CN112269912B - Agricultural big data price early warning management system and method - Google Patents
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Abstract
The invention discloses an agricultural big data price early warning management system and method.A data acquisition platform can acquire online and/or offline agricultural product price information in real time and upload the acquired agricultural product price information to a cloud end; the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity of agricultural products and establishes an agricultural product price risk identification model; the early warning display platform utilizes an agricultural product price risk identification model to perform early warning display of agricultural products according to regions, varieties and price risk identification degrees and performs push information management when the prices of the agricultural products trigger a set threshold value; the real-time mobile platform acquires the price information of the agricultural products at the cloud end and the early warning display and push information transmitted by the early warning display platform through the Internet. The invention realizes the price management function of agricultural production and management by utilizing agricultural big data from the aspects of agricultural product price data acquisition, price early warning information identification and early warning information management.
Description
Technical Field
The invention relates to the technical field of agricultural big data, in particular to a price early warning management system and method for agricultural big data.
Background
Agricultural products are important strategic materials for the relationship between the international civil and social orders, and the price of the agricultural products is a key factor for influencing the level of the price. Due to the asymmetry of supply and demand information of agricultural products and the action of natural risk factors, the market price of the agricultural products fluctuates violently. At present, the price monitoring and early warning of agricultural products is not mature, and due to seasonal, diverse and periodic crop characteristics of the agricultural products, a plurality of problems still exist in the aspects of data acquisition, data analysis, price risk degree identification and early warning information push.
Disclosure of Invention
The invention aims to provide an agricultural big data price early warning management system and method, which realize the price management function of agricultural production and operation by utilizing agricultural big data from the aspects of agricultural product price data acquisition, price early warning information identification and early warning information management.
In order to achieve the purpose, the agricultural big data price early warning management system provided by the invention comprises a data acquisition platform, a big data analysis platform, a real-time moving platform and an early warning display platform, wherein the data acquisition platform can acquire online and/or offline agricultural product price information in real time and upload the acquired agricultural product price information to a cloud end; the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity of agricultural products and establishes an agricultural product price risk identification model; the early warning display platform utilizes an agricultural product price risk identification model to perform early warning display of agricultural products according to regions, varieties and price risk identification degrees and performs push information management when the prices of the agricultural products trigger a set threshold value; the real-time mobile platform acquires agricultural product price information of a cloud end and early warning display and push information transmitted by the early warning display platform through the Internet.
As a further scheme of the invention: the data acquisition platform acquires the price information of the agricultural products by adopting one or more of an internet crawler system, a manual agricultural product price filling system, a batch agricultural product price importing system and an internet platform data interface management system.
As a still further scheme of the invention: the risk early warning, identifying and processing mode of the agricultural product price risk identification model for the agricultural product price comprises the following steps: taking the time T as an analysis time period, the average price of the agricultural product A at the time T is as follows: x = median of all data at this time T, average price of agricultural product a in the past at the same time T: a1= T all data mean 0.8+ T all data mean 0.1+ T all data mean after T, a1 calculation process with all data removed of maximum and minimum values; average price of agricultural product A in the past: a2= mean of all past data, with maximum and minimum values removed from all data in the calculation of a 2; deviation value a 1: comparing the average price X of the agricultural product A at the time T with the average price A1 at the same time in the past, and determining a deviation value a 1; deviation value a 2: comparing the average price X of the agricultural product A at the time T with the average price A2 in the past, and determining a deviation value a 2; the price deviation value a = a1 × 0.8+ a2 × 0.2 of the time T of the agricultural product a; after min-max of a is standardized, the current price is subjected to interval identification of risk early warning, and whether the risk degree of the price is high or low is judged.
As a still further scheme of the invention: after all possible early warning calculation values are subjected to min-max standardization, the early warning calculation values are divided into 7 intervals from small to large, and the intervals correspond to the grades respectively: negative heavy alarm, negative medium alarm, negative light alarm, normal level, positive light alarm, positive medium alarm, positive heavy alarm.
As a still further scheme of the invention: the early warning display platform displays the price risk early warning identification degree through a visual instrument panel and a color identifier, simultaneously sets the early warning level, and pushes reminding information to the real-time mobile platform in any one or more modes of a mobile phone short message, a mailbox and a WeChat when a set threshold value is triggered.
