Catering management method based on healthy diet

Abstract

The invention relates to the field of catering management, in particular to a healthy diet-based catering management method, which comprises the following steps of: acquiring and integrating user information, acquiring user diet basic information, distributing a monitoring period and continuously observing the dynamic change of the user diet basic information to provide a basis for subsequently generating a diet scheme; by generating the initial recipe, processing to obtain the personalized recipe and optimizing the recipe recommendation strategy, the diet plan is ensured to be closer to the actual demand of the user, and the user experience is improved; according to the optimized recipe recommendation strategy, an intelligent diet scheme is evaluated, accurate tracking of food materials and intelligent dish matching are carried out, and the accuracy and controllability of cooking are improved; the financial information of the restaurant is analyzed, the cost control is optimized, the operation cost of the restaurant is reduced, the profitability is improved, and a powerful guarantee is provided for sustainable development of the restaurant. The method is used for solving the technical problem that the current catering management efficiency is not high.

Description

Technical Field

[0001] The present invention relates to the field of catering management, and particularly to a catering management method based on healthy diet. Background Art

[0002] Catering management refers to a series of activities and measures for planning, organizing, controlling, and supervising all aspects of the catering service industry, aiming to improve service quality, increase efficiency, reduce costs, and enhance satisfaction. The core of catering management lies in enhancing the quality of catering services through scientific management methods and means to meet diverse needs, thereby achieving the economic and social benefits of the enterprise.

[0003] Current catering management still faces some challenges, including the following aspects: It is difficult to meet personalized dietary needs. Traditional catering management methods often lack detailed analysis and precise matching for users' personalized dietary needs and cannot fully meet users' personalized requirements in terms of gender, age, health status, taste preferences, and special needs (such as allergen avoidance); The division of dietary strategies is not scientific. Previous catering management was often rather general in the division of dietary strategies, lacking scientific analysis based on users' health data and behavior habits, and it was difficult to formulate a dietary plan that meets the actual needs of users; It is difficult to track the dynamic changes in users' basic dietary information. Users' basic dietary information such as health status and eating habits will change over time, but traditional catering management methods are difficult to continuously track and dynamically adjust this information, resulting in the lack of timeliness and effectiveness of the dietary plan; The effect of restaurant cost control is lacking. In terms of cost control, traditional catering management methods often lack refined analysis and effective technical means, and it is difficult to deeply mine restaurant operation data and transparently manage financial information, resulting in cost waste and a decline in profitability; To address these challenges, corresponding solutions and technical means are needed to improve the efficiency of catering management and the user experience. Summary of the Invention

[0004] The purpose of the present invention is to solve the problems in the background art and propose a catering management method based on healthy diet.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions: A catering management method based on healthy diet, including: Step 1: Collect and integrate user information to obtain users' basic dietary information; divide dietary strategies in combination with users' basic dietary information, and observe the dynamic changes in users' basic dietary information by allocating a monitoring period. Step 2: Generate an initial recipe according to the dynamic changes in users' basic dietary information, process the generated initial recipe to obtain a personalized recipe, and optimize the recipe recommendation strategy according to users' feedback. Step 3: Based on the optimized recipe recommendation strategy, evaluate the intelligent diet plan, complete the side dish preparation and cooking operations, and notify the user to pick up the meal; Step 4: Analyze the financial information of the restaurant to optimize cost control.

[0006] It should be noted that the catering management method based on healthy diet proposed by the present invention can be widely applied to the catering service industry. This method can be used to provide personalized and scientific catering management solutions. Specifically, through a series of advanced technologies (including Bayesian network model, cluster analysis, discriminant analysis, logistic mapping, linear programming, etc.), a comprehensive analysis of user data is carried out. This process covers multiple links such as user information collection, diet strategy division, monitoring period allocation, recipe optimization recommendation, and restaurant financial analysis. These links jointly ensure the health, science, and personalization of the user's diet, thereby improving the satisfaction and efficiency of catering services, and realizing the personalization, precision, and high efficiency of catering services; by accurately integrating and analyzing user information, this method can generate personalized recipes that meet the user's health status, taste preferences, and special needs, and combine dynamic monitoring and optimization strategies to continuously improve the accuracy and controllability of catering management. At the same time, this method also pays attention to the financial cost control of the restaurant, and ensures the transparency and security of transaction information through technical means such as blockchain, providing strong support for the sustainable development of catering services.

