CN112766725A - Fresh product supply chain intelligent coordination management system based on artificial intelligence and cloud computing - Google Patents
Fresh product supply chain intelligent coordination management system based on artificial intelligence and cloud computing Download PDFInfo
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Abstract
The invention discloses an intelligent coordination management system of a fresh product supply chain based on artificial intelligence and cloud computing, which comprises a seller sales fresh product type statistical module, a fresh product historical sales statistical module, a to-be-supplemented fresh product parameter analysis module, a buyer intelligent recommendation module, a to-be-purchased buyer statistical module, a to-be-purchased fresh product parameter analysis module and a planting user intelligent recommendation module The comprehensive management requirement of the fresh product supply chain formed by the buyer and the seller.
Description
Technical Field
The invention belongs to the technical field of supply chain management, relates to a fresh product supply chain management technology, and particularly relates to an intelligent coordination management system of a fresh product supply chain based on artificial intelligence and cloud computing.
Background
China is a large producing and consuming country of fresh products, a huge fresh product circulation industry is owned in China, the supply chain integration mode of the fresh product circulation in China is rapidly developing, and along with the development of the market, a fresh product supply chain coordination management system is more and more necessary to be established. From the perspective of supply chain management, in a fresh product supply chain consisting of purchasers and sellers, when a plurality of purchasers correspond to the sellers, the purchasers need to be managed, and then the best purchasers are selected from the purchasers, so that the replenishment cost corresponding to replenishment of the sellers from the purchasers is reduced; in a fresh product supply chain formed by a grower and a buyer, when a plurality of growers corresponding to the buyer need to be managed, the best grower is selected from the growers, and accordingly the purchase cost corresponding to the purchase of the buyer from the grower is reduced. For the fresh product supply chain formed by the grower, the buyer and the seller, the grower and the buyer need to be managed together to realize the cost control of the seller and the buyer and further improve the income of the seller and the buyer.
However, the management mode of the fresh product supply chain formed by the grower, the buyer and the seller is simple at present, parallel management of the grower and the buyer is difficult to realize, and the comprehensive management requirement of the fresh product supply chain formed by the grower, the buyer and the seller cannot be met.
Disclosure of Invention
The invention aims to provide an intelligent coordination management system of a fresh product supply chain based on artificial intelligence and cloud computing, which can realize parallel management of growers and purchasers, and solves the problems in the background art.
The purpose of the invention can be realized by the following technical scheme:
the fresh product supply chain intelligent coordination management system based on artificial intelligence and cloud computing comprises a seller sales fresh product type statistical module, a fresh product historical sales statistical module, a to-be-supplemented fresh product parameter analysis module, a buyer intelligent recommendation module, a to-be-purchased buyer statistical module, a to-be-purchased fresh product parameter analysis module and a grower intelligent recommendation module;
the seller sales fresh product type statistical module is connected with the fresh product historical sales statistical module, the fresh product historical sales statistical module is connected with the fresh product parameter analysis module to be supplemented, the fresh product parameter analysis module to be supplemented is connected with the buyer intelligent recommendation module, the buyer intelligent recommendation module is connected with the buyer statistical module to be purchased, the buyer statistical module to be purchased is connected with the fresh product parameter analysis module to be purchased, and the fresh product parameter analysis module to be purchased is connected with the planter intelligent recommendation module;
the seller sales fresh product type counting module is used for counting the types of the fresh products sold by the seller, numbering the counted types of the fresh products according to a preset sequence, and sequentially marking the counted types as 1,2.. i.. n;
the fresh product historical sales volume counting module is used for obtaining sales volumes corresponding to months in preset historical years for various fresh products sold by a seller, numbering the preset historical years according to a sequence from short time to long time from the current year, and respectively marking the preset historical years as A, Br y(sr y1,sr y2...,sr yt,...,sr y12)，syt represents the sales volume corresponding to the tth month of the tth fresh product in the tth historical year, r represents the serial number of the type of the fresh product, r is 1,2.. i.. N, y represents the serial number of the historical year, y is A, B.. I.. N, t represents the month, t is 1,2.. 12, and the historical sales volume statistical module of the fresh product sends the historical sales volume set of the fresh product to the parameter analysis module of the fresh product to be replenished;
the parameter analysis module of the fresh products to be replenished receives the historical sales volume set of the fresh products sent by the historical sales volume statistic module of the fresh products, and counts the average sales volume corresponding to each fresh product in the current month according to the current month and the historical sales volume set of the fresh products, and at the same time counts the stock corresponding to each fresh product in the current month in the warehouse of the seller, and further compares the average sales volume corresponding to each fresh product in the current month with the stock corresponding to each fresh product in the current month, if the average sales volume corresponding to a certain fresh product is greater than the stock corresponding to the fresh product, the fresh product is marked as the type of the fresh products to be replenished, and at the moment, the serial number of the fresh products to be replenished corresponding to the current month of the seller is counted, and can be marked as 1,2. Therefore, a replenishment quantity set D (D1, D2.. dj, dj.. dm) of the fresh products to be replenished is formed, dj represents the replenishment quantity corresponding to the jth type of the fresh products to be replenished, and the parameter analysis module of the fresh products to be replenished sends the replenishment quantity set of the fresh products to be replenished to the intelligent recommendation module of the buyer;
the intelligent buyer recommending module receives the fresh product replenishment quantity set of the to-be-replenished goods sent by the fresh product parameter analyzing module of the to-be-replenished goods and carries out buyer recommendation on the fresh products of the to-be-replenished goods, wherein the buyer recommending module comprises a buyer counting and marking module, a buyer current storage product parameter counting module, a candidate buyer transportation distance acquiring module and a buyer recommending terminal;
