A catering food material standardization difference dynamic early warning method and system

Abstract

The present application relates to the technical field of catering system regulation, in particular to a catering material standardization difference dynamic early warning method and system, whether the first node's compliance rate is corrected according to the current early warning level, if so, the correlation model between nodes is established, and the correlation parameters of a plurality of first nodes are obtained through the correlation model; the correlation parameters and the compliance rate of the first node corresponding to the correlation parameters are obtained, and the compliance rate of the first node is corrected through the correlation parameters. Through the above method, the correlation model between nodes is established to obtain a correlation parameter, the compliance rate of the qualified first node is corrected through the correlation parameter, so that all qualified first nodes can obtain a more objective compliance rate, and according to the corrected compliance rate, it is judged again whether the first node needs to be changed to an unqualified second node, thereby affecting the final early warning level and outputting more accurate and objective early warning signals.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of catering system regulation, in particular to a catering food material standardization difference dynamic early warning method and system. BACKGROUND

[0002] The background technology of catering food material standardization mainly comes from the demand for industrialization and chain development of the catering industry, as well as the mature application of digital technology. With the global expansion of the catering industry, chain brands have increasingly high requirements for menu consistency, cost controllability and food safety, and traditional manual management cannot meet the precise control needs. Under this background, the core technology supporting standardization has gradually developed.

[0003] As disclosed in CN115457543A, a visual-based catering production whole-process monitoring and management system includes a food material purchase image acquisition module, a food material purchase image analysis module, a food material freshness detection module, a food material freshness analysis module, a food material appearance information detection module, a food material cleaning detection module, a food material cleaning rule setting module, a food material cleaning analysis module, an early warning terminal and a database. The prior art evaluates the early warning through multiple parameters of the food material, and the focus is on the collection of food material parameters. Since there is a certain correlation between each node and each node in the whole catering process, the prior art does not consider the influence of nodes on early warning evaluation in the whole catering process, which may cause inaccurate final early warning results. SUMMARY

[0004] The purpose of the present application is to provide a catering food material standardization difference dynamic early warning method and system to solve the above problems in the prior art.

[0005] The present application is achieved by the following technical solutions:

[0006] A catering food material standardization difference dynamic early warning method, comprising:

[0007] Setting a standardization standard for food materials, obtaining a plurality of target parameters of a plurality of nodes in the whole catering process, and obtaining a plurality of standard rates of each node according to the target parameters and the standard rate;

[0008] Setting a standard rate qualified threshold, judging whether the node is qualified by the standard rate and the standard rate qualified threshold, if there is an unqualified node, obtaining the current early warning level according to the number of qualified first nodes and the number of unqualified second nodes, and judging whether to correct the standard rate of the first node according to the current early warning level, if not, outputting the current early warning level;

[0009] If yes, an association model between nodes is established, and the association parameters of a plurality of first nodes are obtained through the association model.

[0010] obtaining the association parameter and the first node corresponding to the association parameter, correcting the first node's compliance rate through the association parameter, and outputting the corrected first node's compliance rate;

[0011] determining whether the corrected first node is qualified according to the corrected first node's compliance rate and the compliance rate threshold, and outputting the current warning level after correction according to whether the corrected first node is qualified;

[0012] If there is no unqualified node, no warning is made.

[0013] Preferably, the set food material standardization compliance benchmark comprises:

[0014] A control index table is established, which comprises a plurality of nodes arranged in a first index layer, a food material owned by each node arranged in a second index layer under each of the plurality of nodes, and a plurality of compliance standards of each food material arranged in a third index layer under the food material in the current node.

[0015] When a target parameter that does not meet a certain compliance standard appears, the second index layer in which the current target parameter is located is marked.

[0016] The number of marked second index layers and the number of unmarked second index layers in the same first index layer are counted respectively, and the compliance rate of the plurality of first index layers is outputted.