[0007] Further, the process of collecting and integrating user information to obtain the user's basic diet information, and dividing the diet strategy in combination with the user's basic diet information, and observing the dynamic changes of the user's basic diet information by allocating the monitoring period includes: Combined with the data of wearable devices, using the Bayesian network model in probability statistics, comprehensively collect the user's health status (gender, age, height, weight, past medical history, medication situation), behavioral lifestyle (eating habits, exercise frequency), and tableware requirements (number of chopsticks / spoons, whether public chopsticks / public spoons are needed), and conduct accurate integration and analysis of user information to finally obtain the user's basic diet information; It is understandable that the user's basic diet information is inferred through the Bayesian network model by integrating the data of wearable devices; Comprehensively considering the user's basic diet information, using cluster analysis (i.e., hierarchical cluster analysis) and discriminant analysis (i.e., linear discriminant analysis) in multivariate statistical analysis to divide the diet strategy, thereby generating multiple types of user diet strategies; Introduce the logistic mapping in chaos theory for monitoring period allocation, record and observe the dynamic changes of the user's basic diet information according to the period, and use the dynamic change results as the input information of the personalized recipe.

[0008] Furthermore, there are various types of user diet strategies, specifically including children's diet, adolescents' diet, adult men's diet, adult women's diet, women's diet during menstruation, diet for chronic patients (obesity, hypertension, hyperlipidemia, diabetes), diet for the four seasons of spring, summer, autumn and winter, personalized taste diet, diet for avoiding allergens, and diet planning based on note information.

[0009] Furthermore, the process of generating the initial recipe according to the dynamic changes of the user's diet basic information, processing the generated initial recipe to obtain a personalized recipe, and optimizing the recipe recommendation strategy according to the user's feedback includes: According to the dynamic change results of the user's diet basic information, use a linear programming model to preliminarily design a recipe that meets the nutritional requirements and generate the initial recipe; Further considering the customer's diet preferences and special circumstances (such as allergy information, taboo foods), use matrix factorization technology to perform personalized screening and adjustment on the initial recipe, and finally generate a personalized recipe containing detailed nutritional information (energy, carbohydrates, fat, etc.); Combined with the user's feedback on the personalized recipe, adopt the Markov decision process and Q-learning algorithm to continuously optimize the recipe recommendation strategy, aiming to maximize the diversity of the recipe, and determine an intelligent diet plan including ingredient information, cooking method information, dish weight, etc.

[0010] Furthermore, the process of evaluating the intelligent diet plan based on the optimized recipe recommendation strategy, completing side dish preparation and cooking operations, and notifying the user to pick up the meal includes: Obtain the user's personalized recipe information in real time through the API interface, and use the entropy concept in information theory to evaluate the information accuracy and integrity of the intelligent diet plan; Apply the vehicle routing problem algorithm in operations research to achieve precise tracking of ingredients and intelligent side dish preparation, and optimize the cooking process; Introduce fuzzy sets and fuzzy logic in fuzzy mathematics to analyze the uncertain factors in the cooking process and improve the precision and controllability of cooking; Use the M / M / 1 queue model in queuing theory to automatically allocate tableware, and combine text messages or APP push to notify the user to pick up the meal.

[0011] Furthermore, the process of analyzing the financial information of the restaurant and optimizing cost control includes: Adopt blockchain technology to record transaction information. After the user checks out, automatically count the account information and file it, and use a hash function to ensure the transparency and immutability of the accounts; Use association rules to deeply mine the restaurant operation data, regularly count various expenditures of the restaurant, and generate a financial cost control report; It is understandable that the acquisition of restaurant operation data comes from the transaction database, specifically including each transaction data (i.e., the quantity of dishes sold, price, user payment method, consumption time, etc.), the purchase, warehousing, outbound and inventory situation of restaurant raw materials, as well as data such as employee attendance, salary, and performance.

