decision-making module.
3. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: and a distributed storage module is arranged in the information resource unit, namely all data are stored in a distributed mode according to the category.
4. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: the data acquisition unit is mutually related with the agricultural product market price historical data module, the production data cost historical data module, the resident average dominant income historical data module, the resident consumption situation historical statistical data module, the seasonal price fluctuation historical data module, the on-season agricultural product market supply and demand statistical data module and the agricultural product transaction department macroscopic regulation and control module.
5. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: the application supporting unit is provided with a user management module, a role management module, a unit management module, a resource management module and an index management module; the user management module, the role management module, the unit management module, the resource management module and the index management module are mutually related with the portal service platform and the mobile terminal service platform, and the application support unit is provided with a form module, an instant message module, a short message module, a log management module and a system monitoring module; the form module, the instant message module, the short message module, the log management module, the system monitoring module, the user management module, the role management module, the unit management module, the resource management module and the index management module are mutually related.
6. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: the big data analysis system and the big data analysis model are mutually related with the trend analysis module, the behavior analysis module and the price prediction module.
7. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: the management system performs data mining and image analysis on the price trend and trend of the agricultural products by integrating the agricultural product market price historical data, the main production data cost historical data, the resident average available income historical data, the resident consumption situation historical statistical data, the main seasonal price fluctuation historical data, the current agricultural product market supply and demand statistical data and the agricultural product transaction department macroscopic regulation and control content, and performs early warning on future fluctuation factors and generation reasons of the price of the agricultural products according to the data association analysis and prediction results.
8. The agricultural product market price pre-warning management system based on big data analysis of claim 1, wherein: the big data analysis technology in the management system adopts a Hadoop+spark technical framework; the big data analysis model adopts a time-region-agricultural product-risk monitoring linear regression model, a logistic model and an Apriori algorithm; big data visualization display adopts visualization tool zepplin/dataV; the framework system implementation language is Java+python; the system server comprises an application server and a database server.
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| CN111275498A (en) * | 2020-02-28 | 2020-06-12 | 山东爱城市网信息技术有限公司 | Method and system for constructing network retail price index of agricultural products |
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