[0017] Preferably, the current warning level is obtained according to the number of qualified first nodes and the number of unqualified second nodes, comprising:

[0018] The comprehensive unqualified rate of the plurality of nodes in the whole process is obtained according to the number of first nodes and the number of second nodes.

[0019] The comprehensive unqualified rate and the node's basic parameter are obtained respectively, and a warning level judgment model is established through the first node's compliance rate, the second node's compliance rate and the node's basic parameter.

[0020] A judgment value is outputted through the warning level judgment model, different warning levels are divided according to the corresponding judgment threshold, and the current warning level corresponding to the judgment threshold is outputted according to the judgment value and the range of the judgment threshold.

[0021] Preferably, the node's basic parameter comprises a first parameter of node cost, a second parameter of the number of nodes to be passed through by the consumer, a third parameter of the number of food material types involved in the node, and a fourth parameter of the current food material cost involved in the node.

[0022] Acquire the average value of the first parameter, the second parameter, the third parameter and the fourth parameter respectively, acquire the number of each parameter greater than the average value in each node respectively, and establish an early warning level judgment model;

[0023]

[0024] In the formula, R s is a judgment value, m is the total number of the first parameters greater than Q a , Q i is the i-th first parameter greater than Q a , Q a is the average value of the first parameter, k is the total number of the second parameters greater than N a , N k is the k-th second parameter greater than N a , N a is the average value of the second parameter, o is the total number of the third parameters greater than K a , K o is the o-th third parameter greater than K a , K a is the average value of the third parameter, u is the total number of the fourth parameters greater than G a , G u is the v-th fourth parameter greater than G a , G a is the average value of the fourth parameter, E is the total number of nodes, H2 is the number of the second nodes, and H1 is the number of the first nodes.

[0025] Preferably, the judgment value output by the early warning level judgment model includes:

[0026] The first early warning level, the second early warning level and the highest early warning level and the first judgment threshold, the second judgment threshold and the third judgment threshold corresponding to each early warning level are set;

[0027] The first judgment threshold, the second judgment threshold and the third judgment threshold satisfy:

[0028]

[0029] In the formula, R1 is the end value of the first judgment threshold and the second judgment threshold, and R2 is the end value of the second judgment threshold and the third judgment threshold;

[0030] The first judgment threshold is less than or equal to R1, the second judgment threshold is (R1, R2], and the third judgment threshold is greater than R2;

[0031] The early warning severity of the first early warning level, the second early warning level and the highest early warning level increases in turn.

[0032] Preferably, further comprising:

[0033] receiving the current warning level, if the current warning level is the first warning level, sending the warning signal to the first terminal, if the current warning level is the second warning level, sending to the second terminal, if the current warning level is the highest warning level, sending to the third terminal;

[0034] The management authority of the second terminal is greater than the first terminal, and the management authority of the third terminal is greater than the second terminal.

[0035] establishing a communication method of the first terminal, the second terminal and the third terminal, and adjusting the current warning level according to the communication method.

[0036] Preferably, the communication method of the first terminal, the second terminal and the third terminal comprises:

[0037] When the first terminal receives the first warning level warning signal, the first time threshold is started, if the first warning level warning signal cannot be eliminated within the first time threshold, the current warning signal is replaced by the second warning level signal, sent to the second terminal, and the second time threshold is started;

[0038] If the second warning level warning signal cannot be eliminated within the second time threshold, the current warning signal is replaced by the highest warning level signal, sent to the third terminal;

[0039] When the second terminal receives the second warning level warning signal, the second time threshold is started, if the second warning level warning signal cannot be eliminated within the second time threshold, the current warning signal is replaced by the highest warning level, sent to the third terminal.

[0040] Preferably, the method further comprises:

[0041] If the current warning level is the first warning level or the second warning level, the warning level correction is carried out;

[0042] If the current warning level is the highest warning level, the warning level correction is not carried out.