the buyer counting and marking module is used for counting the buyers cooperating with the seller, numbering the counted buyers and marking the numbers as 1,2.. a.. z respectively;
the buyer current storage product parameter counting module is used for obtaining the types of the currently stored fresh products and the storage quantity corresponding to the various fresh products for each counted buyer, numbering the types of the currently stored fresh products of each buyer and marking the types as 1,2a(ca1,ca2...,cak,...,cal)，cak represents the storage amount corresponding to the kth fresh product currently stored by the ath buyer, at the moment, the variety of the fresh product to be supplemented is extracted from the fresh product supplementing amount set to be supplemented, the category of the fresh product to be supplemented is compared with the variety of the fresh product currently stored by each buyer, the number of the buyer with successfully matched variety of the fresh product is screened out, and the matching of the variety of the fresh product is screened out from the storage amount set of the fresh product currently stored by the buyer according to the number of the buyer with successfully matched variety of the fresh productThe method comprises the steps that storage amounts corresponding to various fresh products currently stored by a successful buyer are obtained, so that the replenishment quantity corresponding to various fresh product types of the goods to be replenished is extracted from a replenishment quantity set of the fresh products to be replenished, the replenishment quantity is compared with the storage amounts corresponding to various fresh products currently stored by the buyer successfully matched with the fresh product types, the number of the buyer successfully matched with the replenishment quantity of the fresh product is screened out from the buyer successfully matched with the fresh product types, and the buyer is marked as a candidate buyer;
the candidate buyer transportation distance acquisition module is used for acquiring the geographic position of each candidate buyer and the geographic position of the seller, further counting the transportation distance between each candidate buyer and the seller according to the geographic position of each candidate buyer and the geographic position of the seller, and sending the transportation distance to the buyer recommendation terminal;
the buyer recommending terminal receives the transportation distance between each candidate buyer and each seller sent by the candidate buyer transportation distance acquiring module, sorts each candidate buyer according to the transportation distance between the candidate buyer and each seller from short to long to obtain the sorting result of each candidate buyer, further selects the candidate buyer ranked at the first position from the sorting result, marks the candidate buyer as the target buyer and recommends the target buyer to the seller;
the to-be-purchased buyer counting module is used for obtaining the times of cooperation with the seller within a preset historical year, the types of the fresh products of each cooperation replenishment and the replenishment quantity corresponding to the types of the fresh products of each buyer, and further counting the average replenishment quantity corresponding to the various fresh products of each buyer, so that the average replenishment quantity corresponding to the various fresh products of each buyer is compared with the storage quantity corresponding to the various fresh products currently stored by each buyer, if the average replenishment quantity corresponding to a certain fresh product of a certain buyer is larger than the storage quantity corresponding to the type of the fresh product, the buyer is marked as the to-be-purchased buyer, and the fresh product is marked as the type of the to-be-purchased fresh product;
the fresh product to be purchased parameter analysis module is used for counting the number of the fresh products to be purchasedThe number of the purchasing supplier can be recorded as 1 ', 2'. a.. z ', and the type number of the fresh product to be purchased corresponding to each purchasing supplier and the purchasing amount corresponding to the type of the fresh product to be purchased are counted, wherein the type number of the fresh product to be purchased corresponding to each purchasing supplier can be recorded as 1', 2 '. k.. l', so that the type number of the fresh product to be purchased corresponding to each purchasing supplier and the purchasing amount corresponding to the type of the fresh product to be purchased form a purchasing amount set G of the fresh product to be purchaseda′(ga′1′,ga′2′...,ga′k′,...,ga′l′)，ga′k ' represents the purchase amount corresponding to the kth ' to-be-purchased fresh product type of the a ' th to-be-purchased purchaser, and the to-be-purchased fresh product parameter analysis module sends the to-be-purchased fresh product purchase amount set to the intelligent planting user recommendation terminal;
the intelligent planting user recommending module receives the purchase quantity set of the fresh products to be purchased sent by the parameter analyzing module of the fresh products to be purchased and carries out the recommendation of the planting user corresponding to each purchaser to be purchased, wherein the intelligent planting user recommending terminal comprises a planting user statistic marking module, a planting user fresh product supply parameter statistic module, a candidate planting user transport distance acquiring module and a planting user recommending terminal;
the grower counting and marking module is used for counting the growers cooperating with the buyer and numbering the counted various growers, and the numbers are respectively marked as 1,2.. b.. x;
plant house and supply with raw and fresh product parameter statistics module and be used for obtaining the current fresh product kind that can supply and the single supply volume that each raw and fresh product kind corresponds of various planting house of statistics to the current fresh product kind that can supply of various planting house numbers, marks as 1,2b(fb1,fb2...,fbe,...,fbh)，fbe represents a single time corresponding to the e-th fresh product type currently available to the b-th growerThe supply amount, at this time, the type of the fresh product to be purchased corresponding to the purchaser to be purchased with the number 1' is extracted from the purchase amount set of the fresh product to be purchased according to the number sequence of the purchaser to be purchased, the fresh product to be purchased is compared with the type of the fresh product to be purchased which can be currently supplied by each planting household, if the type of the fresh product which can be currently supplied by a certain planting household is not less than the extracted type of the fresh product to be purchased corresponding to the purchaser to be purchased, the planting household is marked as a first matching planting household, single supply amounts corresponding to various fresh products which can be currently purchased by each first matching planting household are screened out from the supply amount set of the fresh product currently supplied by the planting household according to the number of the first matching planting household, so that the single supply amounts are compared with the extracted purchase amounts corresponding to the types of the fresh product to be purchased of the planting household to be purchased, and the number of a second matching household is screened out from the first matching household, the second matching planting user is marked as a candidate planting user corresponding to the buyer to be purchased;
