Agricultural product supply and demand hierarchical regulation method applied to Internet cloud platform

Abstract

The present invention relates to the field of agricultural product e-commerce technology, specifically to a hierarchical control method for agricultural product supply and demand applied to an Internet cloud platform, which collects user data of buyers and sellers, obtains their purchase and sales needs, and identifies and classifies buyers and sellers by building an agricultural product transaction cloud platform; creates a personalized transaction matching strategy based on the multi-level scenarios of agricultural product circulation and the multi-dimensional characteristics of buyers and sellers; based on user classification and matching strategies, the cloud platform achieves accurate matching of buyers and sellers, and outputs supply and demand agricultural product data at the same time. The method of the present invention utilizes cloud computing and big data analysis technology to improve the efficiency of agricultural product circulation and provides a new idea for the digital transformation of the agricultural industry.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural product e-commerce, and in particular to a method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform. Background Art

[0002] With the rapid development of Internet technology and the continuous advancement of agricultural modernization, in order to improve the efficiency of agricultural product circulation and promote the upgrading of the agricultural industry, it is urgent to build an agricultural product trading cloud platform based on cloud computing and big data technology.

[0003] At present, the main problems in agricultural product transactions are as follows: First, there is information asymmetry, and it is difficult to effectively match agricultural product supply and demand information; second, the transaction chain is long, with many intermediate links, resulting in high transaction costs; third, the quality and safety of agricultural products is difficult to guarantee, and the traceability system is imperfect; fourth, the transaction model is single, and there is a lack of personalized transaction matchmaking and matching services.

[0004] The invention patent with the publication number CN116911963A discloses a data-driven agricultural and special by-product transaction management method and cloud platform, which involves the field of agricultural product transaction technology. First, the transaction management data of agricultural and special by-products is obtained, and the transaction management data of agricultural and special by-products is preprocessed. Secondly, based on the preprocessed transaction management data of agricultural and special by-products, a big data recommendation strategy for agricultural and special by-products is formulated to recommend suitable agricultural and special by-products to agricultural and special by-product buyers. Finally, based on the results of agricultural and special by-product transaction management, feedback analysis of agricultural and special by-product transaction data is conducted, and agricultural and special by-product transaction management is adjusted and optimized to improve the efficiency of agricultural and special by-product transactions. However, the invention does not carry out multi-level classification and division for agricultural product circulation scenarios, and lacks consideration of supply and demand matching strategies for multiple types of agricultural product buyers and sellers.

[0005] In view of this, the present invention proposes a method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform. Summary of the invention

[0006] The purpose of the present invention is to provide a method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform, and to design a marketing matching strategy based on the characteristics of users with different roles in the agricultural product trading cloud platform to improve the accuracy and practicality of marketing recommendations and the circulation efficiency of agricultural products.

[0007] To achieve the above object, the present invention provides a method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform, comprising:

[0008] Build an agricultural product trading cloud platform to store agricultural product information and user information, collect user data in the agricultural product trading cloud platform, and obtain the purchasing needs of buyer users and the sales needs of seller users; based on the buying and selling needs of users in the agricultural product trading cloud platform, identify and classify buyer users according to downstream retailers, midstream wholesalers and terminal individual consumers; identify and classify seller users according to upstream growers, midstream agricultural product wholesalers and downstream agricultural product retailers; build multi-level agricultural product circulation scenarios, and based on the multi-dimensional feature data of various types of buyers and sellers, create buyer and seller user transaction matching strategies based on the agricultural product trading needs of buyers and sellers in each circulation scenario; according to the identified and classified buyer and seller user categories and the corresponding buyer and seller user transaction matching strategies, the agricultural product trading cloud platform matches buyer and seller users, and outputs supply and demand agricultural product data for both buyers and sellers.

[0009] Preferably, the agricultural product information includes seasonal agricultural product types, seasonal agricultural product production seasons and seasonal agricultural product preservation and storage time; the user data includes user personal information and transaction records; the personal information includes user geographic location information; the transaction records include agricultural product transaction time, transaction type, transaction number, transaction amount and transaction volume.

[0010] Preferably, the buyer user type is classified according to the purchase demand of agricultural products created by the buyer user on the agricultural product trading cloud platform, the purchase demand includes the type and quantity of agricultural products, and the time when the buyer user creates the purchase demand is recorded; the purchase demand data {t, n'} of the buyer user is generated; wherein t is the time when the purchase demand is created, and n' is the quantity of agricultural products required;

[0011] On the agricultural product trading cloud platform, the buyer's purchase demand data {t,n'} is compared with the historical transaction cycle data, and the buyer's user type is determined based on the comparison results.