[0012] Compared with the existing technologies, the advantages of the catering management method based on healthy diet provided by the present invention are as follows: 1. By comprehensively collecting the user's health status (such as gender, age, height, weight, past medical history, medication situation), behavioral lifestyle (such as eating habits, exercise frequency), and tableware requirements (such as the number of chopsticks / spoons, whether public chopsticks / public spoons are needed), the present invention provides a solid foundation for generating personalized recipes in the follow-up. By applying the Bayesian network model and combining with wearable device data, the user's basic diet information can be inferred more accurately. Then, by means of cluster analysis and discriminant analysis, users are divided into different diet strategy types (such as children's diet, diet for chronic patients, etc.), providing a scientific basis for subsequent diet recommendations. By introducing the logistic map in chaos theory for monitoring period allocation, the dynamic changes of the user's basic diet information can be recorded and observed according to the cycle, and the diet strategy can be adjusted in time according to the changes in the user's physical condition, ensuring the timeliness and effectiveness of the diet plan; 2. By using the linear programming model to preliminarily design a recipe that meets the nutritional requirements according to the dynamic changes of the user's basic diet information, the present invention ensures that the nutritional components such as energy, protein, and vitamins ingested by the user reach a balanced state, which helps to maintain physical health. By processing the generated initial recipe, a personalized recipe containing detailed nutritional information is obtained, meeting the user's taste preferences and special diet requirements (such as allergen avoidance), improving the user's diet satisfaction and comfort. In response to user feedback, the recipe recommendation strategy is continuously optimized to ensure that the diet plan is closer to the actual needs of the user and improve the user experience; 3. By using the API interface to obtain the user's personalized recipe information in real time, the present invention uses the entropy concept in information theory to evaluate the information accuracy and integrity of the intelligent diet plan, ensuring that the obtained diet information is accurate and error-free, and avoiding diet risks caused by information errors. By applying the vehicle routing problem algorithm in operations research, the precise tracking of ingredients and intelligent dish matching are realized, the cooking process is optimized, and the cooking efficiency and dish quality are improved. At the same time, the fuzzy set and fuzzy logic in fuzzy mathematics are introduced to analyze the uncertain factors in the cooking process, improving the precision and controllability of cooking. By using the M / M / 1 queue model in queuing theory to automatically allocate tableware and combining with SMS or APP to push notifications to the user to pick up the meal, the convenience and satisfaction of the user's dining are improved; 4. The present invention records transaction information by adopting blockchain technology, ensuring transparent and tamper-proof accounts, improving the financial management level of the restaurant, and guaranteeing the financial security of the restaurant. By using association rules to deeply mine the restaurant operation data, regularly count various expenditures of the restaurant, and generate a financial cost control report, it helps the restaurant managers to timely discover cost waste and potential problems, take effective measures, and provide strong data support for the cost control and optimization of the restaurant.

[0013] In summary, the present invention, through precise user information integration and analysis, personalized recipe recommendation strategies, intelligent side dish and cooking operations, and scientific financial information analysis, jointly constitutes the core framework of the catering management method based on healthy diet. It not only improves the service quality and competitiveness of the restaurant, but also optimizes the cost control and financial management level, ensuring the normal implementation of the subsequent catering management method based on healthy diet. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flowchart of the catering management method based on healthy diet proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0016] Referring to Figure 1 , the catering management method based on healthy diet includes: Step 1: Collect and integrate user information to obtain the basic user diet information; combine the basic user diet information for diet strategy division, and observe the dynamic changes of the basic user diet information by allocating a monitoring period. Step 2: Generate an initial recipe according to the dynamic changes of the basic user diet information, process the generated initial recipe to obtain a personalized recipe, and optimize the recipe recommendation strategy according to the user feedback. Step 3: Evaluate the intelligent diet plan based on the optimized recipe recommendation strategy, complete the side dish and cooking operations, and notify the user to pick up the meal. Step 4: Analyze the financial information of the restaurant and optimize the cost control.

[0017] It should be noted that the catering management method based on healthy diet proposed by the present invention can be widely applied to the catering service industry. This method can be used to provide personalized and scientific catering management solutions. Specifically, it can comprehensively analyze user data through a series of advanced technologies (including Bayesian network models, cluster analysis, discriminant analysis, logistic mapping, linear programming, etc.). This process covers multiple links such as user information collection, diet strategy division, monitoring period allocation, recipe optimization recommendation, and restaurant financial analysis. These links together ensure the health, science, and personalization of users' diets, thereby improving the satisfaction and efficiency of catering services and realizing the personalization, precision, and high efficiency of catering services. By accurately integrating and analyzing user information, this method can generate personalized recipes that meet the user's health status, taste preferences, and special needs, and combine dynamic monitoring and optimization strategies to continuously improve the accuracy and controllability of catering management. At the same time, this method also pays attention to the financial cost control of the restaurant, and uses technical means such as blockchain to ensure the transparency and security of transaction information, providing strong support for the sustainable development of catering services.