the candidate planting user transportation distance acquisition module is used for acquiring the corresponding geographical position of each candidate planting user corresponding to the to-be-purchased buyer, further counting the transportation distance between the to-be-purchased buyer and each candidate planting user corresponding to the to-be-purchased buyer according to the geographical position of the to-be-purchased buyer and the geographical position of each candidate planting user corresponding to the to-be-purchased buyer, and sending the transportation distance to the planting user recommendation terminal;
the planting user recommending terminal receives the transportation distance between the candidate planting user and each corresponding candidate planting user sent by the candidate planting user transportation distance obtaining module, sorts each candidate planting user corresponding to the candidate purchasing user according to the transportation distance from short to long between the candidate purchasing user and each corresponding candidate planting user to obtain the sorting result of each candidate planting user corresponding to the purchasing buyer, further screens out the candidate planting user arranged at the first position from the sorting result, marks the candidate planting user as the target planting user, recommends the target planting user to the purchasing user, counts the types of the fresh products which can be currently supplied by each planting user and the single supply amount corresponding to each type of the fresh products after the recommended supply is provided to the purchasing user with the number of 1', further extracts the next numbered purchasing user from the purchasing set of the fresh products to be purchased, and obtaining the target planting user corresponding to the buyer to be purchased according to the method to recommend to the buyer to be purchased until the last serial number of the buyer to be purchased is extracted.
Further, the preset historical years are not less than three years, and the previous years corresponding to the current years are used as historical years for setting starting points.
Further, the calculation formula of the average sales volume corresponding to each fresh product of the current month is
p is indicated as the current month and,
expressed as the average sales, s, corresponding to the various fresh products of the current monthr yp represents the sales volume corresponding to the current month of the r-th fresh product in the y-th historical year.
Furthermore, the statistical method of the replenishment quantity corresponding to each type of the fresh product to be replenished is to subtract the inventory corresponding to the type of the fresh product to be replenished from the average sales corresponding to each type of the fresh product to be replenished.
Furthermore, the fresh product type matching success means that the type of the fresh product currently stored by a certain buyer is consistent with or greater than the type of the fresh product to be replenished, and the fresh product replenishment quantity matching success means that the storage quantity corresponding to each type of the fresh product to be replenished currently stored by the certain buyer with the successfully matched type of the fresh product is greater than or equal to the replenishment quantity corresponding to the type of the fresh product to be replenished.
Furthermore, the statistical method of the average replenishment quantity corresponding to each fresh product of each buyer is to accumulate the replenishment quantity corresponding to each fresh product type of each cooperative replenishment of each buyer and each seller, and then divide the accumulated replenishment quantity by the number of times of cooperation corresponding to the fresh product type of the cooperative replenishment of each seller.
Further, the purchasing quantity statistical method corresponding to each type of the fresh products to be purchased of each purchasing supplier is to subtract the storage quantity corresponding to the type of the fresh products to be purchased from the average replenishment quantity corresponding to each type of the fresh products to be purchased of each purchasing supplier.
Further, the second matching planting user means that the single supply amount corresponding to each kind of fresh product to be purchased which can be currently supplied by a certain first matching planting user is greater than or equal to the purchase amount corresponding to each kind of fresh product to be purchased of the purchaser to be purchased.
The invention has the following beneficial effects:
(1) the invention carries out the parameter statistics of the fresh products to be purchased and the corresponding purchase quantity by counting the types of the fresh products to be purchased corresponding to the current month of the seller and carrying out the parameter statistics of the currently stored products for each buyer cooperating with the seller, thereby carrying out the recommendation of the buyer, simultaneously screening the buyer to be purchased from the buyers, obtaining the types of the fresh products to be purchased and the corresponding purchase quantity of each buyer, further carrying out the parameter statistics of the fresh products supplied for each grower cooperating with the buyer, thereby carrying out the recommendation of the grower for each buyer to be purchased, realizing the parallel management of the grower and the buyer in the fresh products supply chain formed by the grower, the buyer and the seller, reflecting the comprehensive management of the supply chain, making up the single defect existing in the management mode of the fresh products supply chain, and improving the management level of the fresh products supply chain, the comprehensive management requirement of a fresh product supply chain formed by growers, purchasers and sellers is met.
(2) In the process of recommending buyers for a seller and the process of recommending planters for buyers to be purchased, all adopt a hierarchical recommendation mode, firstly screen out candidate buyers and candidate growers from the buyers and the growers, then obtain the transportation distance between each candidate buyer and the seller and the transportation distance between each candidate grower and the buyer to be purchased according to the characteristic that fresh products are not easy to keep fresh, and further screen out the candidate buyer and the candidate grower with the shortest transportation distance, the buyer and the planting user recommended by the recommendation method can meet the replenishment and purchase requirements of the fresh products corresponding to the seller and the purchasing buyer to be purchased, can meet the fresh-keeping requirements of the fresh products, have the characteristics of high intelligent degree and strong practicability, and comprehensively meet the optimal recommendation requirements of the buyer and the planting user.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a schematic diagram of the module connection of the present invention;
FIG. 2 is a schematic diagram of the buyer intelligent recommendation module connection of the present invention;
FIG. 3 is a schematic diagram of the connection of the intelligent grower recommendation module 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.