[0043] Preferably, the method further comprises:

[0044]

[0045] The method further comprises:

[0046]

[0047] In the formula, W j is the association parameter of the jth first node, alpha b,j is the number of second nodes directly associated with the jth first node, alpha j is the number of all nodes directly associated with the first node, eta z,j is the compliance rate of the jth first node, eta j is the compliance rate of the jth first node.

[0048] In a second aspect, the application further provides a difference dynamic early warning system for food material standardization, comprising:

[0049] An early warning module is configured to set a standardization compliance benchmark, acquire a plurality of target parameters of a plurality of nodes in a whole food service process, and obtain a plurality of compliance rates of each node according to the target parameters and the standardization compliance benchmark.

[0050] A compliance rate qualified threshold is set, and whether the nodes are qualified is judged by the compliance rate and the compliance rate qualified threshold.

[0051] If not, the current early warning level is outputted.

[0052] A correction module is configured to, if yes, establish an association model between the nodes, acquire association parameters of a plurality of first nodes through the association model, acquire the association parameters and the compliance rates of the first nodes corresponding to the association parameters, correct the compliance rates of the first nodes by the association parameters, output the corrected compliance rates of the first nodes, judge whether the corrected first nodes are qualified according to the corrected compliance rates of the first nodes and the compliance rate qualified threshold, and output the current early warning level after correction according to whether the corrected first nodes are qualified.

[0053] The application has at least the following advantages and beneficial effects:

[0054] The method or system provided by the application mainly comprises obtaining a current early warning level, judging whether to correct the compliance rate of the first node according to the current early warning level, if not, outputting the current early warning level; if yes, establishing a correlation model between nodes and nodes, obtaining a plurality of correlation parameters of the first node through the correlation model respectively; obtaining the correlation parameters and the compliance rate of the first node corresponding to the correlation parameters, and correcting the compliance rate of the first node through the correlation parameters. Through the above method, a correlation parameter is obtained by establishing a correlation model between nodes and nodes, the compliance rate of the qualified first node is corrected through the correlation parameter, so that all qualified first nodes can obtain a more objective compliance rate, and according to the corrected compliance rate, it is judged again whether the first node needs to be changed to an unqualified second node, thereby affecting the final early warning level, and outputting a more accurate and objective early warning signal. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0056] Fig. 1 It is a schematic diagram of the overall process of the application.

[0057] Fig. 2 It is a schematic diagram of the system structure of the application. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical scheme and advantages of the embodiments of the application more clear, the technical scheme in the embodiments of the application will be described clearly and completely below in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are some of the embodiments of the application, not all the embodiments. The components of the embodiments of the application described and shown in the drawings can be arranged and designed in various different configurations.

[0059] The terms "first", "second" and the like in the specification and claims of the application and the above drawings are used to distinguish similar objects, and do not necessarily describe a specific order or a logical sequence. The naming or numbering of the steps appearing in the present application does not mean that the steps in the method flow must be executed in the order indicated by the naming or numbering. The execution order of the named or numbered flow steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effect can be achieved.

[0060] Please refer to Figs. 1-2The application discloses a difference dynamic early warning method for catering material standardization, which comprises the following steps:

[0061] S101: setting a standardization reaching standard of food materials, acquiring a plurality of target parameters of a plurality of nodes in a whole catering process respectively, and obtaining a plurality of reaching rates of each node according to the target parameters and the standardization reaching standard;

[0062] The standardization reaching standard of food materials can be understood as the state or process of each food material reaching a qualified standard, and a person skilled in the art can set the standardization reaching standard according to specific conditions, for example, the storage temperature of fresh food materials, the setting temperature as the standardization reaching standard, the storage time of non-fresh food materials, the shelf life as the standardization reaching standard, and the like.

[0063] Secondly, there are a plurality of nodes in the whole catering process, for example, a purchasing node, a cleaning node, a cooking node, a service node, a storage node and the like, and a node can be associated with another node, and the association can cause the unqualified node to affect the qualified node, so that the present application is further processed.

