CN111326233A - Conditional intelligent menu plan generation method, system, equipment and storage medium - Google Patents
Conditional intelligent menu plan generation method, system, equipment and storage medium Download PDFInfo
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- CN111326233A CN111326233A CN202010084466.XA CN202010084466A CN111326233A CN 111326233 A CN111326233 A CN 111326233A CN 202010084466 A CN202010084466 A CN 202010084466A CN 111326233 A CN111326233 A CN 111326233A
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- 238000000034 method Methods 0.000 title claims abstract description 46
- 239000000463 material Substances 0.000 claims abstract description 30
- 235000013305 food Nutrition 0.000 claims abstract description 29
- 238000010411 cooking Methods 0.000 claims abstract description 14
- 235000016709 nutrition Nutrition 0.000 claims abstract description 12
- 230000035764 nutrition Effects 0.000 claims abstract description 8
- 238000004590 computer program Methods 0.000 claims description 6
- 235000021190 leftovers Nutrition 0.000 claims description 5
- 239000002994 raw material Substances 0.000 claims description 5
- 235000021067 refined food Nutrition 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 4
- 235000012054 meals Nutrition 0.000 claims description 4
- 238000013077 scoring method Methods 0.000 claims description 4
- 239000010794 food waste Substances 0.000 claims description 2
- 230000000007 visual effect Effects 0.000 claims description 2
- 238000007726 management method Methods 0.000 description 23
- 235000021186 dishes Nutrition 0.000 description 14
- 235000015277 pork Nutrition 0.000 description 11
- 235000013372 meat Nutrition 0.000 description 5
- 150000001720 carbohydrates Chemical class 0.000 description 4
- 102000004169 proteins and genes Human genes 0.000 description 4
- 108090000623 proteins and genes Proteins 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 235000009508 confectionery Nutrition 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 235000013555 soy sauce Nutrition 0.000 description 2
- 235000013311 vegetables Nutrition 0.000 description 2
- 241000251468 Actinopterygii Species 0.000 description 1
- 235000017166 Bambusa arundinacea Nutrition 0.000 description 1
- 235000017491 Bambusa tulda Nutrition 0.000 description 1
- 244000082204 Phyllostachys viridis Species 0.000 description 1
- 235000015334 Phyllostachys viridis Nutrition 0.000 description 1
- 244000061456 Solanum tuberosum Species 0.000 description 1
- 235000002595 Solanum tuberosum Nutrition 0.000 description 1
- 239000011425 bamboo Substances 0.000 description 1
- 235000021152 breakfast Nutrition 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 235000021443 coca cola Nutrition 0.000 description 1
- 230000003828 downregulation Effects 0.000 description 1
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- 235000012041 food component Nutrition 0.000 description 1
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- 238000012545 processing Methods 0.000 description 1
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- 235000019605 sweet taste sensations Nutrition 0.000 description 1
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- 239000002699 waste material Substances 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0283—Price estimation or determination
Abstract
The invention provides a conditional intelligent menu plan generation method, which comprises the following steps: the method comprises the steps that menu information required by generating a menu plan is stored in advance, wherein the menu information comprises basic data, food material information and item information; setting limiting conditions according to requirements of different items to restrict the generation of a menu, wherein the limiting conditions comprise food materials, nutrition, taste, color, cooking method and gross profit rate; calculating the matching degree of the menu plan filled by the existing items of the user and the set limiting conditions; if the matching is not the case, the menu plan is generated, and if the matching is not the case, automatic or manual adjustment is performed. The invention can automatically generate the menu plan suitable for the user according to various types of limiting conditions and parameter data set by the user, so that the user can conveniently, quickly and accurately complete the work of making the menu plan.
Description
Technical Field
The invention belongs to the field of intelligent menu plans, and particularly relates to a conditional intelligent menu plan generation method, a conditional intelligent menu plan generation system, a conditional intelligent menu plan generation device and a storage medium.
