CN113421125A - Agricultural product price monitoring and early warning system based on big data analysis - Google Patents
Agricultural product price monitoring and early warning system based on big data analysis Download PDFInfo
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Abstract
The invention relates to an agricultural product price monitoring and early warning system based on big data analysis, which comprises a data acquisition platform, a cloud storage platform, a data analysis platform, a display platform and an early warning prompt platform, wherein the data acquisition platform is connected with the cloud storage platform; the data acquisition platform is used for acquiring the real-time price of agricultural products and data influencing the price factors of the agricultural products, the cloud storage platform is used for storing the data acquired by the data acquisition platform and analyzing, calling and storing the industrial data analysis platform, the display platform is used for displaying the real-time price of the agricultural products and the early warning of relevant influencing factors, and the early warning prompt platform is used for pushing data analysis results to users. The invention has the advantages of intellectualization, high efficiency and precision.
Description
Technical Field
The invention relates to the technical field of intelligent agricultural platforms, in particular to an agricultural product price monitoring and early warning system based on big data analysis.
Background
The agricultural products refer to an industrial form combining natural reproduction and social reproduction, play a crucial role in the development of national economy, and the price and fluctuation of the agricultural products influence the civil life and the economy and play a decisive factor in the development of the civil life and the future crop planting.
The agricultural product price monitoring is developed rapidly at the present stage, visual price display can be provided for markets and related upstream and downstream practitioners, communication and understanding of market conditions of individual personnel are facilitated, but influence factors borne by the agricultural product price are more, the price is expected to be provided through professional expert analysis at the present stage, influence caused by personal subjective factors is inevitable, high precision and standardized standards are difficult to realize, price psychological fall easily appears in the market of the agricultural product, market supply and demand imbalance is caused, and great influence is caused to practitioners and consumers.
Disclosure of Invention
To the not enough of above-mentioned prior art, the technical problem that this patent application will be solved is how to provide one kind and relies on big data analysis, combines multiple price factor, provides real-time show, accurate early warning's agricultural product price monitoring early warning system based on big data analysis.
In order to solve the technical problems, the invention adopts the following technical scheme:
a big data analysis-based agricultural product price monitoring and early warning system comprises a data acquisition platform, a cloud storage platform, a data analysis platform, a display platform and an early warning prompt platform; the data acquisition platform is used for acquiring the real-time price of agricultural products and data influencing the price factors of the agricultural products, the cloud storage platform is used for storing the data acquired by the data acquisition platform and analyzing, calling and storing the industrial data analysis platform, the display platform is used for displaying the real-time price of the agricultural products and the early warning of relevant influencing factors, and the early warning prompt platform is used for pushing data analysis results to users.
As optimization, the data acquisition platform comprises a price acquisition module, a capacity/energy storage acquisition module, a weather data acquisition module, a transportation network acquisition module and a labor cost acquisition module; the price acquisition module comprises a real-time price acquisition submodule and a historical price acquisition submodule; the transportation network acquisition module comprises a transportation price acquisition submodule and a road real-time condition acquisition module.
And as optimization, the data acquisition platform adopts an online/offline acquisition mode, and comprises one or more mixed modes of a web crawler system, an offline data acquisition and entry system, an internet platform interface management system and an information sharing platform entry system to acquire related data information.
As optimization, the data analysis platform processes the agricultural product price early warning model based on data training, and the processing mode of the agricultural product price early warning model comprises the following steps: classifying agricultural products, classifying and refining the agricultural products into products with main bodies as detailed production places, carrying out individual price analysis on a single main body, taking forward quantitative time T taking the latest price collection time point as a base point as a first time period, arranging prices in the time period on the basis of time, taking price data of the current period and arranging the price data, carrying out fitting comparison on the price arrangements of the current period and the current period, calculating the difference value of the prices among the time points, arranging all the difference values on the basis of time, calculating average curvature, maximum curvature and minimum curvature, and marking the price points exceeding the average curvature in the current time period T as deviation points c1 and c2 … cn; comparing the current-period capacity/energy storage information, weather data, transportation network price with road conditions and labor cost, distributing factor influence weight proportion to deviation point positions, taking backward quantitative time T with the latest price acquisition time point as a base point as a second time period, arranging current-period price data, comparing the acquired non-price data with the current time point as a reference, arranging the data in a sequence of different sizes, and fitting the different factors with the price of the current-period second time period according to the weight proportion to obtain the price simulation of the current-period second time period.
And taking price simulation data of a second time period as an optimization, respectively drawing maximum price deviation and minimum price deviation arrangement with the maximum curvature and the minimum curvature by taking the current data as a starting point, dividing the interval to obtain a plurality of early warning intervals, and taking the interval in which the price simulation falls as a push early warning interval.