Referring to fig. 1, the fresh product supply chain intelligent coordination management system based on artificial intelligence and cloud computing comprises a seller sales fresh product type statistical module, a fresh product historical sales statistical module, a to-be-supplemented fresh product parameter analysis module, a buyer intelligent recommendation module, a to-be-purchased fresh product statistical module, a to-be-purchased fresh product parameter analysis module and a grower intelligent recommendation module, wherein the seller sales fresh product type statistical module is connected with the fresh product historical sales statistical module, the fresh product historical sales statistical module is connected with the to-be-supplemented fresh product parameter analysis module, the to-be-supplemented fresh product parameter analysis module is connected with the buyer intelligent recommendation module, the buyer intelligent recommendation module is connected with the to-be-purchased fresh product statistical module, and the to-be-purchased fresh product statistical module is connected with the to-be-purchased fresh product parameter analysis module, the fresh product to be purchased parameter analysis module is connected with the intelligent recommendation module of the grower.
The fresh product type counting module sold by the seller is used for counting the types of the fresh products sold by the seller, numbering the counted types of the fresh products according to a preset sequence, and marking the counted types of the fresh products as 1,2.
The fresh product historical sales volume counting module is used for acquiring sales volumes corresponding to months in preset historical years for various fresh products sold by a seller, wherein the preset historical years are not less than three years, a starting point is set by taking the last year corresponding to the current year as the historical years, the preset historical years are numbered according to the sequence from short to long from the current year, the preset historical years are marked as A, Br y(sr y1,sr y2...,sr yt,...,sr y12)，syt represents the sales volume corresponding to the tth month of the tth fresh product in the tth historical year, r represents the serial number of the type of the fresh product, r is 1,2.
The historical sales volume set of the fresh products counted by the embodiment provides a statistical basis for later counting the average sales volumes corresponding to various fresh products in the current month.
This embodiment should be no less than three years through setting up historical year, is to avoid the historical year of setting too little, leads to the average sales volume that each kind of fresh products of present month of back statistics corresponds to have statistical error, does not have the credibility.
Receiving historical sales volume statistical model of fresh product by parameter analysis module of fresh product to be replenishedHistorical sales volume sets of the fresh products sent by the blocks, and the average sales volume corresponding to various fresh products in the current month is counted according to the current month and the historical sales volume sets of the fresh products
p is indicated as the current month and,
expressed as the average sales, s, corresponding to the various fresh products of the current monthr yp is the sales volume of the r-th fresh product in the current month within the y-th historical year, meanwhile, the stock quantities corresponding to the various fresh products in the current month in the warehouse of the seller are counted, the average sales volume corresponding to the various fresh products in the current month is compared with the stock quantities corresponding to the various fresh products in the current month, if the average sales volume corresponding to a certain fresh product is greater than the stock quantity corresponding to the fresh product, the fresh product is marked as the type of the fresh product to be replenished, at the moment, the serial number of the fresh product to be replenished corresponding to the current month of the seller is counted and can be marked as 1,2. Therefore, a replenishment quantity set D (D1, D2.. dj, dj.. dm) of the fresh products to be replenished is formed, dj represents the replenishment quantity corresponding to the jth type of the fresh products to be replenished, and the parameter analysis module of the fresh products to be replenished sends the replenishment quantity set of the fresh products to be replenished to the intelligent recommendation module of the buyer.
In the embodiment, the construction of the replenishment quantity set of the fresh products to be replenished lays a foundation for the subsequent screening of the candidate buyers.
The intelligent buyer recommending module receives the fresh product replenishment quantity set of the to-be-replenished goods sent by the fresh product parameter analyzing module of the to-be-replenished goods, and recommends the buyer of the fresh product of the to-be-replenished goods, and the recommending module of the buyer refers to fig. 2, wherein the recommending module of the buyer comprises a statistic marking module of the buyer, a statistic module of the current stored product parameters of the buyer, a transportation distance acquiring module of a candidate buyer and a recommending terminal of the buyer.
The buyer counting and marking module is used for counting the buyers cooperating with the seller, numbering the counted buyers and marking the numbers as 1,2.. a.. z respectively;
the buyer current storage product parameter counting module is used for obtaining the types of the currently stored fresh products and the storage quantity corresponding to the various fresh products for each counted buyer, numbering the types of the currently stored fresh products of each buyer and marking the types as 1,2a(ca1,ca2...,cak,...,cal)，cak is the storage amount corresponding to the kth fresh product currently stored by the ath buyer, at this time, the variety of each fresh product to be supplemented is extracted from the fresh product supplement amount set to be supplemented, the fresh product variety is compared with the variety of the fresh product currently stored by each buyer, and the buyer number with successfully matched fresh product variety is selected from the fresh product supplement amount set, wherein the successfully matched fresh product variety means that the variety of the fresh product currently stored by a certain buyer is consistent with or larger than the variety of the fresh product to be supplemented, and the storage amount corresponding to each fresh product currently stored by the buyer with successfully matched fresh product variety is screened from the fresh product storage amount set currently stored by the buyer according to the number of the buyer with successfully matched fresh product variety, so that the supplement amount corresponding to each fresh product variety to be supplemented is extracted from the fresh product supplement amount set to be supplemented, comparing the storage amount of the fresh products with the storage amount corresponding to various fresh products currently stored by the buyer successfully matched with the types of the fresh products, and screening out the number of the buyer successfully matched with the replenishment amount of the fresh products from the buyers successfully matched with the types of the fresh products, wherein the successful matching of the replenishment amount of the fresh products means that the storage amount corresponding to each type of the fresh products to be replenished currently stored by the buyer successfully matched with the types of the fresh products is more than or equal to the storage amount corresponding to each type of the fresh products to be replenishedThe corresponding replenishment quantity, and the buyer is marked as a candidate buyer;
the candidate buyer transportation distance acquisition module is used for acquiring the geographic position of each candidate buyer and acquiring the geographic position of the seller, further counting the transportation distance between each candidate buyer and the seller according to the geographic position of each candidate buyer and the geographic position of the seller, and sending the transportation distance to the buyer recommendation terminal;
the embodiment provides a screening basis for screening target buyers from the candidate buyers in the later period by acquiring the transportation distance between each candidate buyer and the seller.