Background
With the development of economy and the improvement of the living standard of people, the demand of people for safe food is continuously increased, and the requirement on the food safety is higher and higher. The large number of catering companies appear like bamboo shoots in spring after rain, and the modern enterprise management system is urgently needed to be introduced into the traditional group food management industry, so that the management of the catering industry is promoted to be gradually improved.
On the premise of insufficient informatization of the current catering industry, a menu plan for daily delivery can be only compiled manually through experience, a large amount of time and energy of relevant workers need to be consumed, and whether the compiled menu is appropriate or not is also testified.
However, in this case, the generated recipe plan often has problems, such as forbidding food, meat and vegetable matching, cooking modes, holiday features, and the like, which need to be taken into consideration, and brings much trouble and loss to companies and clients. Therefore, how to intelligently generate a reasonable menu plan becomes a technical problem which needs to be solved urgently in the informatization development of the catering industry in the existing work flow.
Disclosure of Invention
In view of this, the present invention is directed to a method for generating a conditional intelligent recipe plan, which can automatically generate a recipe plan suitable for a user according to various types of limiting conditions and parameter data set by the user, so that the user can conveniently, quickly and accurately complete the work of making the recipe plan.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a method of conditional intelligent recipe plan generation, the method comprising:
s1: the method comprises the steps that menu information required by generating a menu plan is stored in advance, wherein the menu information comprises basic data, food material information and item information;
s2: setting limiting conditions according to requirements of different items to restrict the generation of a menu, wherein the limiting conditions comprise food materials, nutrition, taste, color, cooking method and gross profit rate;
s3: calculating the matching degree of the menu plan filled by the existing items of the user and the set limiting conditions;
and S4, if the two are matched, generating a menu plan, and if the two are not matched, carrying out automatic or manual adjustment.
Further, in step S1, the basic data includes meal management, unit management, cooking method, dish taste, dish color, and shape management; the food material information includes: category management, food material management, and processed food material management; the item information includes: management of dishes and management of commodities.
Further, step S3 includes using an item scoring system when filling items in each position of the recipe plan, where the item scoring system is to score alternative items, and the scoring method is as follows:
item score
{wiI ═ 1, 2.., n } is a set of weighting coefficients, and the following conditions are satisfied:
(1)0<wi≤1，i＝1,2,...,n
(2)
where n is the number of weight coefficients.
AiI 1, 2.., n } is a set of scoring indices including, but not limited to, nutritional score, taste score, intake rate, leftover rate, yield rate, profit margin rate.
Further, the entrance rate and the leftovers rate are calculated by data collected by the AI visual settlement table and the grade outlet product outlet machine, and the formula is as follows: the remaining rate is (output-sales volume)/sales volume, and the entrance rate is (sales volume-food residue)/sales volume.
Further, the success rate and profit rate are calculated by data configured in the basic setting, and the formula is as follows: yield rate is the actual output/raw material quantity, and profit rate is (selling price-sum of raw material costs of item)/selling price.
The invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the recipe plan generation method according to any one of claims 1 to 5.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the recipe plan generation method according to any one of claims 1 to 5 when executing the computer program.
The invention also provides a conditional intelligent menu plan generating system, which comprises
The system comprises a storage module, a display module and a display module, wherein the storage module is used for pre-storing menu information required by generating a menu plan, and the menu information comprises basic data, food material information and item information;
the condition limiting module is used for setting limiting conditions according to requirements of different projects so as to restrict the generation of the menu, wherein the limiting conditions comprise food materials, nutrition, taste, color, cooking methods and gross profit rate;
the matching degree calculation module is used for calculating the matching degree of the menu plan filled by the existing items of the user and the set limiting conditions;
and the menu generating module is used for generating a menu plan or carrying out automatic or manual adjustment according to the matching result.
Further, an item scoring system is further arranged in the matching degree calculation module, the item scoring system is adopted when items are filled in each position of the menu plan, the item scoring system scores alternative items, and the scoring method comprises the following steps:
item score
{wiI ═ 1, 2.., n } is a set of weighting coefficients, and the following conditions are satisfied:
(1)0<wi≤1，i＝1,2,...,n
(2)
where n is the number of weight coefficients.