[0012] Preferably, the historical transaction cycle data is: },{N}}; }={ }, { } is the increasing sequence of agricultural product transaction time, to The time point at which the buyer creates a purchase demand for the target agricultural product and completes the transaction, dividing the time separation point in the time series and , , when the buyer creates a purchase demand at time t to During the time period, the buyer's purchase demand is regarded as wholesale demand; when the buyer creates a purchase demand at time t to During the time period, the buyer's purchase demand is regarded as retail demand; when the buyer creates the purchase demand at a time t later than At this point in time, the buyer's purchasing needs are regarded as personal consumption needs;

[0013] {N}={ , ,..., }, {N} is the descending sequence of agricultural product trading volume, to The quantity of agricultural product purchase demand created by the buyer at one time and the completed transaction; the quantity separation point in the transaction volume sequence and , ; The single transaction volume is The purchase demand between The purchase demand between The purchasing demand between them is regarded as personal consumption demand;

[0014] When the purchase demands created by buyer users all meet the wholesale demand, the buyer users are divided into midstream wholesalers, and the grower-wholesaler matching strategy based on the matching degree of supply and demand is adopted;

[0015] When the purchase demands created by buyer users all meet the retail demands, the buyer users are divided into downstream retailers, and the wholesaler-retailer matching strategy based on profit maximization is adopted;

[0016] When the purchase demands created by buyer users all meet personal consumption needs, buyer users are classified as terminal individual consumers, and a retailer-consumer matching strategy based on user portraits is adopted;

[0017] When the user types judged based on {t, n'} are inconsistent, the required quantity of agricultural products n' is used as the judgment criterion, and the buyer user types are divided from high to low according to the priority of wholesalers, retailers and consumers.

[0018] Preferably, when it is determined that the buyer user is a midstream wholesaler, a grower-wholesaler matching strategy based on supply and demand matching is triggered; the grower-wholesaler matching strategy based on supply and demand matching includes, based on the wholesaler creating the purchase demand for agricultural products, building a matching model between midstream wholesalers and upstream growers:

[0019]

[0020] in, Indicates the matching degree between midstream wholesalers and upstream growers, A grower types of agricultural products, A grower Agricultural product ratings, A grower The supply of A grower The selling price range, A grower The geographic location coordinates of Is a wholesaler types of agricultural products, Is a wholesaler Intended price range, Is a wholesaler The demand, Is a wholesaler The geographic location coordinates of Is a wholesaler The maximum acceptable transportation distance; Is a wholesaler Minimum quality requirements; is the type matching coefficient, when When is 1, When is 0; and A grower The lower and upper limits of the selling price range; and Is a wholesaler The lower and upper limits of the intended price range; is an indicator function used to determine the grower Does the agricultural product rating meet the wholesaler's Minimum quality requirements; A grower and wholesalers The transportation distance between is the matching adjustment factor.

[0021] Preferably, an optimization model of the matching model between midstream wholesalers and upstream growers is constructed, an objective function is set up, and a maximum total matching degree is constructed:

[0022] ;

[0023] in, is the number of matched growers, is the number of matched wholesalers; for wholesalers, the supply of matched growers is greater than the demand: ; For growers, the demand from the matched wholesalers is greater than the supply: ;

[0024] Wholesalers and growers make multiple matches with each other. If a grower is recommended to wholesaler j, then ,otherwise ; ; The supply between growers and wholesalers is a non-negative integer: ;

[0025] in, is a binary variable. When a grower is recommended to a wholesaler 1 when it is, otherwise 0; Growers are recommended to wholesalers supply.

[0026] Preferably, when it is determined that the buyer user is a downstream retailer, a wholesaler-retailer matching strategy based on profit maximization is triggered; the wholesaler-retailer matching strategy based on profit maximization includes recommending agricultural product types and midstream wholesalers to downstream retailers based on the profit expectations of agricultural products;

[0027] Build downstream retailers to purchase agricultural products from midstream wholesalers Expected profit model:

[0028]

[0029] in, Is a retailer The target profit margin, Is a retailer Type of agricultural product you are interested in, Is a retailer The geographic location coordinates of Is a wholesaler The wholesale prices of agricultural products provided, Is a wholesaler the supply of agricultural products provided; Wholesaler The geographic location coordinates of is the market demand for agricultural products, is the average retail price of agricultural product k; is the price profit margin indicator function, when the wholesale price Less than retail price Multiply by profit margin threshold 1 when it is, otherwise 0; is the agricultural product type matching indicator function. Belong to retailers It is 1 when the species is of interest, otherwise it is 0; e is a natural constant; Is a retailer The distance between wholesalers and is the distance impact parameter, which controls the degree of influence of distance on expected profit;

[0030] Match agricultural products to retailers and corresponding wholesalers based on the retailers' profit expectations.

[0031] Preferably, when the buyer user is determined to be an individual terminal consumer, a retailer-consumer matching strategy based on user portrait is triggered to match agricultural products and downstream retailers for the individual terminal consumer, and seasonal agricultural products sold by retailers are recommended to the individual consumer;

[0032] The recent personal information and purchase records of individual consumers are obtained from the agricultural product trading cloud platform, and different dietary patterns are divided according to the age and gender of individual consumers, and corresponding agricultural product combinations are recommended according to different patterns.