As a still further scheme of the invention: the early warning display platform shows the degree of price risk early warning discernment through visual panel board and colour sign and includes: the website home page displays the name of the agricultural product at the current time and a color identifier for representing the early warning level; clicking the name of the agricultural product to enter the specific price data billboard of the variety comprises the following steps: the price of the index in the week is minimum in the same period and maximum in the same period, and the average value of the last five years, the deviation weeks in the year are accumulated, the upward deviation weeks are accumulated, and the downward deviation weeks are accumulated; price bias situation: the price deviation direction of the week and the accumulated deviation week number of the year are represented by an instrument panel; the method comprises the steps that national price risk monitoring is displayed through a radar map, and the national price risk monitoring comprises five indexes, namely an accumulated deviation index, demand elasticity, a producing area concentration degree, a storage index and a public opinion index; the price trend of the national wholesale market is shown by a line graph, and the price is generally distributed in the past five years by a vertical bar graph; the system also comprises a wholesale market quotation and a price map, wherein the wholesale market quotation indexes comprise time, varieties, provinces, a wholesale market, a highest price, a lowest price and a bulk price; and news information and research reports related to the agricultural product.
As a still further scheme of the invention: the time T is any one of 3 days, weeks, two weeks and months.
As a still further scheme of the invention: the real-time mobile platform is an intelligent terminal, and the intelligent terminal acquires agricultural product price information of a cloud end through a mobile network or a wireless network.
The invention also provides an agricultural big data price early warning management method based on the system, which comprises the following steps:
(1) the data acquisition platform acquires the price information of the agricultural products and uploads the price information to the cloud end by adopting one or more of an internet crawler system, an agricultural product price manual filling system, an agricultural product price batch import system and an internet platform data interface management system;
(2) the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity of agricultural products, an agricultural product price risk identification model is established, the agricultural product price risk identification model takes time T as a unit, deviation values a1 of the time T average price X, the past same time T average price A1, the past average price A2 and X and A1 of any agricultural product, deviation values a2 of X and A2 and deviation values a = a1 0.8+ a2 0.2 of the time T price of the agricultural product A, after min-max of a is standardized, interval identification of risk early warning is carried out on the current price, and the risk degree of the price is judged;
(3) after the early warning display platform carries out min-max standardization on all possible early warning calculation values, the early warning display platform is divided into 7 intervals from small to big equally, and the intervals correspond to the grades respectively: a negative heavy alarm, a negative medium alarm, a negative light alarm, a normal level, a positive light alarm, a positive medium alarm, a positive heavy alarm; the early warning display is carried out on agricultural products in different areas, different varieties and different price risk identification degrees at a terminal and the information pushing management is carried out when the price of the agricultural products triggers a set threshold value through the self-defined setting of the early warning module;
(4) the real-time mobile platform acquires agricultural product price information stored in the cloud in real time and acquires reminding information pushed by the early warning display platform in any one or more modes of a short message, a mailbox and a WeChat.
Compared with the prior art, the invention has the beneficial effects that: the invention establishes a management system integrating data management, visual display and information feedback, and realizes the whole process management of the agricultural product price early warning information data. The result of the early warning analysis is stored and displayed in the form of an image, the visualization degree is high, and the user operation is friendly; through the aspects of acquisition of price data of agricultural products, identification of price early warning information and management of the early warning information, the price management function of agricultural production management by utilizing agricultural big data is realized, the early warning data is reasonable, and the pushing result is timely and effective.
Drawings
FIG. 1 is a functional block diagram of an agricultural big data price early warning management system according to the present invention;
FIG. 2 is a functional block diagram of the price early warning platform of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 and 2, the agricultural big data price early warning management system provided by the invention comprises a data acquisition platform, a big data analysis platform, a real-time mobile platform and an early warning display platform.
The data acquisition platform acquires the price information of the agricultural products in various modes by adopting an internet crawler system, an agricultural product price manual filling system, an agricultural product price batch import system and an internet platform data interface management system, and related data are cleaned and stored to the cloud.