[0018] Please refer to Figure 1 , the present invention provides a catering management method based on healthy diet. In step 1, the user information is collected and integrated to obtain the basic user diet information. The steps of dividing the diet strategy in combination with the basic user diet information and observing the dynamic changes of the basic user diet information by allocating the monitoring period include: Step 101: Combine the data of wearable devices and use the Bayesian network model in probability statistics to comprehensively collect the user's health status (gender, age, height, weight, past medical history, medication situation), behavioral lifestyle (eating habits, exercise frequency), and tableware requirements (number of chopsticks / spoons, whether public chopsticks / spoons are needed), and conduct accurate integration and analysis of user information to finally obtain the basic user diet information; In step 101, the Bayesian network model is specifically , where represents the user's health status (gender, age, height, weight, past medical history, medication situation), behavioral lifestyle (eating habits, exercise frequency), and tableware requirements (number of chopsticks / spoons, whether public chopsticks / spoons are needed) collected, and represents the data obtained by the wearable device; Taking the user's health status as an example, take as the user's past medical history to judge whether the user has hypertension , represents the prior probability of having hypertension in the population; take as the data obtained by the user's wearable device, that is, the average blood pressure value for three consecutive days ; represents the probability of the average blood pressure value for three consecutive days obtained by the wearable device in the case that the user has hypertension ; Indicates the probability of the average blood pressure values obtained by the wearable device over three consecutive days in the general population. By the total probability formula , where represents all possible user health conditions, represents the index of the possible health conditions of the user; It is understandable that through the Bayesian network model, the basic diet information of the user is inferred by integrating the wearable device data; Step 102: Considering the user's basic diet information comprehensively, using cluster analysis (hierarchical cluster analysis) and discriminant analysis (linear discriminant analysis) in multivariate statistical analysis to divide the diet strategies, thereby generating multiple types of user diet strategies, specifically including children's diet, adolescent diet, adult male diet, adult female diet, diet for women during menstruation, diet for chronic patient groups (obesity, hypertension, hyperlipidemia, diabetes), diet for the four seasons of spring, summer, autumn and winter, personalized taste diet, allergen avoidance diet, and diet planning based on note information; In step 102, during the process of cluster analysis, the hierarchical clustering method is adopted, and specifically, the distance formula in hierarchical clustering is used to calculate the similarity or distance between the basic diet information of two users; among them, the specific formula is , where and respectively represent the basic diet information vectors of two users, represents the dimension of the basic diet information vector, represents the index of the basic diet information vector, can be used to represent age, weight, and weekly exercise frequency; It is understandable that by calculating this distance, similar users are clustered together for subsequent targeted diet strategy division; During the process of discriminant analysis, the linear discriminant analysis method is adopted for analysis: for two-class problems, the goal is to find a projection direction such that the ratio of the between-class variance to the within-class variance is maximized, and the specific formula is , where represents the between-class scatter matrix, which is used to measure the dispersion degree between different categories. Taking healthy people and diseased people as an example, assuming there are two types of users, one is a healthy population and the other is a population suffering from a certain disease. For each category, calculate its corresponding mean vector , then , represents the within-class scatter matrix, which is used to measure the dispersion degree within each category. For each sample of the basic diet information in the healthy population category, calculate and sum to get , similarly, for the population category suffering from a certain disease, obtain , then , represents the transpose of the matrix; By maximizing the ratio of between-class variance to within-class variance find the optimal projection direction , so as to conduct effective dietary strategy division; Step 103: Introduce the logistic map in chaos theory to allocate monitoring periods, record and observe the dynamic changes of the user's basic diet information according to the periods, and use the dynamic change results as the input information of the personalized recipe; In step 103, according to the logistic map formula allocate the monitoring periods, where, is the th state, representing the state of the user's basic diet information within a certain time period. For example can represent the degree of balanced nutrition intake of the user in the th monitoring period ( , 0 means completely unbalanced, 1 means completely balanced), represents the control parameter , different values will result in different dynamic changes.