[0033] An intelligent recommendation system for marketing content for agricultural product sales and circulation scenarios, which is implemented based on the agricultural product supply and demand hierarchical regulation method applied to the Internet cloud platform, and includes: a data collection module, a user classification module, a circulation scenario classification module, a strategy recommendation module, and a marketing recommendation module;

[0034] The data collection module is used to build an agricultural product trading cloud platform, store agricultural product information and user information, collect user data in the agricultural product trading cloud platform, and obtain the purchase demand of buyer users and the sales demand of seller users;

[0035] The user classification module, based on the buying and selling needs of users in the agricultural product trading cloud platform, classifies buyer users into downstream retailers, midstream wholesalers and terminal individual consumers; and classifies seller users into upstream growers, midstream agricultural product wholesalers and downstream agricultural product retailers;

[0036] The circulation scenario classification module is used to construct multi-level agricultural product circulation scenarios, including agricultural product circulation scenarios from upstream growers to midstream wholesalers, from midstream wholesalers to downstream retailers, and from downstream retailers to end consumers;

[0037] The strategy recommendation module creates a transaction matching strategy for each buyer and seller in each circulation scenario based on the multi-dimensional feature data of various buyer and seller users. The transaction matching strategy includes a grower-wholesaler matching strategy based on supply-demand matching, a wholesaler-retailer matching strategy based on profit maximization, and a retailer-consumer matching strategy based on user portraits. According to the categories of the buyer and seller users, the corresponding matching strategy is matched to recommend matching seller transaction objects to the buyer user, and the types and quantities of marketable agricultural products are recommended;

[0038] According to the categories of buyer and seller users, the corresponding matching strategy is matched to recommend matching seller transaction objects to the buyer users, and the types and quantities of marketable agricultural products are also recommended.

[0039] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; the processor executes the agricultural product supply and demand hierarchical regulation method applied to an Internet cloud platform by calling the computer program stored in the memory.

[0040] A storage medium stores instructions, which, when executed on a computer, enable the computer to execute the agricultural product supply and demand grading control method applied to an Internet cloud platform.

[0041] Beneficial effects of the present invention: The method provided by the present invention can accurately match the supply and demand sides and realize the efficient circulation of agricultural products. By collecting user data of the agricultural product trading cloud platform, the needs of buyers and sellers are obtained, and user classification and circulation scenario division are performed based on multi-dimensional characteristics. A matching strategy is designed for each scenario, which can accurately match the supply and demand sides of agricultural products, shorten the transaction chain, and reduce circulation costs.

[0042] The present invention also optimizes the recommendation of agricultural product combinations and improves the user's purchasing experience. Based on the user portrait of the end consumer, the dietary preferences and consumption habits of the end consumer are analyzed, and suitable agricultural product combinations and retailers are recommended in a targeted manner. Intelligent recommendations are also made based on the seasonal characteristics of agricultural products, which can effectively guide consumption and improve user purchase satisfaction and platform stickiness.

[0043] The method provided by the present invention can improve the sales efficiency of agricultural products, help upgrade the agricultural industry, achieve accurate matching of supply and demand of agricultural products through intelligent algorithms, optimize product recommendations, significantly improve the sales efficiency and sales of agricultural products, accelerate the turnover of agricultural product inventory, reduce losses and waste, and empower the digital and intelligent upgrade of the agricultural industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the flow chart of the agricultural product supply and demand classification control method applied to the Internet cloud platform of the present invention;

[0045] Figure 2 This is a schematic diagram of the structure of the agricultural product supply and demand classification control system applied to the Internet cloud platform of the present invention;

[0046] Figure 3 It is a schematic diagram of the structure of an electronic device provided by the present invention;

[0047] Figure 4 It is a schematic diagram of the storage medium structure provided by the present invention. DETAILED DESCRIPTION

[0048] In order to better understand the present invention, a more detailed description will be made of various aspects of the present invention with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0049] In the accompanying drawings, the size, dimensions and shapes of the elements have been slightly adjusted for ease of illustration. The accompanying drawings are for illustration only and are not strictly drawn to scale. As used herein, the terms "substantially", "approximately" and similar terms are used as terms of approximation, not as terms of degree, and are intended to illustrate the inherent deviations in measurements or calculations that will be recognized by those of ordinary skill in the art. In addition, in the present invention, the order in which the steps are described does not necessarily represent the order in which these processes occur in actual operation, unless otherwise specified or can be derived from the context.

[0050] It should also be understood that expressions such as "comprises", "including", "having", "includes" and / or "comprising" are open rather than closed expressions in this specification, which indicate the presence of the stated features, elements and / or components, but do not exclude the presence of one or more other features, elements, components and / or combinations thereof. In addition, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features rather than just the individual elements in the list. In addition, when describing embodiments of the present invention, "may" is used to mean "one or more embodiments of the present invention". And, the term "exemplary" is intended to refer to an example or illustration.