As optimization, the time period T is any one of 5 days, weeks, 14 days and months, and the selection criterion selects the time period closest to the duration of the target sale period 1/5 based on the current target sale period.
And as optimization, the display platform displays the current-stage data, the current-stage data and the early warning data through visualization and displays the current-stage data, the current-stage data and the early warning data through color distinction.
As optimization, the early warning prompt platform adopts one or more modes of pushing, short messages, WeChat and mailboxes in the system to carry out early warning.
To sum up: compared with the prior art, the scheme can be used for comparing the prices of agricultural products and the cost of the agricultural products through a large amount of collected agricultural products, a price early warning and supervision system integrating data management, big data analysis, visual display and message feedback is established, the early warning precision is high, the subjective intention of an individual is not dominant, an early warning system taking data as guidance is formed, and the accurate, efficient and accurate guidance can be provided for wide practitioners and consumers.
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Fig. 1 is a frame diagram of an agricultural product price monitoring and early warning system based on big data analysis according to the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings. In the description of the present invention, it is to be understood that the orientation or positional relationship indicated by the orientation words such as "upper, lower" and "top, bottom" etc. are usually based on the orientation or positional relationship shown in the drawings, and are only for convenience of description and simplicity of description, and in the case of not making a reverse description, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore, should not be interpreted as limiting the scope of the present invention; the terms "inner and outer" refer to the inner and outer relative to the profile of the respective component itself.
According to fig. 1, an agricultural product price monitoring and early warning system based on big data analysis comprises a data acquisition platform, a cloud storage platform, a data analysis platform, a display platform and an early warning prompt platform; the data acquisition platform is used for acquiring the real-time price of agricultural products and data influencing the price factors of the agricultural products, the cloud storage platform is used for storing the data acquired by the data acquisition platform and analyzing, calling and storing the industrial data analysis platform, the display platform is used for displaying the real-time price of the agricultural products and the early warning of relevant influencing factors, and the early warning prompt platform is used for pushing data analysis results to users.
Preferably, the data acquisition platform comprises a price acquisition module, a capacity/energy storage acquisition module, a weather data acquisition module, a transportation network acquisition module and a labor cost acquisition module; the price acquisition module comprises a real-time price acquisition submodule and a historical price acquisition submodule; the transportation network acquisition module comprises a transportation price acquisition submodule and a road real-time condition acquisition module.
Preferably, the data acquisition platform adopts an online/offline acquisition mode, and comprises one or more mixed modes of a web crawler system, an offline data acquisition and entry system, an internet platform interface management system and an information sharing platform entry system to acquire related data information.
Preferably, the data analysis platform processes the agricultural product price early warning model based on data training, and the processing mode of the agricultural product price early warning model comprises: classifying agricultural products, classifying and refining the agricultural products into products with main bodies as detailed production places, carrying out individual price analysis on a single main body, taking forward quantitative time T taking the latest price collection time point as a base point as a first time period, arranging prices in the time period on the basis of time, taking price data of the current period and arranging the price data, carrying out fitting comparison on the price arrangements of the current period and the current period, calculating the difference value of the prices among the time points, arranging all the difference values on the basis of time, calculating average curvature, maximum curvature and minimum curvature, and marking the price points exceeding the average curvature in the current time period T as deviation points c1 and c2 … cn; comparing the current-period capacity/energy storage information, weather data, transportation network price with road conditions and labor cost, distributing factor influence weight proportion to deviation point positions, taking backward quantitative time T with the latest price acquisition time point as a base point as a second time period, arranging current-period price data, comparing the acquired non-price data with the current time point as a reference, arranging the data in a sequence of different sizes, and fitting the different factors with the price of the current-period second time period according to the weight proportion to obtain the price simulation of the current-period second time period.
Preferably, the price simulation data of the second time period is taken, the current data is taken as a starting point, the maximum price deviation and the minimum price deviation arrangement are respectively drawn with the maximum curvature and the minimum curvature, the interval is divided to obtain a plurality of early warning intervals, and the interval in which the price simulation falls is taken as a push early warning interval.
Preferably, the time period T is any one of 5 days, weeks, 14 days and months, and the selection criterion selects the time period closest to the duration of the target sale period 1/5 based on the current target sale period.
Preferably, the display platform displays the current stage data, the current stage data and the early warning data through visualization, and displays the current stage data, the current stage data and the early warning data through color distinction.
Preferably, the early warning prompt platform adopts one or more modes of pushing, short messages, WeChat and mailboxes in the system to carry out early warning.