[0019] Please refer to Figure 1 , the present invention provides a catering management method based on healthy diet. In the second step, according to the dynamic changes of the user's basic diet information, generate a primary recipe, process the generated primary recipe to obtain a personalized recipe, and the steps of optimizing the recipe recommendation strategy for user feedback include: Step 201: According to the dynamic change results of the user's basic diet information, use a linear programming model to preliminarily design a recipe that meets the nutritional requirements and generate a primary recipe; In step 201, assume that it is necessary to meet kinds of nutritional requirements (such as nutritional components such as protein, vitamin C, calcium, etc.), and there are kinds of foods (such as rice, eggs, apples, etc.) available for selection; Use to represent the intake of the th food, represents the content of the th nutritional component in the th food (for example represents the protein content in the th food), represents the lower limit of the th nutritional requirement (for example, at least g of protein); The linear programming model is: , , , where, represents the cost, calories, or other factors to be optimized for the th food (e.g., if cost control is required, represents the unit price of the th food, and if calorie intake control is required, represents the calorie value of the th food); Step 202: Further consider the customer's dietary preferences and special conditions (such as allergy information, restricted foods), and use matrix factorization technology to perform personalized screening and adjustment on the initial recipe, and finally generate a personalized recipe containing detailed nutritional information (energy, carbohydrates, fat, etc.); In Step 202, construct a user-food rating matrix ; where the user-food rating matrix is a matrix, represents the number of users, represents the number of foods; Decompose the user-food rating matrix into , where, represents a matrix, represents a matrix, represents the latent factor; For example, assume that represents the rating of the th user for the th food (such as a score from 1 to 5), The element in the matrix represents the relationship strength between the th user and the th latent factor, The element in the matrix represents the relationship strength between the th food and the th latent factor; Step 203: Combine the user's feedback on the personalized recipe, and use the Markov decision process and Q-learning algorithm to continuously optimize the recipe recommendation strategy, aiming to maximize the diversity of the recipe, and determine an intelligent diet plan including ingredient information, cooking method information, dish weight, etc.; In step 203, in the Markov decision process, set the diet satisfaction transition probability , which is used to represent the probability of transferring to a new diet satisfaction after adopting an adjustment strategy under the current diet satisfaction ; among them, the diet satisfaction includes three attributes: satisfied, average, and dissatisfied, and the adjustment strategy represents the adjustment strategy for the personalized recipe (such as adding a certain food, changing the cooking method, etc.); Update using the Q-learning algorithm: , in the formula, is the learning rate , which is used to determine the speed of learning new information. For example, means that only 10% of the new information is accepted for each update, represents the discount factor , which is used to measure the importance of future rewards. If , it means that the reward value of the next step in the future is 90% of the current reward value, is the immediate reward, which represents the user's diet satisfaction after adjusting the personalized recipe, represents the updated diet satisfaction and the corresponding adjustment strategy.

[0020] Please refer to Figure 1 , the present invention provides a catering management method based on healthy diet. In the third step, based on the optimized recipe recommendation strategy, the steps of evaluating the intelligent diet plan, completing the side dish and cooking operations, and notifying the user to pick up the meal include: Step 301: Obtain the user's personalized recipe information in real time through the API interface, and evaluate the information accuracy and integrity of the intelligent diet plan using the entropy concept in information theory; In step 301, the entropy concept formula is specifically: , In the formula, represents the information evaluation value of the intelligent diet plan, represents all possible values of the intelligent diet plan, respectively represent that a certain ingredient information in the intelligent diet plan is accurate and the cooking method information is accurate, represents the probability of the value . If has a low value, it means that the uncertainty of the information of the intelligent diet plan is small, and the accuracy and integrity are high; Step 302: Apply the vehicle routing problem algorithm in operations research to achieve precise tracking of ingredients and intelligent side dish preparation, and optimize the cooking process; In step 302, for each user, obtain the ingredient requirement points , that is, the different ingredients required for each dish; Take the vehicles as the resources or process links for side dish preparation, that is, different side dish preparers or side dish preparation equipment; Mark the cost (such as time, distance, etc.) from point to point as ; Define the decision variable ; If vehicle goes from point to point , then the value of the decision variable is 1, otherwise the value of the decision variable is 0; Create the objective function: , and set the constraint conditions of the objective function: , , , , where the constraint condition means that each vehicle must depart from the distribution center (point 0) once, the constraint condition means that each vehicle must return to the distribution center (point 0) once, the constraint condition means that each ingredient requirement point must be served by one vehicle once, and the constraint condition means that each ingredient requirement point can only be served by one vehicle once; Step 303: Introduce fuzzy sets and fuzzy logic in fuzzy mathematics to analyze the uncertain factors in the cooking process and improve the accuracy and controllability of cooking; In step 303, during the cooking process, mark the ideal cooking temperature as the fuzzy set , and its membership function defines the degree to which the element belongs to the set , and ; where the element represents the current temperature state (which can be measured by indicators such as temperature), and the function represents the degree to which the current temperature state is close to the ideal cooking temperature. When When it is, it indicates that the current cooking state is relatively close to the ideal state. It is understandable that for uncertain factors (such as the fuzzy evaluation of ingredient freshness, the fuzzy control of cooking temperature, etc.), fuzzy logic can be used for modeling and analysis to improve the accuracy and controllability of cooking; Step 304: Use the M / M / 1 queue model in queuing theory to automatically allocate tableware and combine SMS or APP push to notify users to pick up their meals; In step 304, in the M / M / 1 queue, define the arrival rate and service rate as ; where represents the average rate at which users who need tableware arrive. For example, there are users arriving per hour; represents the average rate of service. For example, tableware can be prepared for users per hour; Then there is an average number of users .