[0051] Unless otherwise defined, all terms (including engineering terms and scientific and technological terms) used in this document have the same meaning as commonly understood by ordinary technicians in the field to which the present invention belongs. It should also be understood that unless otherwise clearly stated in the present invention, words defined in commonly used dictionaries should be interpreted as having the same meaning as their meaning in the context of the relevant technology, and should not be interpreted in an idealized or overly formal sense.

[0052] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0053] Example 1

[0054] Reference Figure 1 The first embodiment of the present invention is specifically a method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform.

[0055] Build an agricultural product trading cloud platform to store agricultural product information and user information, collect user data in the agricultural product trading cloud platform, and obtain the purchasing needs of buyer users and the sales needs of seller users.

[0056] The agricultural product information includes seasonal agricultural product types, seasonal agricultural product production seasons, and seasonal agricultural product preservation and storage time; the user data includes user personal information and transaction records; the personal information includes user geographic location information; the transaction records include agricultural product transaction time, transaction type, transaction number, transaction amount, and transaction volume.

[0057] Based on the buying and selling needs of users in the agricultural products trading cloud platform, buyer users are identified and classified according to downstream retailers, midstream wholesalers and end-user consumers; seller users are identified and classified according to upstream growers, midstream agricultural products wholesalers and downstream agricultural products retailers.

[0058] Among the buyer users, the role of the midstream wholesaler is to purchase agricultural products from upstream growers or other wholesalers, and then sell them to downstream retailers or end consumers; the role of the downstream retailer is to purchase agricultural products from the midstream wholesaler, and then sell them to end consumers. Among the seller users, the role of the upstream growers is to sell agricultural products to the midstream wholesalers; the role of the midstream wholesalers is to purchase agricultural products from upstream growers or other wholesalers, and then sell them to downstream retailers or end consumers; the role of the downstream retailers is to purchase agricultural products from the midstream wholesalers, and then sell them to end consumers; the midstream wholesalers and downstream retailers purchase and sell agricultural products as both buyer users and seller users.

[0059] According to the purchase demand of agricultural products created by buyer users on the agricultural products trading cloud platform, the buyer user types are classified, the purchase demand includes the type and quantity of agricultural products, and the time when the buyer user creates the purchase demand is recorded; the purchase demand data {t,n'} of the buyer user is generated; wherein t is the time when the purchase demand is created, and n' is the quantity of agricultural products required.

[0060] On the agricultural product trading cloud platform, the buyer's purchase demand data {t,n'} is compared with the historical transaction cycle data, and the buyer's user type is determined based on the comparison results.

[0061] The historical transaction cycle data is: },{N}}; }={ }, { } is the increasing sequence of agricultural product transaction time, to The time point at which the buyer creates a purchase demand for the target agricultural product and completes the transaction, dividing the time separation point in the time series and , , when the buyer creates a purchase demand at time t to During the time period, the buyer's purchase demand is regarded as wholesale demand; when the buyer creates a purchase demand at time t to During the time period, the buyer's purchase demand is regarded as retail demand; when the buyer creates the purchase demand at a time t later than At this point in time, the buyer's purchasing needs are regarded as personal consumption needs.

[0062] {N}={ , ,..., }, {N} is the descending sequence of agricultural product trading volume, to The quantity of agricultural product purchase demand created by the buyer at one time and the completed transaction; the quantity separation point in the transaction volume sequence and , ; The single transaction volume is The purchase demand is regarded as wholesale demand, and the single transaction volume is The purchasing demand is regarded as retail demand, and the single transaction volume is The purchasing demand is regarded as personal consumption demand.

[0063] When the purchase demands created by buyer users all meet the wholesale demand, the buyer users are divided into midstream wholesalers, and the grower-wholesaler matching strategy based on the matching degree of supply and demand is adopted;

[0064] When the purchase demands created by buyer users all meet the retail demands, the buyer users are divided into downstream retailers, and the wholesaler-retailer matching strategy based on profit maximization is adopted;

[0065] When the purchase demands created by buyer users all meet personal consumption needs, buyer users are classified as terminal individual consumers, and a retailer-consumer matching strategy based on user portraits is adopted;

[0066] When the user types judged based on {t, n'} are inconsistent, the required quantity of agricultural products n' is used as the judgment criterion, and the buyer user types are divided from high to low according to the priority of wholesalers, retailers and consumers.

[0067] Construct multi-level agricultural product circulation scenarios, and based on the multi-dimensional characteristic data of various types of buyers and sellers, create buyer and seller transaction matching strategies based on the agricultural product trading needs of buyers and sellers in each circulation scenario.

[0068] Based on the multi-dimensional feature data of various types of buyers and sellers, a transaction matching strategy is created for buyers and sellers in each circulation scenario. The transaction matching strategies include a grower-wholesaler matching strategy based on supply and demand matching, a wholesaler-retailer matching strategy based on profit maximization, and a retailer-consumer matching strategy based on user portraits.

[0069] Based on the identified and classified buyer and seller user categories and the corresponding buyer and seller transaction matching strategies, the agricultural product trading cloud platform matches the buyer and seller users and outputs the supply and demand agricultural product data to both parties.