[0064] S102: setting a reaching rate qualified threshold, judging whether the node is qualified or not by the reaching rate and the reaching rate qualified threshold, if there is an unqualified node, obtaining a current early warning level according to the number of the qualified first node and the number of the unqualified second node, and judging whether the reaching rate of the first node is modified or not according to the current early warning level, if not, outputting the current early warning level;

[0065] In the application, the early warning level can be divided into a plurality of levels according to specific conditions, and in a normal condition, only the early warning level of the non-highest early warning level is modified, and since the highest early warning level has no higher early warning level to replace, the highest early warning level has no any influence, so that the modification of the reaching rate of the first node is meaningless at this time.

[0066] S103: if yes, establishing an association model between the nodes, and obtaining a plurality of first node association parameters through the association model;

[0067] S104: acquiring the association parameters and the reaching rate of the first node corresponding to the association parameters, modifying the reaching rate of the first node through the association parameters, and outputting the modified reaching rate of the first node;

[0068] S105: judging whether the modified first node is qualified or not according to the modified reaching rate of the first node and the reaching rate qualified threshold, and outputting the current early warning level after modification according to whether the modified first node is qualified or not;

[0069] The early warning level is determined according to the first node quantity and the second node quantity, and if the first node becomes an unqualified second node, the final early warning level can be affected, resulting in a change from one early warning level to another early warning level, or the early warning level can remain unchanged within the threshold range of the original early warning level, and the specific condition can be further determined according to the set threshold of the early warning level.

[0070] S106: If there is no unqualified node, no early warning is performed.

[0071] The method and system provided by the application mainly include obtaining a current early warning level, determining whether to correct the passing rate of the first node according to the current early warning level, if not, outputting the current early warning level, if yes, establishing an association model between nodes, obtaining a plurality of association parameters of the first node through the association model, obtaining the association parameters and the passing rate of the first node corresponding to the association parameters, and correcting the passing rate of the first node through the association parameters. Through the above method, an association parameter is obtained by establishing an association model between nodes, the passing rate of the qualified first node is corrected through the association parameter, so that all qualified first nodes can obtain a more objective passing rate, and according to the corrected passing rate, it is determined again whether the first node needs to be changed to an unqualified second node, thereby affecting the final early warning level, and outputting a more accurate and objective early warning signal.

[0072] In an example embodiment of the application, the passing standard of the food material standardization includes:

[0073] A comparison index table is established, the comparison index table includes a plurality of nodes arranged in a first index layer, a food material owned by each node arranged in a second index layer under the plurality of nodes, and a plurality of passing standards of each food material arranged in a third index layer under the food material in the current node.

[0074] When a target parameter that does not meet a certain passing standard appears, the second index layer where the current target parameter is located is marked;

[0075] The number of marked second index layers and the number of unmarked second index layers in the same first index layer are counted respectively, and the passing rate of the plurality of first index layers is output.

[0076] For example, the first index layer includes a procurement node, a kitchen node and a storage node, and the procurement node is selected as an example, the second index layer of the procurement node includes apples, Chinese cabbage, green onions and the like, and the apples are selected as an example of the passing standard, and the third index layer of the apples includes whether the storage time is qualified, whether the storage temperature is qualified, whether the apple damage rate is over standard, and the like.

[0077] If one of the third index layers does not meet the standard, the second index layer is marked, so that the node located in the first index layer can be quickly output, and the unqualified second index layer can quickly obtain the pass rate of the node.

[0078] In an example embodiment of the present application, the current warning level is obtained according to the number of qualified first nodes and the number of unqualified second nodes, and includes:

[0079] The comprehensive unqualified rate of the current multiple nodes in the whole process is obtained according to the number of first nodes and the number of second nodes; the comprehensive unqualified rate and the basic parameter of the node are obtained respectively, the warning level judgment model is established through the pass rate of the first node, the pass rate of the second node and the basic parameter of the node; the judgment value is output through the warning level judgment model, different warning levels are divided respectively corresponding to the judgment threshold value, and the current warning level corresponding to the judgment threshold value is output according to the range of the judgment value and the judgment threshold value.