{Ai1, 2., n } is a set of scoring indices including, but not limited to, nutritional score, taste score, intake rate, and percentage of remaining vegetablesYield, profit margin.
Compared with the prior art, the conditional intelligent recipe plan generation method has the following advantages:
(1) the preset information required by the recipe plan generation is stored in the server in advance, so that the recipe plan generation system can be used all the time after one-time input is finished, and a form does not need to be checked before the recipe plan is made every time. And after the recipe plan is generated, specific numerical values such as various nutrients and the capillary rate can be calculated and displayed by the system, which cannot be realized under the condition that the existing manual work writes through experience;
(2) compared with the existing manual writing, the efficiency of the method is greatly improved. The manual recipe plan compiling usually needs one day or even several days, but only several minutes are needed by using the method of the invention, and batch generation and modification can be carried out, thus saving time and labor and relieving a large amount of labor cost for enterprises;
(3) after the menu plan is used, various data can be collected so as to intelligently adjust the menu plan generated in the future, so that the overall purchasing cost, waste cost, profit, public praise of customers and the like are obviously optimized;
(4) because the manual operation is replaced, the accuracy is also very guaranteed, and unnecessary troubles and losses brought to companies and clients due to forgetting certain important conditions in the past can be avoided.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for generating a conditional intelligent recipe plan according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
The recipe plan generating method and system according to the embodiment of the present invention may be implemented in a terminal equipped with an operating system such as Windows (an operating system platform developed by microsoft corporation), Android (an operating system platform developed by google corporation for portable mobile smart devices), iOS (an operating system platform developed by apple corporation for portable mobile smart devices), or Windows Phone (an operating system platform developed by microsoft corporation for portable mobile smart devices), and the terminal may be any one of a desktop computer, a notebook computer, a mobile Phone, a palm computer, and a tablet computer.
The invention is further illustrated by the following figures and examples.
As shown in fig. 1, in this embodiment, a generation method of a conditional intelligent recipe plan is used to realize that a server generates a recipe plan intelligently for a user, and the generation method of an intelligent recipe plan includes the following steps 1 to 5:
step 1, storing preset information required by generating a menu plan to a server in advance; the preset information comprises basic data, food material information and item information;
in step 1, the basic data includes: management of meal type, unit management, cooking mode, dish taste, dish color and shape.
The meal can be freely defined, such as breakfast and dinner, respectively, corresponding to 8:00 to 10: 00 and 17: 00 to 19: 00.
the units can be freely defined, such as parts, cases, discs, etc.
The cooking manner can be freely defined, such as frying, stir-frying, frying and the like.
The taste of the dish can be freely defined, such as sour, sweet, bitter, spicy, etc.
The color of the dish can be freely defined, such as red, yellow, green, etc.
The shape can be freely defined, e.g. a bar, a block, a segment, etc.
In step 1, the food material information includes: category management, food material management, and processed food material management.
The category management may set categories of food materials such as meat, vegetables, fish, and the like.
Food material management food materials, such as pork streaky pork, can be added and edited, and his category is selected to be meat, which is sold at a price of 60 yuan per kilogram, and contains about 598.7 kilojoules of energy, 13.2 grams of protein, 37 grams of fat, and 3.4 grams of carbohydrate per 100 grams of pork.
The processed food material management can add and edit processed food materials, such as pork streaky pork, and select his category as meat, which is in the shape of a block, sold at a price of 60 yuan per kilogram, and contains about 598.7 kilojoules of energy, 13.2 grams of protein, 37 grams of fat, and 3.4 grams of carbohydrate per 100 grams of pork.
In step 1, the item information includes: management of dishes and management of commodities.
The management of dishes can add and edit items, such as pork braised in soy sauce, the selling price is 35 yuan, the unit is a plate, the cooking mode is the pork braised in soy sauce, the taste is sweet, the color is red, the shape is a block, and the food ingredients are 300 g of pork streaky pork blocks and 200 g of potatoes.