[0070] When the buyer user is determined to be a midstream wholesaler, a grower-wholesaler matching strategy based on supply and demand matching is triggered; the grower-wholesaler matching strategy based on supply and demand matching includes building a matching model between midstream wholesalers and upstream growers based on the purchase demand for agricultural products created by wholesalers:

[0071]

[0072] in, Indicates the matching degree between midstream wholesalers and upstream growers, A grower types of agricultural products, A grower Agricultural product ratings, A grower The supply of A grower The selling price range, A grower The geographic location coordinates of Is a wholesaler types of agricultural products, Is a wholesaler Intended price range, Is a wholesaler The demand, Is a wholesaler The geographic location coordinates of It's a wholesaler The maximum acceptable transportation distance; Is a wholesaler Minimum quality requirements; is the type matching coefficient, when When is 1, When is 0; and A grower The lower and upper limits of the selling price range; and Is a wholesaler The lower and upper limits of the intended price range; is an indicator function used to determine the grower Does the agricultural product rating meet the wholesaler's Minimum quality requirements; A grower and wholesalers The transportation distance between is the matching adjustment coefficient, which is determined by those skilled in the art through a large number of experiments.

[0073] Construct an optimization model for the matching model between midstream wholesalers and upstream growers, set up an objective function, and construct a model to maximize the total matching degree:

[0074] ;

[0075] in, is the number of matched growers, is the number of matched wholesalers; for wholesalers, the supply of matched growers is greater than the demand: ; For growers, the demand from the matched wholesalers is greater than the supply: .

[0076] Wholesalers and growers can have multiple matches with each other. If a grower is recommended to wholesaler j, then ,otherwise ; ; The supply between growers and wholesalers is a non-negative integer: .

[0077] in, is a binary variable. When a grower is recommended to a wholesaler 1 when it is, otherwise 0; Growers are recommended to wholesalers supply.

[0078] When it is determined that the buyer user is a downstream retailer, a wholesaler-retailer matching strategy based on profit maximization is triggered; the wholesaler-retailer matching strategy based on profit maximization includes recommending agricultural product types and midstream wholesalers to downstream retailers based on the profit expectations of agricultural products.

[0079] Build downstream retailers to purchase agricultural products from midstream wholesalers Expected profit model:

[0080]

[0081] in, Is a retailer The target profit margin, Is a retailer Type of agricultural product you are interested in, Is a retailer The geographic location coordinates of Is a wholesaler The wholesale prices of agricultural products provided, Is a wholesaler the supply of agricultural products provided; Wholesaler The geographic location coordinates of is the market demand for agricultural products, is the average retail price of agricultural product k; is the price profit margin indicator function, when the wholesale price Less than retail price Multiply by profit margin threshold 1 when it is, otherwise 0; is the agricultural product type matching indicator function. Belong to retailers It is 1 when the species is of interest, otherwise it is 0; e is a natural constant; Is a retailer The distance between wholesalers and is the distance influence parameter, which controls the influence of distance on expected profit.

[0082] Match agricultural products to retailers and corresponding wholesalers based on the retailers' profit expectations.

[0083] When the buyer is determined to be an end-user individual consumer, the retailer-consumer matching strategy based on user portrait is triggered to match agricultural products and downstream retailers for the end-user individual consumer, and at the same time recommend seasonal agricultural products sold by retailers to the individual consumer.

[0084] Extract individual consumers’ registration information, including age, gender, and delivery address, from the user database of the agricultural product trading cloud platform; obtain individual consumers’ agricultural product purchase records within the past month, including purchase time, purchase category, purchase quantity, purchase frequency, post-purchase evaluation, etc.

[0085] Algorithms such as collaborative filtering and association rule mining are used to analyze individual consumers’ preferences for agricultural products and form a multi-dimensional user preference portrait.

[0086] Based on the geographic location information of individual consumers, we match them with high-quality agricultural product retailers in their vicinity to form a set of candidate retailers; we conduct a comprehensive evaluation of the candidate retailers’ agricultural product categories, inventory, sales volume, prices, promotional efforts, etc., and select retailers that are most relevant to consumer preferences; based on the matching degree between the retailers’ agricultural product sales data and the preferences of individual consumers, we recommend highly matched agricultural products to individual consumers.

[0087] At the same time, based on the agricultural product listing time and the retailer's promotional calendar of the agricultural product trading cloud platform, seasonal agricultural products sold by retailers are recommended to individual consumers.

[0088] Extract the origin information and market launch time patterns of different agricultural products from the agricultural product database of the agricultural product trading cloud platform; obtain the seasonal agricultural product promotion plans of platform retailers, including promotion time, promotion category and promotion intensity, etc.; match the consumption time series of individual consumers with the seasonal characteristics of agricultural products to identify their potential demand for seasonal agricultural products; recommend fresh agricultural products with significant promotional discounts to individual consumers during the seasonal market period of agricultural products; the recommended content includes graphic information of agricultural products, location navigation of retailers, reminders of preferential promotion activities, etc.