[0080] Specifically, the basic parameter of the node includes a first parameter of node cost, a second parameter of the number of nodes to be passed through by the node to the consumer, a third parameter of the number of food materials involved in the node, and a fourth parameter of the current cost of the food materials involved in the node.

[0081] The average values of the first parameter, the second parameter, the third parameter and the fourth parameter are obtained respectively, the number of each parameter greater than the average value in each node is obtained respectively, and the warning level judgment model is established.

[0082]

[0083] In the formula, R s is the judgment value, m is the total number of the first parameters greater than Q a , Q i is the i-th first parameter greater than Q a , Q a is the average value of the first parameter, k is the total number of the second parameters greater than N a , N k is the k-th second parameter greater than N a , N a is the average value of the second parameter, o is the total number of the third parameters greater than K a , K o is the o-th third parameter greater than K a , K a is the average value of the third parameter, u is the total number of the fourth parameters greater than G a , G u is the v-th fourth parameter greater than G a , and G aThe average value of the fourth parameter, E is the total number of nodes, H2 is the number of second nodes, and H1 is the number of first nodes.

[0084] In the present application, the node cost, the number of nodes to be passed through by the consumer, the number of food materials involved in the node, and the current cost of the food materials involved in the node are adopted. The advantages of selecting these four parameters are that the cost of the node reflects the proportion of the current node in the whole process; the number of nodes to be passed through by the consumer reflects the direct influence of the current node on the final consumer, for example, there are procurement, kitchen and inventory links. Therefore, the procurement and inventory links need to pass through the kitchen link to reach the consumer, so the number of nodes to be passed through is 1, and the smaller the number, the more important the node; the number of food materials involved in the node and the current cost of the food materials involved in the node both reflect the importance of the current node to specific food materials.

[0085] This multi-dimensional early warning mechanism not only breaks through the limitations of single indicator analysis, but also improves the accuracy of the final early warning result through the dynamic coupling relationship between parameters. Its advantages are the precision of risk prediction, the scientificity of management decision and the significant improvement of the resilience of the supply chain through data linkage.

[0086] Secondly, the judgment value output by the early warning level judgment model is divided into different early warning levels corresponding to different judgment thresholds.

[0087] The first early warning level, the second early warning level and the highest early warning level and the first judgment threshold, the second judgment threshold and the third judgment threshold corresponding to each early warning level are set;

[0088] The first judgment threshold, the second judgment threshold and the third judgment threshold satisfy:

[0089]

[0090] In the formula, R1 is the endpoint value of the first judgment threshold and the second judgment threshold, and R2 is the endpoint value of the second judgment threshold and the third judgment threshold;

[0091] The first judgment threshold is less than or equal to R1, the second judgment threshold is (R1, R2], and the third judgment threshold is greater than R2.

[0092] The early warning severity of the first early warning level, the second early warning level and the highest early warning level increases in turn.

[0093] In the present application, the meaning of the judgment value as a whole is a rejection rate, and the first judgment threshold value is in the range of (0, R1] in principle. Since 0 is not followed by a warning, in the present embodiment, the case where a warning has already been given is not considered, and therefore R1 is set to be equal to or less than R1.

[0094] Secondly, in the setting of the threshold value, the higher the number of first nodes, the higher the overall pass rate, and the smaller the difference between the end values of the first judgment threshold value and the second judgment threshold value. In the present embodiment, R2 is set to a constant value, and R1 gradually increases. In the case where the pass rate gradually increases, the range corresponding to the first warning level can be appropriately adjusted. Specifically, the specific numerical value of the first judgment threshold value or the second judgment threshold value can be set according to the specific circumstances of those skilled in the art.