And the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity attributes of various agricultural products through establishing an agricultural product price risk identification model. If the risk early warning identification processing mode aiming at the price of the agricultural products is as follows: the average price per week of agricultural product a, as analyzed by the degree of week: x = median of all data for this week, average past week for agricultural product a: a1= average of all data (maximum and minimum subtracted) of the same week in the past 0.8+ average of all data (maximum and minimum subtracted) of the week before the same week in the past 0.1+ average of all data (maximum and minimum subtracted) of the week after the same week in the past 0.1; average price of agricultural product A in the past: a2= mean of all past data (maximum and minimum subtracted); deviation value a 1: comparing the average price X of the agricultural product A in the week with the average price A1 in the past, and determining a deviation value a 1; deviation value a 2: comparing the current week average price X of the agricultural product A with the past average price A2, and determining a deviation value a 2; produce a this week price deviation a = a1 × 0.8+ a2 × 0.2. After min-max of a is standardized, the interval of risk early warning can be identified for the current price, and whether the risk degree of the price is high or low is judged.
The early warning display platform can realize early warning display and push management of different regions, different varieties and different price risk identification degrees through the self-defined setting of the early warning module, can display at a mobile terminal and a PC terminal in real time, and can also carry out push management on users in modes of mobile phone short messages, emails and the like. If the early warning display platform performs early warning display according to the early warning values calculated by the big data analysis platform, one display mode is that after all possible early warning calculation values are subjected to min-max standardization, 7 intervals are equally divided from small to big. The 7 intervals from small to large correspond to the grades respectively: negative heavy alarm, negative medium alarm, negative light alarm, normal level, positive light alarm, positive medium alarm, positive heavy alarm. The degree of price risk early warning identification by utilizing a visual instrument panel and a visual color identifier is displayed through website release, and meanwhile, the early warning level can be set in a management background so that reminding information can be pushed to a user in a mode of mobile phone short messages, mailboxes and the like when a set threshold value is triggered.
The real-time mobile platform comprises an intelligent terminal, and the intelligent terminal acquires real-time agricultural data of a cloud end through a mobile network or WIFI.
In the actual service management, the method also comprises early warning plan management, service user management, data reporting, authority management and system interface setting.
The agricultural big data price early warning management method comprises the following steps:
(1) the data acquisition platform adopts an internet crawler system, an agricultural product price manual filling system, an agricultural product price batch import system and an internet platform data interface management system to capture agricultural product price information in multiple modes and upload the information to the cloud;
(2) the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity of agricultural products, an agricultural product price risk identification model is established, the agricultural product price risk identification model takes week T as a unit, deviation values a1 of the T average price X of the week of any agricultural product, the T average price A1 of the same week in the past, the A2 of the average price in the past and the A1 of the week in the past, deviation values a2 of the X and the A2 of the week of the agricultural product, and deviation values a = a1 0.8+ a2 0.2 of the T price of the week of the agricultural product A, after min-max of a is standardized, interval identification of risk early warning is carried out on the current price, and the risk degree of the price is judged;
(3) after the early warning display platform carries out min-max standardization on all possible early warning calculation values, the early warning display platform is divided into 7 intervals from small to big equally, and the intervals correspond to the grades respectively: a negative heavy alarm, a negative medium alarm, a negative light alarm, a normal level, a positive light alarm, a positive medium alarm, a positive heavy alarm; through the self-defined setting of the early warning module, agricultural products in different areas, different varieties and different price risk identification degrees are subjected to early warning display at a terminal through release control management, and information pushing management is carried out when the price of the agricultural products triggers a set threshold value, wherein the release mode comprises short message information, FTP transmission, MAIL and websites;