[0089] During the offline stage, individual consumers are divided into user portraits and dietary patterns, and agricultural product combinations of different patterns are matched based on user tags; the latest purchasing behavior of individual consumers is obtained in real time, and user portraits and recommended agricultural product combinations are updated; during the seasonal listing and promotion period of agricultural products, precise push notifications are made to individual consumers in combination with the marketing rhythm of retailers; recommendation feedback data from individual consumers is collected, the recommendation model is optimized, and a closed-loop learning mechanism is formed; and differentiated recommendation frequencies and recommendation channels are set for different dietary patterns to adapt to user purchasing needs.

[0090] Example 2

[0091] Reference Figure 2 , which is the second embodiment of the present invention, provides a hierarchical control system for supply and demand of agricultural products applied to an Internet cloud platform.

[0092] The system includes a data collection module, a user identification and classification module, a circulation scene classification module, and an agricultural product supply and demand transaction module.

[0093] The data collection module, based on the constructed agricultural product trading cloud platform, stores agricultural product information and user information, collects user data in the agricultural product trading cloud platform, and obtains the purchasing needs of buyer users and the selling needs of seller users.

[0094] The user identification and classification module identifies and classifies buyer users according to downstream retailers, midstream wholesalers and terminal individual consumers based on the buying and selling needs of users in the agricultural products trading cloud platform; and identifies and classifies seller users according to upstream growers, midstream agricultural products wholesalers and downstream agricultural products retailers.

[0095] The circulation scenario classification module is used to construct multi-level agricultural product circulation scenarios, and based on the multi-dimensional feature data of various types of buyers and sellers, create a buyer and seller transaction matching strategy based on the agricultural product transaction needs of buyers and sellers in each circulation scenario.

[0096] The agricultural product supply and demand transaction module matches the buyer and seller users according to the identified and classified buyer and seller user categories and the corresponding buyer and seller user transaction matching strategies, and outputs the supply and demand agricultural product data to the buyers and sellers.

[0097] Example 3

[0098] Figure 3 FIG. 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, according to another aspect of the present invention, an electronic device 500 is also provided. The electronic device 500 may include one or more processors and one or more memories. The memories store computer readable codes, and when the computer readable codes are executed by one or more processors, the agricultural product supply and demand hierarchical control method applied to the Internet cloud platform as described above can be executed.

[0099] The method or system according to the embodiment of the present invention can also be used by Figure 3 The architecture of the electronic device shown is implemented.

[0100] like Figure 3 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a ROM 503, a RAM 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, and the like.

[0101] The storage device in the electronic device 500, such as ROM 503 or hard disk 507, can store the agricultural product supply and demand hierarchical control method applied to the Internet cloud platform provided by the present invention.

[0102] The method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform includes: building an agricultural product trading cloud platform, storing agricultural product information and user information, collecting user data in the agricultural product trading cloud platform, and obtaining the purchasing demand of buyer users and the sales demand of seller users; based on the buying and selling demands of users in the agricultural product trading cloud platform, identifying and classifying buyer users according to downstream retailers, midstream wholesalers and terminal individual consumers; identifying and classifying seller users according to upstream growers, midstream agricultural product wholesalers and downstream agricultural product retailers; building multi-level agricultural product circulation scenarios, and based on the multi-dimensional feature data of various types of buyers and sellers, creating buyer and seller user transaction matching strategies based on the agricultural product transaction demands of buyers and sellers in each circulation scenario; according to the identified and classified buyer and seller user categories and the corresponding buyer and seller user transaction matching strategies, the agricultural product trading cloud platform matches the buyer and seller users, and outputs agricultural product data of supply and demand for the buyers and sellers at the same time.

[0103] Furthermore, the electronic device 500 may also include a user interface 508. Figure 3 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 3 One or more components of an electronic device are shown.

[0104] Example 4

[0105] Figure 4 It is a schematic diagram of the storage medium structure provided by an embodiment of the present invention.

[0106] like Figure 4 As shown is a storage medium 600 according to one embodiment of the present invention.

[0107] The storage medium 600 has computer-readable instructions stored thereon.

[0108] When the computer-readable instructions are executed by the processor, the agricultural product supply and demand hierarchical control method applied to the Internet cloud platform according to the embodiment of the present invention described with reference to the above drawings can be executed.

[0109] The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. In addition, according to an embodiment of the present invention, the process described above with reference to the flowchart may be implemented as a computer software program.