[0095] One example embodiment of the present application further comprises:

[0096] The current warning level is received, and if the current warning level is the first warning level, an alarm signal is sent to the first terminal, if the current warning level is the second warning level, it is sent to the second terminal, and if the current warning level is the highest warning level, it is sent to the third terminal.

[0097] The management authority of the second terminal is greater than that of the first terminal, and the management authority of the third terminal is greater than that of the second terminal. A communication method for the first terminal, the second terminal and the third terminal is established, and the current warning level is adjusted according to the communication method.

[0098] It should be noted that the management authority refers to the functional management range between each terminal and terminal. In the present embodiment, three terminals with different management ranges are selected, and the terminal with greater management authority encompasses the terminal with smaller management authority.

[0099] For example, the department management terminal: has global data access rights, such as supply chain cost fluctuations and inventory turnover rates, and can set warning threshold rules.

[0100] Regional supervisor terminal: only views data within the jurisdiction, such as cold chain transportation loss rate in a certain region, and has temporary adjustment of some parameters, such as reducing the shelf life of seafood from 24 hours to 18 hours.

[0101] Store operator terminal: can only enter and view store data, such as daily food inspection records, and cannot modify system rules to avoid data distortion caused by misoperation at the grassroots level.

[0102] Specifically, the communication method for the first terminal, the second terminal and the third terminal comprises:

[0103] When the first terminal receives the early warning signal of the first early warning level, a first time threshold is started, if the early warning signal of the first early warning level cannot be eliminated within the first time threshold, the current early warning signal is replaced by the early warning signal of the second early warning level, and is sent to the second terminal, and a second time threshold is started;

[0104] If the early warning signal of the second early warning level cannot be eliminated within the second time threshold, the current early warning signal is replaced by the early warning signal of the highest early warning level, and is sent to the third terminal;

[0105] When the second terminal receives the early warning signal of the second early warning level, the second time threshold is started, if the early warning signal of the second early warning level cannot be eliminated within the second time threshold, the current early warning signal is replaced by the early warning signal of the highest early warning level, and is sent to the third terminal.

[0106] Through the above method, the relationship among the three terminals is constrained, if the early warning cannot be eliminated within the appropriate time threshold, the early warning signal at this time is changed to the early warning signal of the next higher level, and is sent to the different terminal, and finally the purpose of timely processing the early warning situation is achieved.

[0107] Secondly, whether the first node's compliance rate is modified according to the current early warning level includes:

[0108] If the current early warning level is the first early warning level or the second early warning level, the early warning level modification is performed;

[0109] If the current early warning level is the highest early warning level, the early warning level modification is not performed.

[0110] In an example embodiment of the present application, the association model between the nodes is established, and includes:

[0111]

[0112] The first node's compliance rate is modified through the association parameter, and includes:

[0113]

[0114] In the formula, W j is the association parameter of the jth first node, alpha b,j is the number of second nodes directly associated with the jth first node, alpha j is the number of all nodes directly associated with the first node, eta z,j is the compliance rate of the jth modified first node, eta j is the compliance rate of the jth first node.

[0115] In the embodiment, the unqualified second node can have a great impact on the qualified first node, for example, the unqualified inventory node directly affects the kitchen node, so the embodiment considers the number of second nodes directly associated with the first node to re-evaluate the qualified first node. Secondly, the definition of direct association in the embodiment is the next or previous target node that the current node must pass through, so the two nodes are directly associated.

[0116] For example, there are currently procurement nodes, cleaning nodes, inventory nodes, financial nodes, cooking nodes, and inventory nodes. The nodes directly associated with the cooking node are the cleaning node, the inventory node, and the financial node. Then, judge whether each node is a first node or a second node, and then correct the first node compliance rate. As for which nodes are considered to have direct association, the specific data of the relationship after setting can be obtained according to the specific situation of the catering personnel, and the specific result can be obtained through the method.