inputting a website http:// quote. agndata. cn/edge/risk Assessment _ pc. html, entering a main page, displaying year and week on the main page, respectively representing a negative heavy alarm, a negative middle alarm, a negative light alarm, a normal level, a positive light alarm, a positive middle alarm and a positive heavy alarm by different colors, wherein the front of each variety name is colored to represent the current price grade, clicking the variety name to enter a specific price data billboard of the variety, including the index price of the week, the minimum and the maximum in the same period, the average value of the last five years, the accumulated deviated week number of the year, the accumulated upwards deviated week number and the accumulated downwards deviated week number; price bias situation: the price deviation direction of the week and the accumulated deviation week number of the year are represented by an instrument panel; the method comprises the steps that national price risk monitoring is displayed through a radar map, and the national price risk monitoring comprises five indexes, namely an accumulated deviation index, demand elasticity, a producing area concentration degree, a storage index and a public opinion index; the price trend of the national wholesale market is shown by a line graph, and the price is generally distributed in the past five years by a vertical bar graph; the system also comprises a wholesale market quotation and a price map, wherein the wholesale market quotation indexes comprise time, varieties, provinces, a wholesale market, a highest price, a lowest price and a bulk price; and news information and research reports related to the agricultural product;
(4) the real-time mobile platform acquires agricultural product price information stored in the cloud in real time and acquires reminding information pushed by the early warning display platform through a mobile phone short message and a mailbox.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (8)
1. The utility model provides an agricultural big data price early warning management system which characterized in that: the online and/or offline agricultural product price information monitoring system comprises a data acquisition platform, a big data analysis platform, a real-time mobile platform and an early warning display platform, wherein the data acquisition platform can acquire online and/or offline agricultural product price information in real time and upload the acquired agricultural product price information to a cloud end; the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity of agricultural products and establishes an agricultural product price risk identification model; the early warning display platform utilizes an agricultural product price risk identification model to perform early warning display of agricultural products according to regions, varieties and price risk identification degrees and performs push information management when the prices of the agricultural products trigger a set threshold value; the real-time mobile platform acquires agricultural product price information at the cloud end and early warning display and push information transmitted by the early warning display platform through the Internet;
the risk early warning, identifying and processing mode of the agricultural product price risk identification model for the agricultural product price comprises the following steps: taking the time T as an analysis time period, the average price of the agricultural product A at the time T is as follows: x = median of all data at this time T, average price of agricultural product a in the past at the same time T: a1= T all data mean 0.8+ T all data mean 0.1+ T all data mean after T, a1 calculation process with all data removed of maximum and minimum values; average price of agricultural product A in the past: a2= mean of all past data, with maximum and minimum values removed from all data in the calculation of a 2; deviation value a 1: comparing the average price X of the agricultural product A at the time T with the average price A1 at the same time in the past, and determining a deviation value a 1; deviation value a 2: comparing the average price X of the agricultural product A at the time T with the average price A2 in the past, and determining a deviation value a 2; the price deviation value a = a1 × 0.8+ a2 × 0.2 of the time T of the agricultural product a; after min-max of a is standardized, the current price is subjected to interval identification of risk early warning, and whether the risk degree of the price is high or low is judged.
2. The agricultural big data price early warning management system of claim 1, wherein: the data acquisition platform acquires the price information of the agricultural products by adopting one or more of an internet crawler system, a manual agricultural product price filling system, a batch agricultural product price importing system and an internet platform data interface management system.
3. The agricultural big data price early warning management system of claim 1, wherein: after all possible early warning calculation values are subjected to min-max standardization, the early warning calculation values are divided into 7 intervals from small to large, and the intervals correspond to the grades respectively: negative heavy alarm, negative medium alarm, negative light alarm, normal level, positive light alarm, positive medium alarm, positive heavy alarm.
4. The agricultural big data price early warning management system of claim 3, wherein: the early warning display platform displays the price risk early warning identification degree through a visual instrument panel and a color identifier, simultaneously sets the early warning level, and pushes reminding information to the real-time mobile platform in any one or more modes of a mobile phone short message, a mailbox and a WeChat when a set threshold value is triggered.
