Menu automatic adjustment method and system based on smart canteen and medium

Abstract

The invention discloses an automatic menu adjustment method and system based on an intelligent canteen and a medium, and the method comprises the steps: screening out an initial dish array from a menu according to a set automatic meal arrangement recommendation rule in combination with recommendation parameters; arranging dishes except for a preset type in the initial dish array in a single row to obtain a first dish array, arranging other dishes according to the sequence of the preset type, arranging the same type of dishes in a descending order according to the weight to obtain a second dish array, and calculating the weight and data; calculating the total weight of planned cooking dishes and the planned average cooking pot number; according to the weight, the data, the planned average cooking pot number and the total cooking dish weight, the overweight is obtained; comparing the overweight with the single-pot weight of the ordered dishes, and if the overweight is greater than the single-pot weight, subtracting one from the planned average cooking pot number; skipping if the current dish pot number is equal to one; according to the steps, a recommendation menu is automatically generated in combination with a specified generation condition; the method has the advantage that the optimal dish matching scheme is automatically generated.

Description

Technical Field

[0001] The present invention relates to the technical field of smart canteens, and in particular to a method, system and medium for automatic adjustment of menus based on a smart canteen. Background Art

[0002] With the launch of "smart restaurants", more and more companies no longer use the traditional group dining operation model, but use advanced technology to replace manpower, reduce food waste and reduce costs, and improve customer satisfaction. For example, the traditional meal scheduling requires canteen operators to prepare the menu for the next week in advance. Due to insufficient data support, canteen operators are not clear about the specific conditions of customers' tastes, appetite, consumption capacity, etc., and have to rack their brains to think about the combination of meat and vegetables, the portion size of dishes, and the repetition rate of the menu. This is not only labor-intensive, but also may not meet customer needs. It may also lead to customer loss and food waste, causing certain losses to the restaurant. Summary of the invention

[0003] In view of the defects in the prior art, the present invention provides a method, system, terminal and medium for automatic adjustment of menu based on a smart canteen to overcome the defects in the prior art.

[0004] In a first aspect, the present invention provides a method for automatically adjusting a menu based on a smart canteen, comprising the following steps:

[0005] Predefine automatic meal arrangement recommendation rules; wherein the automatic meal arrangement recommendation rules include corresponding dish classification, cooking equipment used, dish quantity and meat-vegetarian ratio;

[0006] According to the set automatic meal arrangement recommendation rules and in combination with the recommendation parameters, an initial array of dishes that meet the dish type is randomly selected from the current canteen's store menu; wherein the recommendation parameters include the number of diners and the average meal size per person;

[0007] List the dishes other than the preset types in the initial dish array separately to obtain a first dish array, and define the corresponding fixed number of pots as one pot;

[0008] Arrange the remaining dishes in the initial dish array in the order of preset types, and arrange the same type in descending order of weight to obtain a second dish array, and calculate its weight and data;

[0009] Calculate the total weight of the planned cooking dishes based on the number of diners and the average meal size per person;

[0010] Calculate the planned average number of cooking pots by using the total weight of the planned cooking dishes and the weight and data;

[0011] The excess weight is calculated by using the weight and data, the planned average number of cooking pots and the total weight of the planned cooking dishes;

[0012] Compare the overweight weight with the weight of a single pot of the sorted dishes in the second dish array one by one, starting from the first dish, if the overweight weight is greater than the weight of a single pot, then reduce the average number of cooking pots in this plan by one; if the overweight weight is less than the weight of a single pot, then continue to compare with the second dish until the last one; if all are less than the weight of a single pot, then end and exit;

[0013] When executing the deduction logic, if the current planned average number of cooking pots is already equal to one, it will be skipped directly; according to the above steps, combined with the specified generation conditions, the final recommended menu is automatically generated.