[0117] A difference dynamic early warning system for catering material standardization, comprising:

[0118] Setting a standardization compliance benchmark, obtaining a plurality of target parameters of a plurality of nodes in the whole catering process, and obtaining a plurality of compliance rates of each node according to the target parameters and the compliance benchmark;

[0119] Setting a compliance rate threshold, judging whether the node is qualified by the compliance rate and the compliance rate threshold, if there is an unqualified node, then according to the number of qualified first nodes and the number of unqualified second nodes, obtaining the current early warning level, and judging whether to correct the compliance rate of the first node according to the current early warning level, if not, output the current early warning level;

[0120] If yes, an association model between nodes is established, and the association parameters of a plurality of first nodes are obtained through the association model;

[0121] Obtaining the association parameters and the compliance rate of the first node corresponding to the association parameters, correcting the compliance rate of the first node through the association parameters, and outputting the corrected compliance rate of the first node;

[0122] According to the corrected compliance rate of the first node and the compliance rate threshold, judging whether the corrected first node is qualified, and outputting the corrected current early warning level according to whether the corrected first node is qualified;

[0123] If there is no unqualified node, no early warning is made.

[0124] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0125] When the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. The computer software product stored in a storage medium includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of each embodiment of the present application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0126] The above is only the preferred embodiment of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for dynamically warning differences in food material standardization, characterized in that, The method comprises the following steps: Setting a standardization standard for food materials, obtaining a plurality of target parameters of a plurality of nodes in the whole process of catering, and obtaining a plurality of standard rates of each node according to the target parameters and the standardization standard; Setting a standard rate threshold, judging whether the node is qualified by the standard rate and the standard rate threshold, if there is an unqualified node, obtaining the current warning level according to the number of qualified first nodes and the number of unqualified second nodes, and judging whether to correct the standard rate of the first node according to the current warning level, if not, outputting the current warning level; If yes, an association model between nodes is established, and the association parameters of a plurality of first nodes are obtained through the association model; Obtaining the association parameters and the standard rate of the first node corresponding to the association parameters, correcting the standard rate of the first node by the association parameters, and outputting the corrected standard rate of the first node; According to the corrected standard rate of the first node and the standard rate threshold, judging whether the corrected first node is qualified, and outputting the current warning level after correction according to whether the corrected first node is qualified; If there is no unqualified node, no warning is made; The setting of the standardization standard for food materials comprises: Establishing a reference index table, the reference index table comprises a plurality of nodes arranged in a first index layer, food materials owned by each node arranged in a second index layer under the plurality of nodes, and a plurality of standardization standards of each food material arranged in a third index layer under the food materials in the current node; When a target parameter that does not meet a certain standardization standard appears, the second index layer where the current target parameter is located is marked; The number of marked second index layers and the number of unmarked second index layers in the same first index layer are counted respectively, and the standard rate of a plurality of first index layers is outputted; The current warning level is obtained according to the number of first nodes and the number of second nodes, which comprises: Obtaining the comprehensive unqualified rate of the plurality of nodes in the whole process according to the number of first nodes and the number of second nodes; Obtaining the comprehensive unqualified rate and the basic parameters of the node respectively, and establishing a warning level judgment model; Outputting a judgment value through the warning level judgment model, dividing different judgment thresholds corresponding to a plurality of warning levels, and outputting the warning level corresponding to the current judgment threshold according to the judgment value and the range of the judgment threshold; The basic parameters of the node include a first parameter of node cost, a second parameter of the number of nodes to be passed through by the consumer, a third parameter of the number of food material types involved in the node, and a fourth parameter of the current food material cost involved in the node; The average values of the first parameter, the second parameter, the third parameter and the fourth parameter are obtained respectively, the number of each parameter greater than the average value in each node is obtained respectively, and a warning level judgment model is established; In the formula, For the judgment value, greater than The total number of the first parameters, For the i-th greater than The first parameter, The average value of the first parameter. greater than The total number of the second parameter, For the kth greater than The second parameter, The average value of the second parameter. greater than The total number of the third parameter, For the o-th greater than The third parameter, The average value of the third parameter. greater than The total number of fourth parameters, For the vth greater than The fourth parameter, The average value of the fourth parameter. The total number of nodes. The number of second nodes. The number of first nodes; The establishment of the association model between nodes comprises: The correction of the standard rate of the first node by the association parameters comprises: wherein is a correlation parameter for the jth first node, is the number of second nodes directly associated with the jth first node, is the number of all nodes directly associated with the first node, is the compliance rate of the jth first node after correction, is the compliance rate of the jth first node.