The commodity management can add and edit commodities such as coca cola, which is sold at 3 yuan, each 100 ml of which contains about 180 kilojoules of energy, 0 gram of protein, 0 gram of fat and 11 grams of carbohydrate.
Step 2, the user sets corresponding limiting conditions in the system according to the requirements of different projects to restrict the generation of the menu and stores the menu in the server; wherein the limiting conditions include food material, nutrition, taste, color, cooking method and gross profit rate;
for example, a user needs to generate a menu A, and the food materials are pork shavings with sweet taste and red color, the cooking mode is braised, the nutrition energy is about 0-598.7 kilojoules, the protein is 0-13.2 grams, the fat is 0-37 grams, the carbohydrate is 0-3.4 grams, and the gross profit rate is 20%.
And 3, the server performs matching judgment according to the preset information stored by the user in the step 1 and the limiting conditions set in the step 2:
when the server judges that the matching degree of the menu plan filled by the existing items of the user and the set limiting condition reaches a preset matching degree threshold value, the server displays the generated menu plan to the user; otherwise, the server goes to step 4 to execute the manual menu adjustment plan of the user;
specifically, for the generation method of the conditional intelligent recipe plan, in step 3, the preset matching degree threshold is 100%. That is, the server will fill the item into the recipe plan only when the item completely matches the limit condition set by the user;
the method carries out gross profit verification when the menu is generated, calculates the gross profit according to different grades, regenerates the menu if the gross profit does not meet the conditions until the menu meeting the gross profit standard is obtained, stores the menu with the highest gross profit once in the generated menu in the process, adopts the menu with the highest gross profit and prompts if the menu does not meet the standards after being generated for a certain number of times.
For example, by implementing the exemplary constraints in step 2, a recipe a plan is generated that selects red-cooked meat as the filling item.
And 4, after the menu plan is generated, manually adjusting the unsatisfied part in the menu plan by a user according to the requirement of the user, wherein the adjustment mode is to add, delete or replace the filled items in the menu plan.
The specific process of manually adjusting the menu comprises the following steps:
(1) when some positions in the menu template can not find the fillable dishes, leaving a blank and prompting a user to explain reasons (the reasons are recorded in the menu generating process, if the conditions X cause that the usable dishes can not be selected), guiding the user to manually select the dishes to be filled, or modifying the conditions to regenerate the menu, and carrying out the next step after the menu is complete, otherwise, the user can not confirm to store.
(2) When a user adjusts existing dishes, a recommended alternative dish list is given, available alternative dishes are obtained by inquiring a raw material set used by other recipes in the same time, and then screening is carried out by using other conditions such as current template conditions, food material inventory and workshop workload, so that the method is more reasonable.
(3) The manual operation is not limited at all (for example, a certain food material does not repeatedly appear in N days, dishes repeatedly appear in the same day, the processing workload of the food material exceeds the upper limit of the workshop capacity, and the like), the dish list can be stored as long as the dish list is complete, but any unreasonable situation occurs due to the manual operation, and a prompt needs to be made.
(4) The change of the menu caused by manual operation is recorded and the information of related dishes is updated (such as the last using time, the weight and the number of times of appearance which is modified if the dish appearance rate is counted).
In addition, in consideration of the fact that the recipe plan generated intelligently by the system does not necessarily completely meet the psychological expectation of the user, in order to enable the generated recipe plan to be convenient for the user to use and adjust, all abnormal situations need to be prompted to the user at different levels after the recipe plan is generated. Wherein the abnormal condition comprises: available dishes cannot be found, the requirements are not completely met (such as the gross profit rate does not reach the standard but is as close as possible), and the nutrition, the taste, the color, the cooking method and the like are unreasonable.
And 5, storing the menu plan to the server after the user finishes the adjustment, recalculating and generating a new menu plan by the system according to the adjustment, and displaying the new menu plan to the user.
The generated menu is stored in the server so that the user can continue to use the menu at a later date or generate the associated menu based on the menu.