[0014] In a second aspect, an embodiment of the present invention provides a menu automatic adjustment system based on a smart canteen, comprising: a definition module, a screening and processing module, a calculation module, a judgment module and a recipe generation module;

[0015] The definition module is used to predefine automatic meal arrangement recommendation rules; wherein the automatic meal arrangement recommendation rules include corresponding dish classification, cooking equipment used, dish quantity and meat-vegetarian ratio;

[0016] The screening processing module is used for:

[0017] According to the set automatic meal arrangement recommendation rules and in combination with the recommendation parameters, an initial array of dishes that meet the dish type is randomly selected from the current canteen's store menu; wherein the recommendation parameters include the number of diners and the average meal size per person;

[0018] List the dishes other than the preset types in the initial dish array separately to obtain a first dish array, and define the corresponding fixed number of pots as one pot;

[0019] Arrange the remaining dishes in the initial dish array in the order of preset types, and arrange the same type in descending order of weight to obtain a second dish array, and calculate its weight and data;

[0020] The calculation module is used for:

[0021] Calculate the total weight of the planned cooking dishes based on the number of diners and the average meal size per person;

[0022] Calculate the planned average number of cooking pots by using the total weight of the planned cooking dishes and the weight and data;

[0023] The excess weight is calculated by using the weight and data, the planned average number of cooking pots and the total weight of the planned cooking dishes;

[0024] The judgment module is used to compare the overweight weight with the weight of a single pot of the sorted dishes in the second dish array one by one, starting from the first dish, if the overweight weight is greater than the weight of a single pot, then the average number of cooking pots in this plan is reduced by one; if the overweight weight is less than the weight of a single pot, then continue to compare with the second dish until the last one; if all are less than the weight of a single pot, then end and exit;

[0025] When the recipe generation module is used to execute the deduction logic, if the current planned average number of cooking pots is equal to one, it is directly skipped; according to the above steps, combined with the specified generation conditions, the final recommended menu is automatically generated.

[0026] In a third aspect, an embodiment of the present invention provides an intelligent terminal, comprising a processor, an input device, an output device and a memory, wherein the processor is connected to the input device, the output device and the memory respectively, the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the method described in the first aspect above.

[0027] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method described in the first aspect above.

[0028] Beneficial effects of the present invention:

[0029] The embodiment of the present invention randomly selects an initial dish array that meets the dish type according to the set automatic meal scheduling recommendation rule and in combination with the recommendation parameters, and then lists the dishes other than the preset type in the selected initial dish array to obtain a first dish array, and arranges the remaining dishes in the order of the preset types, and arranges the same type in descending order of weight to obtain a second dish array, and calculates its weight and data; at the same time, calculates the total weight of the planned cooking dishes, the planned average number of cooking pots and the overweight weight, and then executes the deduction logic according to the overweight weight and the weight of a single pot; finally, according to the above steps, automatically generates a final recommended menu under the specified generation conditions; thereby automatically generating the optimal dish matching plan for the canteen operator, helping the canteen operator to solve the high-frequency and headache-inducing meal scheduling problem, while also reducing the waste of food materials, better controlling costs and budgets, and improving both the canteen service efficiency and the customer's dining experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0031] Figure 1 A flowchart of a method for automatically adjusting menus based on a smart canteen provided in a first embodiment of the present invention is shown;

[0032] Figure 2 A schematic diagram showing the structure of a menu automatic adjustment system based on a smart canteen provided by a second embodiment of the present invention;

[0033] Figure 3 A schematic diagram of the structure of an intelligent terminal provided by the third embodiment of the present invention is shown. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0036] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0037] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0038] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0039] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the invention belongs.

[0040] like Figure 1 As shown, a menu automatic adjustment method based on a smart canteen provided by the first embodiment of the present invention is shown, comprising the following steps:

[0041] S101, pre-defining automatic meal arrangement recommendation rules; wherein the automatic meal arrangement recommendation rules include corresponding dish classification, cooking equipment to be used, number of dishes and ratio of meat and vegetables;

[0042] S102, randomly selecting an initial array of dishes that meet the dish type from the current canteen's store menu according to the set automatic meal recommendation rule and in combination with recommendation parameters; wherein the recommendation parameters include the number of diners and the average meal size per person;

[0043] S103, listing dishes other than the preset types in the initial dish array separately to obtain a first dish array, and defining the corresponding fixed number of pots as one pot;

[0044] S104, arranging the remaining dishes in the initial dish array in the order of preset types, and arranging the same type in descending order of weight, to obtain a second dish array, and calculating its weight and data;

[0045] S105, calculating the total weight of the planned cooking dishes according to the number of diners and the average meal size per person;

[0046] S106, calculating a planned average number of cooking pots by using the planned total weight of the dishes to be cooked and the weight and data;

[0047] S107, calculating the overweight weight by using the weight and data, the planned average number of cooking pots and the planned total weight of the dishes to be cooked;

[0048] S108, comparing the overweight weight with the weight of a single pot of the ordered dishes in the second dish array one by one, starting from the first dish, if the overweight weight is greater than the weight of a single pot, then the average number of cooking pots in this plan is reduced by one; if the overweight weight is less than the weight of a single pot, then continue to compare with the second dish until the last one; if all are less than the weight of a single pot, then end and exit;

[0049] S109, when executing the deduction logic, if the current planned average number of cooking pots is equal to one, it is skipped directly; according to the above steps, combined with the specified generation conditions, the final recommended menu is automatically generated.