To sum up: compared with the prior art, the scheme can be used for comparing the prices of agricultural products and the cost of the agricultural products through a large amount of collected agricultural products, a price early warning and supervision system integrating data management, big data analysis, visual display and message feedback is established, the early warning precision is high, the subjective intention of an individual is not dominant, an early warning system taking data as guidance is formed, and the accurate, efficient and accurate guidance can be provided for wide practitioners and consumers.
Finally, it should be noted that: various modifications and alterations of this invention may be made by those skilled in the art without departing from the spirit and scope of this invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.
Claims (8)
1. An agricultural product price monitoring and early warning system based on big data analysis is characterized by comprising a data acquisition platform, a cloud storage platform, a data analysis platform, a display platform and an early warning prompt platform; the data acquisition platform is used for acquiring the real-time price of agricultural products and data influencing the price factors of the agricultural products, the cloud storage platform is used for storing the data acquired by the data acquisition platform and analyzing, calling and storing the industrial data analysis platform, the display platform is used for displaying the real-time price of the agricultural products and the early warning of relevant influencing factors, and the early warning prompt platform is used for pushing data analysis results to users.
2. The big data analysis-based agricultural product price monitoring and early warning system as claimed in claim 1, wherein the data acquisition platform comprises a price acquisition module, a capacity/energy storage acquisition module, a weather data acquisition module, a transportation network acquisition module and a labor cost acquisition module; the price acquisition module comprises a real-time price acquisition submodule and a historical price acquisition submodule; the transportation network acquisition module comprises a transportation price acquisition submodule and a road real-time condition acquisition module.
3. The agricultural product price monitoring and early warning system based on big data analysis as claimed in claim 2, wherein the data collection platform adopts an online/offline collection mode, including one or more mixed modes of a web crawler system, an offline data collection and entry system, an internet platform interface management system, and an information sharing platform entry system to obtain related data information.
4. The big data analysis-based agricultural product price monitoring and early warning system according to claim 3, wherein the data analysis platform performs processing based on a data-trained agricultural product price early warning model, and the processing manner of the agricultural product price early warning model comprises: classifying agricultural products, classifying and refining the agricultural products into products with main bodies as detailed production places, carrying out individual price analysis on a single main body, taking forward quantitative time T taking the latest price collection time point as a base point as a first time period, arranging prices in the time period on the basis of time, taking price data of the current period and arranging the price data, carrying out fitting comparison on the price arrangements of the current period and the current period, calculating the difference value of the prices among the time points, arranging all the difference values on the basis of time, calculating average curvature, maximum curvature and minimum curvature, and marking the price points exceeding the average curvature in the current time period T as deviation points c1 and c2 … cn; comparing the current-period capacity/energy storage information, weather data, transportation network price with road conditions and labor cost, distributing factor influence weight proportion to deviation point positions, taking backward quantitative time T with the latest price acquisition time point as a base point as a second time period, arranging current-period price data, comparing the acquired non-price data with the current time point as a reference, arranging the data in a sequence of different sizes, and fitting the different factors with the price of the current-period second time period according to the weight proportion to obtain the price simulation of the current-period second time period.
5. The agricultural product price monitoring and early warning system based on big data analysis as claimed in claim 4, characterized in that price simulation data of a second time period is taken, a maximum price deviation and a minimum price deviation arrangement are respectively drawn with a maximum curvature and a minimum curvature by taking the current data as a starting point, the interval is divided to obtain a plurality of early warning intervals, and the interval in which the price simulation falls is taken as a push early warning interval.
6. The agricultural product price monitoring and early warning system based on big data analysis as claimed in claim 5, wherein the time period T is any one of 5 days, weeks, 14 days and months, and the selection criterion is based on the current target sale period, and the time period closest to the target sale period 1/5 is selected.
7. The agricultural product price monitoring and early warning system based on big data analysis as claimed in claim 6, wherein the display platform displays the present stage data, the past stage data and the early warning data through visualization and displays the present stage data, the past stage data and the early warning data through color differentiation.
8. The agricultural product price monitoring and early warning system based on big data analysis as claimed in claim 7, wherein the early warning prompt platform adopts one or more of push in the system, short message, WeChat and mailbox for early warning.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114331090A (en) * | 2021-12-24 | 2022-04-12 | 江苏业派生物科技有限公司 | Agricultural product market supply and demand data monitoring system and method based on big data |
| CN116720881A (en) * | 2023-08-08 | 2023-09-08 | 新立讯科技股份有限公司 | Agricultural product sales supervision early warning method, system and medium based on positioning information |
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