And the buyer recommending terminal receives the transportation distance between each candidate buyer and the seller, which is sent by the candidate buyer transportation distance acquiring module, sorts each candidate buyer according to the transportation distance between the candidate buyer and the seller from short to long to obtain the sorting result of each candidate buyer, further selects the candidate buyer ranked at the first position from the sorting results, marks the candidate buyer as the target buyer and recommends the target buyer to the seller.
The statistical module of the purchasing company to be purchased is used for acquiring the number of times of cooperation with the seller, the fresh product type of each cooperative replenishment and the replenishment quantity corresponding to each fresh product type within a preset historical age for each purchasing company which cooperates with the seller, wherein the statistical method of the average replenishment quantity corresponding to each fresh product of each purchasing company is to accumulate the replenishment quantity corresponding to each fresh product type of each cooperative replenishment of each purchasing company and the seller, divide the accumulated replenishment quantity by the cooperation number corresponding to each fresh product type of the cooperative replenishment of the seller, compare the average replenishment quantity corresponding to each fresh product of each purchasing company with the storage quantity corresponding to each fresh product currently stored by each purchasing company, and if the average replenishment quantity corresponding to a certain fresh product of a certain purchasing company is larger than the storage quantity corresponding to the fresh product type, the purchasing company is marked as the purchasing company to be purchased, the kind of fresh product is recorded as the kind of fresh product to be purchased.
The parameter analysis module of the fresh product to be purchased is used for counting the serial number of the purchaser to be purchased, and can be recorded as 1 ', 2'.A '. z', and counting the number of the types of the fresh products to be purchased corresponding to each buyer to be purchased and the purchase amount corresponding to the types of the fresh products to be purchased, wherein the method for counting the purchase amount corresponding to the types of the fresh products to be purchased of each buyer to be purchased is to subtract the storage amount corresponding to the types of the fresh products to be purchased from the average replenishment amount corresponding to the types of the fresh products to be purchased of each buyer to be purchased, wherein the number of the types of the fresh products to be purchased corresponding to each buyer to be purchased can be recorded as 1 ', 2'. k '. l', so that the number of the types of the fresh products to be purchased corresponding to each buyer to be purchased and the purchase amount corresponding to the types of the fresh products to be purchased form a purchase amount set G of the fresh products to be purchaseda′(ga′1′,ga′2′...,ga′k′,...,ga′l′)，ga′And k ' represents the purchase amount corresponding to the kth ' to-be-purchased fresh product type of the a ' th to-be-purchased purchaser, and the to-be-purchased fresh product parameter analysis module sends the to-be-purchased fresh product purchase amount set to the intelligent planting user recommendation terminal.
The intelligent planting user recommending module receives the purchase quantity set of the to-be-purchased fresh products sent by the to-be-purchased fresh product parameter analyzing module, and carries out planting user recommendation corresponding to each to-be-purchased purchaser, and as shown in fig. 3, the intelligent planting user recommending terminal comprises a planting user statistic marking module, a planting user supply fresh product parameter statistic module, a candidate planting user transport distance acquiring module and a planting user recommending terminal.
The planter counting and marking module is used for counting planters cooperating with a buyer, numbering the counted planters and marking the counted planters as 1,2.. b.. x respectively;
the parameter counting module for the fresh product supplied by the grower is used for acquiring the types of the fresh products which can be supplied currently and the single supply amount corresponding to the types of the fresh products which can be supplied currently for various growers in statistics, numbering the types of the fresh products which can be supplied currently by various growers, and marking the types as 1,2And Fb(fb1,fb2...,fbe,...,fbh)，fbe represents the single supply quantity corresponding to the e-th fresh product type which can be currently supplied by the b-th planter, at this time, the fresh product type to be purchased with the number of 1' is extracted from the fresh product purchase quantity set to be purchased according to the number sequence of the purchaser to be purchased, the fresh product type to be purchased is compared with the fresh product type which can be currently supplied by each planter, if the fresh product type which can be currently supplied by a certain planter is not less than the extracted fresh product type to be purchased corresponding to the purchaser to be purchased, the planter is marked as a first matching planter, and the single supply quantity corresponding to the various fresh products which can be currently supplied by each first matching planter is screened from the fresh product supply quantity set currently supplied by the planter according to the number of the first matching planter, so as to compare the single supply quantity corresponding to the extracted fresh product type to be purchased of the purchaser to be purchased by the b-th planter, screening out a second matching planting user number from the first matching planting users, wherein the second matching planting users refer to that the single supply quantity corresponding to each kind of the fresh products to be purchased which can be currently supplied by a certain first matching planting user is more than or equal to the purchase quantity corresponding to each kind of the fresh products to be purchased of the purchaser to be purchased, and the second matching planting users are marked as candidate planting users corresponding to the purchaser to be purchased;
the candidate planting user transportation distance acquisition module is used for acquiring the corresponding geographical position of each candidate planting user corresponding to the to-be-purchased buyer, further counting the transportation distance between the to-be-purchased buyer and each candidate planting user corresponding to the to-be-purchased buyer according to the geographical position of the to-be-purchased buyer and the geographical position of each candidate planting user corresponding to the to-be-purchased buyer, and sending the transportation distance to the planting user recommendation terminal;
the embodiment provides a screening basis for screening the target growers from the candidate growers in the later period by acquiring the transportation distance between each candidate grower and the to-be-purchased purchaser.