2. The method of claim 1, wherein the method comprises: The output of the judgment value through the warning level judgment model and the division of different judgment thresholds corresponding to a plurality of warning levels comprise: The first warning level, the second warning level and the highest warning level are set, and the first judgment threshold, the second judgment threshold and the third judgment threshold corresponding to each warning level are set; The first judgment threshold, the second judgment threshold and the third judgment threshold satisfy: In the formula, is an end value of the first judgment threshold and the second judgment threshold, is an end value of the second judgment threshold and the third judgment threshold. The first judgment threshold is less than or equal to , the second judgment threshold is , and the third judgment threshold is greater than ; The warning severity of the first warning level, the second warning level and the highest warning level increases in turn.

3. The method of claim 2, wherein the method further comprises: Further comprising: Receiving the current warning level, if the current warning level is the first warning level, sending an alarm signal to the first terminal, if the current warning level is the second warning level, sending to the second terminal, if the current warning level is the highest warning level, sending to the third terminal; The management authority of the second terminal is greater than that of the first terminal, and the management authority of the third terminal is greater than that of the second terminal; A communication method of the first terminal, the second terminal and the third terminal is established, and the current warning level is adjusted according to the communication method.

4. The method of claim 3, wherein the method further comprises: The communication method of the first terminal, the second terminal and the third terminal comprises: When the first terminal receives the first warning level warning signal, the first time threshold is started, if the first warning level warning signal cannot be eliminated within the first time threshold, the current warning signal is replaced by the second warning level signal, sent to the second terminal, and the second time threshold is started; If the second warning level warning signal cannot be eliminated within the second time threshold, the current warning signal is replaced by the highest warning level signal, sent to the third terminal; When the second terminal receives the second warning level warning signal, the second time threshold is started, if the second warning level warning signal cannot be eliminated within the second time threshold, the current warning signal is replaced by the highest warning level, sent to the third terminal.

5. The method of claim 4, wherein the method further comprises: The current warning level is used to judge whether to correct the first node's compliance rate, comprising: If the current warning level is the first warning level or the second warning level, the warning level correction is performed; If the current warning level is the highest warning level, the warning level correction is not performed.

6. A difference dynamic early warning system for catering food material standardization, characterized in that, Comprising: The warning module is configured to set the standardization of food materials, obtain a plurality of target parameters of a plurality of nodes in the whole process of catering, and obtain a plurality of compliance rates of each node according to the target parameters and the compliance benchmark; A compliance rate threshold is set, and whether the node is qualified is judged by the compliance rate and the compliance rate threshold, if there is an unqualified node, the current warning level is obtained according to the number of qualified first nodes and the number of unqualified second nodes, and whether to correct the compliance rate of the first node is judged according to the current warning level, if not, the current warning level is output; The correction module is configured to if yes, an association model between nodes is established, and the association parameters of a plurality of first nodes are obtained through the association model; the association parameters and the compliance rate of the first node corresponding to the association parameters are obtained, the compliance rate of the first node is corrected through the association parameters, and the corrected compliance rate of the first node is output; According to the corrected compliance rate of the first node and the compliance rate threshold, whether the corrected first node is qualified is judged, and the current warning level after correction is output according to whether the corrected first node is qualified. If there is no unqualified node, no pre-warning is made; The main control module is connected with the pre-warning module and the correction module, and is used for executing the difference dynamic pre-warning method for the catering food material standardization according to any one of claims 1-5.

Images