[0110] For example, the present invention provides a non-temporary machine-readable storage medium, which stores machine-readable instructions, and the machine-readable instructions can be run by a processor to execute instructions corresponding to the method steps provided by the present invention, for example: building an agricultural product trading cloud platform, storing agricultural product information and user information, collecting user data in the agricultural product trading cloud platform, and obtaining the purchasing needs of buyer users and the sales needs of seller users; based on the buying and selling needs of users in the agricultural product trading cloud platform, identifying and classifying buyer users according to downstream retailers, midstream wholesalers and terminal individual consumers; identifying and classifying seller users according to upstream growers, midstream agricultural product wholesalers and downstream agricultural product retailers; building multi-level agricultural product circulation scenarios, and based on the multi-dimensional feature data of various types of buying and selling users, creating buying and selling user transaction matching strategies based on the agricultural product trading needs of buying and selling users in each circulation scenario; according to the identified and classified buyer and seller user categories and the corresponding buying and selling user transaction matching strategies, the agricultural product trading cloud platform matches the buyer and seller users, and outputs supply and demand agricultural product data for the buyers and sellers at the same time.

[0111] When the computer program is executed by the central processing unit (CPU), the above functions defined in the method of the present invention are performed. The method, apparatus, and device of the present invention may be implemented in many ways. For example, the method, apparatus, and device of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware.

[0112] The above sequence for the steps of the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless otherwise specifically stated.

[0113] In addition, in some embodiments, the present invention can also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Therefore, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0114] In addition, the parts of the above technical solutions provided in the embodiments of the present invention that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail to avoid excessive redundancy.

[0115] The specific implementation modes as described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation mode of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A hierarchical control method for agricultural product supply and demand applied to an Internet cloud platform, characterized in that: include: Build an agricultural product trading cloud platform to store agricultural product information and user information, collect user data in the agricultural product trading cloud platform, and obtain the purchasing needs of buyer users and the sales needs of seller users; Based on the buying and selling needs of users in the agricultural product trading cloud platform, buyer users are identified and classified according to downstream retailers, midstream wholesalers and terminal individual consumers; seller users are identified and classified according to upstream growers, midstream agricultural product wholesalers and downstream agricultural product retailers; Construct multi-level agricultural product circulation scenarios, and create a transaction matching strategy for buyers and sellers based on the multi-dimensional feature data of various buyers and sellers and the agricultural product transaction needs of buyers and sellers in each circulation scenario; According to the identified buyer and seller user categories and the corresponding buyer and seller transaction matching strategies, the agricultural product trading cloud platform matches the buyer and seller users and outputs the supply and demand agricultural product data for both parties. According to the purchase demand of agricultural products created by the buyer user on the agricultural product trading cloud platform, the buyer user type is classified, the purchase demand includes the type and quantity of agricultural products, and the time when the buyer user creates the purchase demand is recorded; the purchase demand data {t, n'} of the buyer user is generated; where t is the time when the purchase demand is created, and n' is the quantity of agricultural products required; On the agricultural product trading cloud platform, the buyer's purchasing demand data {t,n'} is compared with the historical trading cycle data, and the buyer's user type is determined based on the comparison results; The historical transaction cycle data is: },{N}}; }={ }, { } is the increasing sequence of agricultural product transaction time, to The time point at which the buyer creates a purchase demand for the target agricultural product and completes the transaction, dividing the time separation point in the time series and , , when the buyer creates a purchase demand at time t to During the time period, the buyer's purchase demand is regarded as wholesale demand; when the buyer creates a purchase demand at time t to During the time period, the buyer's purchase demand is regarded as retail demand; when the buyer creates the purchase demand at a time t later than At this point in time, the buyer's purchasing needs are regarded as personal consumption needs; { N}={ , ,..., }, {N} is the descending sequence of agricultural product trading volume, to The quantity of agricultural product purchase demand created by the buyer at one time and the completed transaction; the quantity separation point in the transaction volume sequence and , ; The single transaction volume is ) is regarded as wholesale demand, and the single transaction volume is The purchasing demand is regarded as retail demand, and the single transaction volume is The purchasing demand between them is regarded as personal consumption demand; When the purchase demands created by buyer users all meet the wholesale demand, the buyer users are divided into midstream wholesalers, and the grower-wholesaler matching strategy based on the matching degree of supply and demand is adopted; When the purchase demands created by buyer users all meet the retail demands, the buyer users are divided into downstream retailers, and the wholesaler-retailer matching strategy based on profit maximization is adopted; When the purchase demands created by buyer users all meet personal consumption needs, buyer users are classified as terminal individual consumers, and a retailer-consumer matching strategy based on user portraits is adopted; When the user types determined by {t, n'} are inconsistent, the quantity of agricultural products required n' is used as the judgment standard to divide the buyer user types from high to low according to the priority of wholesalers, retailers and consumers; When the buyer is determined to be a midstream wholesaler, the grower-wholesaler matching strategy based on supply-demand matching is triggered; The grower-wholesaler matching strategy based on supply-demand matching includes building a matching model between midstream wholesalers and upstream growers based on the purchase demand of agricultural products created by wholesalers: ； in, Indicates the matching degree between midstream wholesalers and upstream growers, A grower types of agricultural products, A grower Agricultural product ratings, A grower The supply of A grower The selling price range, A grower The geographic location coordinates of Is a wholesaler types of agricultural products, Is a wholesaler Intended price range, Is a wholesaler The demand, Is a wholesaler The geographic location coordinates of Is a wholesaler The maximum acceptable transportation distance; Is a wholesaler Minimum quality requirements; is the type matching coefficient, when When is 1, When is 0; and A grower The lower and upper limits of the selling price range; and Is a wholesaler The lower and upper limits of the intended price range; is an indicator function used to determine the grower Does the agricultural product rating meet the wholesaler's Minimum quality requirements; A grower and wholesalers The transportation distance between is the matching adjustment factor; Construct an optimization model for the matching model between midstream wholesalers and upstream growers, set up an objective function, and maximize the total matching degree: ； in, is the number of matched growers, is the number of matched wholesalers; for wholesalers, the supply of matched growers is greater than the demand: ; For growers, the demand from the matched wholesalers is greater than the supply: ; Wholesalers and growers make multiple matches with each other. If a grower is recommended to wholesaler j, then ,otherwise ; ; The supply between growers and wholesalers is a non-negative integer: ; in, is a binary variable. When a grower is recommended to a wholesaler 1 when it is, otherwise 0; Growers are recommended to wholesalers supply.