The planting user recommending terminal receives the transportation distance between the candidate planting user and each corresponding candidate planting user sent by the candidate planting user transportation distance obtaining module, sorts each candidate planting user corresponding to the candidate purchasing user according to the transportation distance between the candidate purchasing user and each corresponding candidate planting user from short to long to obtain the sorting result of each candidate planting user corresponding to the to-be-purchased purchasing user, further screens out the candidate planting user ranked at the first position from the sorting result, marks the candidate planting user as the target planting user, recommends the target planting user to the to-be-purchased purchasing user, counts the types of the fresh products which can be currently supplied by each planting user and the single supply amount corresponding to each type of the fresh products after recommending and supplying to the to-be-purchased purchasing user with the number of 1', further extracts the next numbered to-be-purchased purchasing user from the to-be-purchased fresh product purchasing amount set, and obtaining the target planting user corresponding to the buyer to be purchased according to the method to recommend to the buyer to be purchased until the last serial number of the buyer to be purchased is extracted.
In the process of recommending buyers to a seller and recommending planters to each buyer to be purchased, all adopt a hierarchical recommendation mode, firstly screen out candidate buyers and candidate growers from the buyers and the growers, then obtain the transportation distance between each candidate buyer and the seller and the transportation distance between each candidate grower and the buyer to be purchased according to the characteristic that fresh products are not easy to keep fresh, and further screen out the candidate buyer and the candidate grower with the shortest transportation distance, the buyer and the planting user recommended by the recommendation method can meet the replenishment and purchase requirements of the fresh products corresponding to the seller and the purchasing buyer to be purchased, can meet the fresh-keeping requirements of the fresh products, have the characteristics of high intelligent degree and strong practicability, and comprehensively meet the optimal recommendation requirements of the buyer and the planting user.
In the embodiment, the buyer recommendation is carried out on the seller, and the planter recommendation is carried out on each buyer to be purchased, so that the parallel management of the planters and the buyers in the fresh product supply chain consisting of the planters, the buyers and the sellers is realized, the comprehensive management of the supply chain is embodied, the defect of simplification of the management mode of the current fresh product supply chain is overcome, the cost control of the sellers and the buyers is further realized, the income of the sellers and the buyers is improved, the management level of the fresh product supply chain is improved, and the comprehensive management requirement of the fresh product supply chain consisting of the planters, the buyers and the sellers is met.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (8)
1. Give birth to bright product supply chain intelligent coordination management system based on artificial intelligence and cloud calculate, its characterized in that: the system comprises a seller sales fresh product type statistical module, a fresh product historical sales statistical module, a fresh product parameter analysis module to be replenished, a buyer intelligent recommendation module, a buyer statistical module to be purchased, a fresh product parameter analysis module to be purchased and a grower intelligent recommendation module;
the seller sales fresh product type statistical module is connected with the fresh product historical sales statistical module, the fresh product historical sales statistical module is connected with the fresh product parameter analysis module to be supplemented, the fresh product parameter analysis module to be supplemented is connected with the buyer intelligent recommendation module, the buyer intelligent recommendation module is connected with the buyer statistical module to be purchased, the buyer statistical module to be purchased is connected with the fresh product parameter analysis module to be purchased, and the fresh product parameter analysis module to be purchased is connected with the planter intelligent recommendation module;
the seller sales fresh product type counting module is used for counting the types of the fresh products sold by the seller, numbering the counted types of the fresh products according to a preset sequence, and sequentially marking the counted types as 1,2.. i.. n;
the fresh product historical sales volume counting module is used for acquiring sales volumes corresponding to months in preset historical years for various fresh products sold by sellers, and at the moment, the preset historical years are used for counting the distance between the various fresh productsNumbering the current year time from short to long, marking the current year time as A, Br y(sr y1,sr y2...,sr yt,...,sr y12)，syt represents the sales volume corresponding to the tth month of the tth fresh product in the tth historical year, r represents the serial number of the type of the fresh product, r is 1,2.. i.. N, y represents the serial number of the historical year, y is A, B.. I.. N, t represents the month, t is 1,2.. 12, and the historical sales volume statistical module of the fresh product sends the historical sales volume set of the fresh product to the parameter analysis module of the fresh product to be replenished;
the parameter analysis module of the fresh products to be replenished receives the historical sales volume set of the fresh products sent by the historical sales volume statistic module of the fresh products, and counts the average sales volume corresponding to each fresh product in the current month according to the current month and the historical sales volume set of the fresh products, and at the same time counts the stock corresponding to each fresh product in the current month in the warehouse of the seller, and further compares the average sales volume corresponding to each fresh product in the current month with the stock corresponding to each fresh product in the current month, if the average sales volume corresponding to a certain fresh product is greater than the stock corresponding to the fresh product, the fresh product is marked as the type of the fresh products to be replenished, and at the moment, the serial number of the fresh products to be replenished corresponding to the current month of the seller is counted, and can be marked as 1,2. Therefore, a replenishment quantity set D (D1, D2.. dj, dj.. dm) of the fresh products to be replenished is formed, dj represents the replenishment quantity corresponding to the jth type of the fresh products to be replenished, and the parameter analysis module of the fresh products to be replenished sends the replenishment quantity set of the fresh products to be replenished to the intelligent recommendation module of the buyer;