[0050] In this embodiment, the above method can be deployed in a smart terminal, a client, and a server, and is not limited here.

[0051] When scheduling meals, use the pre-defined automatic meal recommendation rules, select the dish category and cooking equipment, and then enter the quantity and proportion of each type of dish to ensure that the sum of the proportions of each type of dish is equal to 100; it should be noted that each store also has a pre-built corresponding menu, including a variety of types of dishes.

[0052] In this embodiment, the per capita meal amount (the default per capita is 400g, which can be customized); the recommended parameters are input through an input device or collected through an Internet of Things device; for example, when scheduling meals, you only need to fill in the number of diners and the per capita portion, and then combine the configured automatic meal scheduling recommendation rules to automatically and randomly select dishes that meet the dish type from the current canteen store menu and define them as the initial dish array.

[0053] The preset types include semi-meat dishes, small meat dishes, large meat dishes, vegetarian dishes, cold dishes and coarse grains.

[0054] That is, the dishes other than semi-meat dishes, small meat dishes, large meat dishes, vegetarian dishes, cold dishes, and coarse grains in the initial dish array are listed separately to obtain the first dish array, which is recorded as R1; here, the dishes such as desserts and snacks in the initial dish array are defined and defaulted to one pot;

[0055] Then, the remaining dishes in the initial dish array are arranged in the order of semi-meat dishes, small meat dishes, large meat dishes, vegetarian dishes, cold dishes, and coarse grains, and the dishes of the same type are arranged in descending order of weight, to obtain the second dish array, which is recorded as R2; at the same time, the data of the sum of their weights is calculated and recorded as T2;

[0056] Then, according to the number of diners * average number of grams per person (average meal amount), the total weight of the planned cooking dishes is obtained, recorded as T3;

[0057] Then T3 / T2 is divided to obtain the planned average number of cooking pots, which is defined as G1. When calculating the planned average number of cooking pots, the calculation result is rounded up.

[0058] Use T2*G1-T3 to get the super-heavy weight T4;

[0059] Then compare T4 with the weight of each pot of the dishes sorted in R2 one by one; starting from the first dish, if T4> the weight of each pot, then reduce the planned average number of cooking pots by 1; if T4< the weight of each pot, then continue to compare with the second dish until the last one; if all are less than the weight of each pot, then exit;

[0060] The weight of a single pot is the weight of the dish obtained during research and development; that is, how heavy the dish is after cooking; different dishes correspond to different single pot weights;

[0061] It should be noted that when executing the deduction logic, if the current planned average number of cooking pots is equal to one, it will be skipped directly; according to the above steps, the optimal dish combination plan is automatically generated under the specified conditions; if the calculated weight is less than the cooking weight of a single pot (single pot weight), it will be cooked as one pot by default and no further deductions will be made.

[0062] In this embodiment, the specified generation condition is that the calculated dish cannot be smaller than one pot; that is, the calculated dish cannot be smaller than one pot, and being smaller than one pot means that it cannot be cooked;

[0063] The number of pots required to cook a dish is calculated through different dimensions, and a cooking menu is finally generated.

[0064] When applied, for a single canteen, based on the pre-defined automatic meal recommendation rules, the number of people eating at each meal, the average amount of grams eaten by each person, the total number of dishes that need to be arranged, and the proportion of meat and vegetarian dishes are calculated based on this data. Then, the total weight that should be cooked is calculated, and then the number of grams that should be allocated to each dish is divided by the weight of the dish on the recipe to get the number of cooking pots.

[0065] The above technical scheme, by using the automatic meal scheduling recommendation rules that have been set and combining the recommendation parameters, first randomly screens out an initial dish array that meets the dish type, then lists the dishes other than the preset type in the screened initial dish array to obtain a first dish array, and arranges the remaining dishes in the order of the preset types, and arranges the same type in descending order of weight to obtain a second dish array, and calculates its weight and data; at the same time, calculates the total weight of the planned cooking dishes, the planned average number of cooking pots, and the overweight weight, and then executes the deduction logic based on the overweight weight and the weight of a single pot; finally, according to the above steps, automatically generates a recommended menu under the specified generation conditions; thereby automatically generating the optimal dish combination plan for the canteen operator, helping the canteen operator to solve the high-frequency and headache-inducing meal scheduling problem, while also reducing the waste of food, better controlling costs and budgets, and improving both the canteen service efficiency and the customer's dining experience.