5. The agricultural big data price early warning management system of claim 4, wherein: the early warning display platform shows the degree of price risk early warning discernment through visual panel board and colour sign and includes: the website home page displays the name of the agricultural product at the current time and a color identifier for representing the early warning level; clicking the name of the agricultural product to enter the specific price data billboard of the variety comprises the following steps: the price of the index in the week is minimum in the same period and maximum in the same period, and the average value of the last five years, the deviation weeks in the year are accumulated, the upward deviation weeks are accumulated, and the downward deviation weeks are accumulated; price bias situation: the price deviation direction of the week and the accumulated deviation week number of the year are represented by an instrument panel; the method comprises the steps that national price risk monitoring is displayed through a radar map, and the national price risk monitoring comprises five indexes, namely an accumulated deviation index, demand elasticity, a producing area concentration degree, a storage index and a public opinion index; the price trend of the national wholesale market is shown by a line graph, and the price is generally distributed in the past five years by a vertical bar graph; the system also comprises a wholesale market quotation and a price map, wherein the wholesale market quotation indexes comprise time, varieties, provinces, a wholesale market, a highest price, a lowest price and a bulk price; and news information and research reports related to the agricultural product.
6. The agricultural big data price early warning management system of claim 1, wherein: the time T is any one of 3 days, weeks, two weeks and months.
7. The agricultural big data price early warning management system of claim 1, wherein: the real-time mobile platform is an intelligent terminal, and the intelligent terminal acquires agricultural product price information of a cloud end through a mobile network or a wireless network.
8. The agricultural big data price early warning management method for the agricultural big data price early warning management system according to claim 1, which is characterized by comprising the following steps:
(1) the data acquisition platform acquires the price information of the agricultural products and uploads the price information to the cloud end by adopting one or more of an internet crawler system, an agricultural product price manual filling system, an agricultural product price batch import system and an internet platform data interface management system;
(2) the big data analysis platform analyzes supply and demand attributes, seasonality and periodicity of agricultural products, and establishes an agricultural product price risk identification model, wherein the agricultural product price risk identification model takes time T as a unit, and agricultural products A are equal in price at the time T: x = median of all data at this time T, average price of agricultural product a in the past at the same time T: a1= T all data mean 0.8+ T all data mean 0.1+ T all data mean after T, a1 calculation process with all data removed of maximum and minimum values; average price of agricultural product A in the past: a2= mean of all past data, with maximum and minimum values removed from all data in the calculation of a 2; deviation value a 1: comparing the average price X of the agricultural product A at the time T with the average price A1 at the same time in the past, and determining a deviation value a 1; deviation value a 2: comparing the average price X of the agricultural product A at the time T with the average price A2 in the past, and determining a deviation value a 2; the price deviation value a = a1 × 0.8+ a2 × 0.2 of the time T of the agricultural product a; after min-max of a is standardized, carrying out risk early warning interval identification on the current price, and judging whether the risk degree of the price is high or low;
(3) after the early warning display platform carries out min-max standardization on all possible early warning calculation values, the early warning display platform is divided into 7 intervals from small to big equally, and the intervals correspond to the grades respectively: a negative heavy alarm, a negative medium alarm, a negative light alarm, a normal level, a positive light alarm, a positive medium alarm, a positive heavy alarm; the early warning display is carried out on agricultural products in different areas, different varieties and different price risk identification degrees at a terminal and the information pushing management is carried out when the price of the agricultural products triggers a set threshold value through the self-defined setting of the early warning module;
(4) the real-time mobile platform acquires agricultural product price information stored in the cloud in real time and acquires reminding information pushed by the early warning display platform in any one or more modes of a short message, a mailbox and a WeChat.
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| CN113065051B (en) * | 2021-04-02 | 2022-04-15 | 西南石油大学 | Visual agricultural big data analysis interactive system |
| CN113393277B (en) * | 2021-07-01 | 2023-11-28 | 安徽洲弋电子商务有限公司 | Agricultural product market data analysis system based on big data |
| CN113421125A (en) * | 2021-07-02 | 2021-09-21 | 中农仓农业科技(北京)有限公司 | Agricultural product price monitoring and early warning system based on big data analysis |
| CN114881706A (en) * | 2022-05-30 | 2022-08-09 | 布瑞克(苏州)农业互联网股份有限公司 | Method and system for automatically adjusting agricultural product quotation |
| CN116881526B (en) * | 2023-09-07 | 2023-12-15 | 埃睿迪信息技术（北京）有限公司 | Data processing method, device and equipment |
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| CN109978616A (en) * | 2019-03-22 | 2019-07-05 | 中国农业科学院农业信息研究所 | Agricultural product data monitoring early warning system |
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