The invention also includes counting the preference of the user according to the historical menu, adjusting the weight of the dishes to make the generated menu more in line with the expectation, and the counting mode is to record the times of the appearance of the dishes, adjust the preference parameter according to the use frequency, record the dishes operated manually, manually increase the dish up-regulation preference parameter and manually delete the dish down-regulation preference parameter.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A conditional intelligent menu plan generation method is characterized by comprising the following steps: the method comprises the following steps:
s1: the method comprises the steps that menu information required by generating a menu plan is stored in advance, wherein the menu information comprises basic data, food material information and item information;
s2: setting limiting conditions according to requirements of different items to restrict the generation of a menu, wherein the limiting conditions comprise food materials, nutrition, taste, color, cooking method and gross profit rate;
s3: calculating the matching degree of the menu plan filled by the existing items of the user and the set limiting conditions;
and S4, if the two are matched, generating a menu plan, and if the two are not matched, carrying out automatic or manual adjustment.
2. The method of claim 1, wherein the method comprises: in step S1, the basic data includes meal management, unit management, cooking method, dish taste, dish color, and shape management; the food material information includes: category management, food material management, and processed food material management; the item information includes: management of dishes and management of commodities.
3. The method of claim 1, wherein the method comprises: step S3 further includes using an item scoring system when filling items for each position of the recipe plan, where the item scoring system scores alternative items, and the scoring method includes:
item score
{wiI ═ 1, 2.., n } is a set of weighting coefficients, and the following conditions are satisfied:
(1)0<wi≤1，i＝1,2,...,n
(2)
where n is the number of weight coefficients.
AiI 1, 2.., n } is a set of scoring indices including, but not limited to, nutritional score, taste score, intake rate, leftover rate, yield rate, profit margin rate.
4. The method of claim 3, wherein the method comprises: the entrance rate and the leftovers rate are calculated by data collected by an AI visual settlement table and a grade outlet product outlet machine, and the formula is as follows: the remaining rate is (output-sales volume)/sales volume, and the entrance rate is (sales volume-food residue)/sales volume.
5. The method of claim 3, wherein the method comprises: the rate of success and profit are calculated by data configured in the basic setting, and the formula is as follows: yield rate is the actual output/raw material quantity, and profit rate is (selling price-sum of raw material costs of item)/selling price.
6. A computer-readable storage medium having stored thereon a computer program, characterized in that: the program when executed by a processor realizes the steps of the recipe plan generation method as claimed in any one of claims 1 to 5.
7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein: the processor, when executing the computer program, realizes the steps of the recipe plan generation method according to any one of claims 1 to 5.
8. A conditional intelligent menu plan generating system is characterized in that: comprises that
The system comprises a storage module, a display module and a display module, wherein the storage module is used for pre-storing menu information required by generating a menu plan, and the menu information comprises basic data, food material information and item information;
the condition limiting module is used for setting limiting conditions according to requirements of different projects so as to restrict the generation of the menu, wherein the limiting conditions comprise food materials, nutrition, taste, color, cooking methods and gross profit rate;
the matching degree calculation module is used for calculating the matching degree of the menu plan filled by the existing items of the user and the set limiting conditions;
and the menu generating module is used for generating a menu plan or carrying out automatic or manual adjustment according to the matching result.
9. The system of claim 8, wherein the system further comprises: the matching degree calculation module is also provided with an item scoring system, the item scoring system is adopted when filling items for each position of the menu plan, the item scoring system can score alternative items, and the scoring method comprises the following steps:
item score
{wiI ═ 1, 2.., n } is a set of weighting coefficients, and the following conditions are satisfied:
(1)0<wi≤1，i＝1,2,...,n
(2)
where n is the number of weight coefficients.
{AiI 1, 2.., n } is a set of scoring indices including, but not limited to, nutritional score, taste score, intake rate, leftover rate, yield rate, profit margin rate.
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| CN113990444A (en) * | 2021-10-11 | 2022-01-28 | 医膳通(广东)信息技术有限公司 | Intelligent nutrition diet management method and system based on data analysis and deep learning |
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Application publication date: 20200623 |