[0066] When applied, in another embodiment, based on the above technical solution, the method further includes an optimization step, specifically:

[0067] The menu is optimized based on cooking methods and seasonal factors to make it more in line with current actual conditions.

[0068] In the above method embodiment, a method for automatically adjusting menus based on a smart canteen is provided. Correspondingly, the present application also provides a system for automatically adjusting menus based on a smart canteen. Figure 2 , which is a structural diagram of a menu automatic adjustment system based on a smart canteen provided by the second embodiment of the present invention. Since the system embodiment is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The system embodiment described below is only illustrative.

[0069] like Figure 2 As shown, a schematic diagram of the structure of a menu automatic adjustment system based on a smart canteen provided by another embodiment of the present invention is shown, the system includes: a definition module, a screening and processing module, a calculation module, a judgment module and a recipe generation module;

[0070] The definition module is used to predefine automatic meal arrangement recommendation rules; wherein the automatic meal arrangement recommendation rules include corresponding dish classification, cooking equipment used, dish quantity and meat-vegetarian ratio;

[0071] The screening processing module is used for:

[0072] According to the set automatic meal arrangement recommendation rules and in combination with the recommendation parameters, an initial array of dishes that meet the dish type is randomly selected from the current canteen's store menu; wherein the recommendation parameters include the number of diners and the average meal size per person;

[0073] List the dishes other than the preset types in the initial dish array separately to obtain a first dish array, and define a fixed number of pots as one pot;

[0074] Arrange the remaining dishes in the initial dish array in the order of preset types, and arrange the same type in descending order of weight to obtain a second dish array, and calculate its weight and data;

[0075] The calculation module is used for:

[0076] Calculate the total weight of the planned cooking dishes based on the number of diners and the average meal size per person;

[0077] Calculate the planned average number of cooking pots by using the total weight of the planned cooking dishes and the weight and data;

[0078] The excess weight is calculated by using the weight and data, the planned average number of cooking pots and the total weight of the planned cooking dishes;

[0079] The judgment module is used to compare the overweight weight with the weight of a single pot of the sorted dishes in the second dish array one by one, starting from the first dish, if the overweight weight is greater than the weight of a single pot, then the average number of cooking pots in this plan is reduced by one; if the overweight weight is less than the weight of a single pot, then continue to compare with the second dish until the last one; if all are less than the weight of a single pot, then end and exit;

[0080] When the recipe generation module is used to execute the deduction logic, if the current planned average number of cooking pots is equal to one, it is directly skipped; according to the above steps, combined with the specified generation conditions, the final recommended menu is automatically generated.

[0081] In this embodiment, the specified generation condition is that the calculated dish cannot be smaller than one pot.

[0082] In this embodiment, the preset types include semi-meat, small meat, large meat, vegetarian, cold dishes and coarse grains; when calculating the planned average number of cooking pots, the calculation result is rounded up.

[0083] An automatic menu adjustment system based on a smart canteen provided in an embodiment of the present invention and an automatic menu adjustment method based on a smart canteen provided in the above-mentioned first embodiment are based on the same inventive concept and have the same beneficial effects, which will not be repeated here.

[0084] like Figure 3As shown, a structural schematic diagram of an intelligent terminal provided in the third embodiment of the present invention is shown, the terminal includes a processor, an input device, an output device and a memory, the processor is connected to the input device, the output device and the memory respectively, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described in the above first embodiment.

[0085] It should be understood that in the embodiments of the present invention, the processor referred to may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0086] Input devices may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and output devices may include a display (LCD, etc.), a speaker, etc.

[0087] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0088] In a specific implementation, the processor, input device, and output device described in the embodiments of the present invention may execute the implementation described in the method embodiment provided in the embodiments of the present invention, or may execute the implementation described in the system embodiment described in the embodiments of the present invention, which will not be described in detail here.

[0089] The present invention further provides an embodiment of a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method described in the above embodiment.