the intelligent buyer recommending module receives the fresh product replenishment quantity set of the to-be-replenished goods sent by the fresh product parameter analyzing module of the to-be-replenished goods and carries out buyer recommendation on the fresh products of the to-be-replenished goods, wherein the buyer recommending module comprises a buyer counting and marking module, a buyer current storage product parameter counting module, a candidate buyer transportation distance acquiring module and a buyer recommending terminal;
the buyer counting and marking module is used for counting the buyers cooperating with the seller, numbering the counted buyers and marking the numbers as 1,2.. a.. z respectively;
the buyer current storage product parameter counting module is used for obtaining the types of the currently stored fresh products and the storage quantity corresponding to the various fresh products for each counted buyer, numbering the types of the currently stored fresh products of each buyer and marking the types as 1,2a(ca1,ca2...,cak,...,cal)，cak is the storage amount corresponding to the kth fresh product currently stored by the ith buyer, the category of each fresh product to be supplemented is extracted from the fresh product supplement amount set to be supplemented, the category of each fresh product to be supplemented is compared with the category of each fresh product currently stored by each buyer, the number of the buyer with successfully matched category of the fresh product is screened out, the storage amount corresponding to each fresh product currently stored by the buyer with successfully matched category of the fresh product is screened out from the storage amount set of the fresh product currently stored by the buyer according to the number of the buyer with successfully matched category of the fresh product, the supplement amount corresponding to each fresh product category of the fresh product to be supplemented is extracted from the fresh product supplement amount set to be supplemented, the storage amount corresponding to each fresh product currently stored by the buyer with successfully matched category of each fresh product is compared, and the number of the buyer with successfully matched category of the fresh product is screened out from the buyer with successfully matched category of each fresh product The buyer is marked as a candidate buyer;
the candidate buyer transportation distance acquisition module is used for acquiring the geographic position of each candidate buyer and the geographic position of the seller, further counting the transportation distance between each candidate buyer and the seller according to the geographic position of each candidate buyer and the geographic position of the seller, and sending the transportation distance to the buyer recommendation terminal;
the buyer recommending terminal receives the transportation distance between each candidate buyer and each seller sent by the candidate buyer transportation distance acquiring module, sorts each candidate buyer according to the transportation distance between the candidate buyer and each seller from short to long to obtain the sorting result of each candidate buyer, further selects the candidate buyer ranked at the first position from the sorting result, marks the candidate buyer as the target buyer and recommends the target buyer to the seller;
the to-be-purchased buyer counting module is used for obtaining the times of cooperation with the seller within a preset historical year, the types of the fresh products of each cooperation replenishment and the replenishment quantity corresponding to the types of the fresh products of each buyer, and further counting the average replenishment quantity corresponding to the various fresh products of each buyer, so that the average replenishment quantity corresponding to the various fresh products of each buyer is compared with the storage quantity corresponding to the various fresh products currently stored by each buyer, if the average replenishment quantity corresponding to a certain fresh product of a certain buyer is larger than the storage quantity corresponding to the type of the fresh product, the buyer is marked as the to-be-purchased buyer, and the fresh product is marked as the type of the to-be-purchased fresh product;
the to-be-purchased fresh product parameter analysis module is used for counting the serial numbers of the to-be-purchased purchasers, wherein the serial numbers can be recorded as 1 ', 2'. a.. z ', and counting the serial numbers of the to-be-purchased fresh products corresponding to the to-be-purchased purchasers and the purchase amounts corresponding to the types of the to-be-purchased fresh products, wherein the serial numbers of the to-be-purchased fresh products corresponding to the to-be-purchased purchasers can be recorded as 1', 2 '. k.. l', so that the serial numbers of the to-be-purchased fresh products corresponding to the to-be-purchased purchasers and the purchase amounts corresponding to the types of the to-be-purchased fresh products form a to-be-purchased fresh product purchase amount set Ga′(ga′1′,ga′2′...,ga′k′,...,ga′l′)，ga′k 'is represented as the purchasing quantity corresponding to the kth product type to be purchased of the a' th purchasing supplier to be purchased, and the parameter analysis module of the to-be-purchased fresh product gathers the purchasing quantity of the to-be-purchased fresh productSending the information to an intelligent recommendation terminal of a grower;
the intelligent planting user recommending module receives the purchase quantity set of the fresh products to be purchased sent by the parameter analyzing module of the fresh products to be purchased and carries out the recommendation of the planting user corresponding to each purchaser to be purchased, wherein the intelligent planting user recommending terminal comprises a planting user statistic marking module, a planting user fresh product supply parameter statistic module, a candidate planting user transport distance acquiring module and a planting user recommending terminal;
the grower counting and marking module is used for counting the growers cooperating with the buyer and numbering the counted various growers, and the numbers are respectively marked as 1,2.. b.. x;