2. The agricultural product supply and demand hierarchical control method applied to the Internet cloud platform according to claim 1 is characterized in that: The agricultural product information includes seasonal agricultural product types, seasonal agricultural product production seasons, and seasonal agricultural product preservation and storage time; the user data includes user personal information and transaction records; the personal information includes user geographic location information; the transaction records include agricultural product transaction time, transaction type, transaction number, transaction amount, and transaction volume.

3. The agricultural product supply and demand hierarchical control method applied to the Internet cloud platform according to claim 2 is characterized in that: When the buyer user is determined to be a downstream retailer, the wholesaler-retailer matching strategy based on profit maximization is triggered; The profit maximization-based wholesaler-retailer matching strategy includes, based on the expected profit of agricultural products, recommending agricultural product types and midstream wholesalers to downstream retailers; Build downstream retailers to purchase agricultural products from midstream wholesalers Expected profit model: ； in, Is a retailer The target profit margin, Is a retailer Type of agricultural product you are interested in, Is a retailer The geographic location coordinates of Is a wholesaler The wholesale prices of agricultural products provided, Is a wholesaler the supply of agricultural products provided; Wholesaler The geographic location coordinates of is the market demand for agricultural products, is the average retail price of agricultural product k; is the price profit margin indicator function, when the wholesale price Less than retail price Multiply by profit margin threshold 1 when it is, otherwise 0; is the agricultural product type matching indicator function. Belong to retailers It is 1 when the species is of interest, otherwise it is 0; e is a natural constant; Is a retailer The distance between wholesalers and is the distance impact parameter, which controls the degree of influence of distance on expected profit; Match agricultural products to retailers and corresponding wholesalers based on the retailers' profit expectations.

4. The agricultural product supply and demand hierarchical control method applied to the Internet cloud platform according to claim 3 is characterized in that: When the buyer is determined to be an individual consumer, the retailer-consumer matching strategy based on the user portrait is triggered to match agricultural products and downstream retailers for the individual consumer, and at the same time recommend seasonal agricultural products sold by retailers to the individual consumer; The recent personal information and purchase records of individual consumers are obtained from the agricultural product trading cloud platform, and different dietary patterns are divided according to the age and gender of individual consumers, and corresponding agricultural product combinations are recommended according to different patterns.

5. A system for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform, used to implement a method for hierarchical regulation of agricultural product supply and demand applied to an Internet cloud platform as described in any one of claims 1 to 4, characterized in that: include: Data collection module, user identification and classification module, circulation scenario classification module, agricultural product supply and demand transaction module; The data collection module stores agricultural product information and user information based on the constructed agricultural product trading cloud platform, collects user data in the agricultural product trading cloud platform, and obtains the purchasing needs of buyer users and the selling needs of seller users; The user identification and classification module identifies and classifies buyer users according to downstream retailers, midstream wholesalers and terminal individual consumers based on the buying and selling needs of users in the agricultural product trading cloud platform; and identifies and classifies seller users according to upstream growers, midstream agricultural product wholesalers and downstream agricultural product retailers; The circulation scenario classification module is used to construct multi-level agricultural product circulation scenarios, and based on the multi-dimensional feature data of various types of buyers and sellers, create a buyer and seller transaction matching strategy based on the agricultural product transaction needs of buyers and sellers in each circulation scenario; The agricultural product supply and demand transaction module matches the buyer and seller users according to the identified and classified buyer and seller user categories and the corresponding buyer and seller user transaction matching strategies, and outputs the supply and demand agricultural product data to the buyers and sellers.

6. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; the processor executes the agricultural product supply and demand hierarchical regulation method applied to the Internet cloud platform as described in any one of claims 1 to 4 by calling the computer program stored in the memory.

7. A storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the agricultural product supply and demand hierarchical control method applied to an Internet cloud platform as described in any one of claims 1 to 4.

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