[0090] The computer-readable storage medium may be an internal storage unit of the terminal described in the foregoing embodiments, such as a hard disk or memory of the terminal. The computer-readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit of the terminal and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0091] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the terminals and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0093] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A menu automatic adjustment method based on a smart canteen, characterized in that: The following steps are involved: Predefine automatic meal arrangement recommendation rules; wherein the automatic meal arrangement recommendation rules include corresponding dish classification, cooking equipment used, dish quantity and meat-vegetarian ratio; According to the set automatic meal arrangement recommendation rules and in combination with the recommendation parameters, an initial array of dishes that meet the dish type is randomly selected from the current canteen's store menu; wherein the recommendation parameters include the number of diners and the average meal size per person; List the dishes other than the preset types in the initial dish array separately to obtain a first dish array, and define the corresponding fixed number of pots as one pot; Arrange the remaining dishes in the initial dish array in the order of preset types, and arrange the same type in descending order of weight to obtain a second dish array, and calculate its weight and data; Calculate the total weight of the planned cooking dishes based on the number of diners and the average meal size per person; Calculate the planned average number of cooking pots by using the total weight of the planned cooking dishes and the weight and data; The excess weight is calculated by using the weight and data, the planned average number of cooking pots and the total weight of the planned cooking dishes; Compare the overweight weight with the weight of a single pot of the sorted dishes in the second dish array one by one, starting from the first dish, if the overweight weight is greater than the weight of a single pot, then reduce the average number of cooking pots in this plan by one; if the overweight weight is less than the weight of a single pot, then continue to compare with the second dish until the last one; if all are less than the weight of a single pot, then end and exit; When executing the deduction logic, if the current planned average number of cooking pots is already equal to one, it will be skipped directly; according to the above steps, combined with the specified generation conditions, the final recommended menu is automatically generated.

2. The method according to claim 1, characterized in that The specified generation condition is that the calculated dish cannot be smaller than one pot.

3. The method according to claim 2, characterized in that The recommended parameters are input through an input device or collected through an Internet of Things device.

4. The method according to claim 2, characterized in that When calculating the planned average number of cooking pots, the calculation result is rounded up.

5. The method according to claim 1, characterized in that The preset types include semi-meat dishes, small meat dishes, large meat dishes, vegetarian dishes, cold dishes and coarse grains.

6. A menu automatic adjustment system based on a smart canteen, characterized in that: include: Definition module, screening and processing module, calculation module, judgment module and recipe generation module; The definition module is used to predefine automatic meal arrangement recommendation rules; wherein the automatic meal arrangement recommendation rules include corresponding dish classification, cooking equipment used, dish quantity and meat-vegetarian ratio; The screening processing module is used for: According to the set automatic meal arrangement recommendation rules and in combination with the recommendation parameters, an initial array of dishes that meet the dish type is randomly selected from the current canteen's store menu; wherein the recommendation parameters include the number of diners and the average meal size per person; List the dishes other than the preset types in the initial dish array separately to obtain a first dish array, and define the corresponding fixed number of pots as one pot; Arrange the remaining dishes in the initial dish array in the order of preset types, and arrange the same type in descending order of weight to obtain a second dish array, and calculate its weight and data; The calculation module is used for: Calculate the total weight of the planned cooking dishes based on the number of diners and the average meal size per person; Calculate the planned average number of cooking pots by using the total weight of the planned cooking dishes and the weight and data; The excess weight is calculated by using the weight and data, the planned average number of cooking pots and the total weight of the planned cooking dishes; The judgment module is used to compare the overweight weight with the weight of a single pot of the sorted dishes in the second dish array one by one, starting from the first dish, if the overweight weight is greater than the weight of a single pot, then the average number of cooking pots in this plan is reduced by one; if the overweight weight is less than the weight of a single pot, then continue to compare with the second dish until the last one; if all are less than the weight of a single pot, then end and exit; When the recipe generation module is used to execute the deduction logic, if the current planned average number of cooking pots is equal to one, it is directly skipped; according to the above steps, combined with the specified generation conditions, the final recommended menu is automatically generated.

7. The system according to claim 6, characterized in that The specified generation condition is that the calculated dish cannot be smaller than one pot.

8. The system according to claim 7, characterized in that When calculating the planned average number of cooking pots, the calculation result is rounded up.

9. An intelligent terminal, comprising a processor, an input device, an output device and a memory, wherein the processor is connected to the input device, the output device and the memory respectively, and the memory is used to store a computer program, wherein the computer program comprises program instructions, and wherein: The processor is configured to call the program instructions to execute the method according to any one of claims 1-5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 5.

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