plant house and supply with raw and fresh product parameter statistics module and be used for obtaining the current fresh product kind that can supply and the single supply volume that each raw and fresh product kind corresponds of various planting house of statistics to the current fresh product kind that can supply of various planting house numbers, marks as 1,2b(fb1,fb2...,fbe,...,fbh)，fbe represents the single supply quantity corresponding to the e-th fresh product type which can be currently supplied by the b-th planter, at this time, the fresh product type to be purchased with the number of 1' is extracted from the fresh product purchase quantity set to be purchased according to the number sequence of the purchaser to be purchased, the fresh product type to be purchased is compared with the fresh product type which can be currently supplied by each planter, if the fresh product type which can be currently supplied by a certain planter is not less than the extracted fresh product type to be purchased corresponding to the purchaser to be purchased, the planter is marked as a first matching planter, and the single supply quantity corresponding to the various fresh products which can be currently supplied by each first matching planter is screened from the fresh product supply quantity set currently supplied by the planter according to the number of the first matching planter, so as to compare the single supply quantity corresponding to the extracted fresh product type to be purchased of the purchaser to be purchased by the b-th planter, screening from first matched growersOutputting a second matching planting household number, and recording the second matching planting household as a candidate planting household corresponding to the buyer to be purchased;
the candidate planting user transportation distance acquisition module is used for acquiring the corresponding geographical position of each candidate planting user corresponding to the to-be-purchased buyer, further counting the transportation distance between the to-be-purchased buyer and each candidate planting user corresponding to the to-be-purchased buyer according to the geographical position of the to-be-purchased buyer and the geographical position of each candidate planting user corresponding to the to-be-purchased buyer, and sending the transportation distance to the planting user recommendation terminal;
the planting user recommending terminal receives the transportation distance between the candidate planting user and each corresponding candidate planting user sent by the candidate planting user transportation distance obtaining module, sorts each candidate planting user corresponding to the candidate purchasing user according to the transportation distance from short to long between the candidate purchasing user and each corresponding candidate planting user to obtain the sorting result of each candidate planting user corresponding to the purchasing buyer, further screens out the candidate planting user arranged at the first position from the sorting result, marks the candidate planting user as the target planting user, recommends the target planting user to the purchasing user, counts the types of the fresh products which can be currently supplied by each planting user and the single supply amount corresponding to each type of the fresh products after the recommended supply is provided to the purchasing user with the number of 1', further extracts the next numbered purchasing user from the purchasing set of the fresh products to be purchased, and obtaining the target planting user corresponding to the buyer to be purchased according to the method to recommend to the buyer to be purchased until the last serial number of the buyer to be purchased is extracted.
2. The fresh produce product supply chain intelligent coordination management system based on artificial intelligence and cloud computing of claim 1, wherein: the preset historical years are not less than three years, and the last years corresponding to the current years are used as historical years for setting starting points.
3. The fresh produce supply chain intelligent coordination pipe based on artificial intelligence and cloud computing of claim 1The reason system, its characterized in that: the calculation formula of the average sales volume corresponding to various fresh products in the current month is
p is indicated as the current month and,
expressed as the average sales, s, corresponding to the various fresh products of the current monthr yp represents the sales volume corresponding to the current month of the r-th fresh product in the y-th historical year.
4. The fresh produce product supply chain intelligent coordination management system based on artificial intelligence and cloud computing of claim 1, wherein: the statistical method of the replenishment quantity corresponding to each category of the fresh products to be replenished is to subtract the stock corresponding to each category of the fresh products to be replenished from the average sales corresponding to each category of the fresh products to be replenished.
5. The fresh produce product supply chain intelligent coordination management system based on artificial intelligence and cloud computing of claim 1, wherein: the fresh product type matching success means that the type of the fresh product currently stored by a certain buyer is consistent with or larger than the type of the fresh product to be supplemented, and the fresh product replenishment quantity matching success means that the storage quantity corresponding to each type of the fresh product to be supplemented currently stored by the buyer with a certain fresh product type matching success is larger than or equal to the replenishment quantity corresponding to the type of the fresh product to be supplemented.
6. The fresh produce product supply chain intelligent coordination management system based on artificial intelligence and cloud computing of claim 1, wherein: the statistical method of the average replenishment quantity corresponding to each fresh product of each buyer is to accumulate the replenishment quantity corresponding to each fresh product type of each cooperative replenishment of each buyer and each seller, and then divide the accumulated replenishment quantity by the cooperation frequency corresponding to the fresh product type of the cooperative replenishment of each seller.
7. The fresh produce product supply chain intelligent coordination management system based on artificial intelligence and cloud computing of claim 1, wherein: the statistical method of the purchasing quantity corresponding to each type of the fresh products to be purchased of each buyer to be purchased is to subtract the storage quantity corresponding to the type of the fresh products to be purchased from the average replenishment quantity corresponding to each type of the fresh products to be purchased of each buyer to be purchased.
8. The fresh produce product supply chain intelligent coordination management system based on artificial intelligence and cloud computing of claim 1, wherein: the second matching planting user refers to that the single supply quantity corresponding to each kind of the fresh product to be purchased which can be currently supplied by a certain first matching planting user is more than or equal to the purchase quantity corresponding to each kind of the fresh product to be purchased of the purchasing company to be purchased.
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