[0021] Please refer to Figure 1 , the present invention provides a catering management method based on healthy diet. In step four, the steps of analyzing the financial information of the restaurant and optimizing cost control include: Step 401: Use blockchain technology to record transaction information. After the user checks out, automatically count the account information and file it, and use the hash function to ensure the transparency and immutability of the accounts; In step 401, for any input , use the hash function to convert into a hash value output of a fixed length; where represents the transaction information (including dish information, price, user information, etc.). For example, , after calculation by the hash function, is obtained (represented in hexadecimal); if changes in any way, then the value of will change significantly, ensuring the transparency and immutability of the accounts; Step 402: Use association rules to deeply mine the restaurant operation data, regularly count various expenditures of the restaurant, and generate a financial cost control report; In step 402, the acquisition of the restaurant operation data comes from the transaction database, specifically including each transaction data (i.e., the quantity of dishes sold, price, user payment method, consumption time, etc.), the purchase, warehousing, outbound and inventory situations of the restaurant raw materials, and data such as employee attendance, salary, performance, etc.; For the transaction database , set the minimum support and minimum confidence to be ; among them, the transaction database contains various transaction records of restaurant operations, such as ingredient purchase records, employee salary expenditure records, etc.; for example, the minimum support means that the occurrence frequency of an item set (i.e., ingredient 1 and ingredient 2 appear simultaneously) in the database must reach at least 20% to be considered a frequent item set, and the minimum confidence means that in all transactions containing ingredient 1, when 80% of the transactions also contain ingredient 2, it is considered that "if ingredient 1 is purchased, then ingredient 2 is purchased".

[0022] In the embodiment of the present invention, by collecting information such as the user's health status, behavioral lifestyle, and tableware needs, customized dietary services can be provided to each user to meet their unique nutritional and taste needs. By combining the user's basic dietary information to divide the dietary strategy, it is helpful for the restaurant to formulate appropriate menus and dietary suggestions for different user groups and improve user satisfaction. By allocating monitoring cycles to observe the dynamic changes of the user's basic dietary information, the restaurant can adjust the dietary strategy in time to ensure the user's dietary health and safety. By using a linear programming model to preliminarily design a recipe that meets the nutritional needs, it is ensured that the user obtains a comprehensive nutritional intake. By further considering the user's dietary preferences and special circumstances, the matrix decomposition technology is used to personalize the initial recipe and adjust it to improve the recipe's acceptance and satisfaction. By combining the user's feedback on the personalized recipe, the Markov decision process and the Q-learning algorithm are used to continuously optimize the recipe recommendation strategy, thereby improving the restaurant's service quality and competitiveness. By using the entropy concept in information theory to evaluate the effectiveness of the intelligent dietary plan The accuracy and completeness of information ensures the accuracy and reliability of recipes. By applying the vehicle routing problem algorithm in operations research, accurate tracking of ingredients and intelligent side dishes are achieved, the cooking process is optimized, and the operating efficiency of the restaurant is improved. By introducing fuzzy sets and fuzzy logic in fuzzy mathematics, the uncertainty factors in the cooking process are analyzed to improve the accuracy and controllability of cooking, and the quality and taste of dishes are ensured. By using the M / M / 1 queue model in queuing theory to automatically distribute tableware, and combining SMS or APP push notifications to users to pick up meals, the user's dining experience and satisfaction are improved. By using blockchain technology to record transaction information, the account is ensured to be transparent and cannot be tampered with, and the financial management level and credibility of the restaurant are improved. By using association rules to deeply mine the restaurant's operating data, the restaurant's various expenditures are regularly counted, and a financial cost control report is generated to help the restaurant accurately control costs and improve profitability. By deeply mining the restaurant's operating data, a strong data support is provided for the restaurant's management and decision-making, which helps the restaurant to formulate a more scientific and reasonable business strategy and development plan. In summary, the example of the present invention involves data processing, comprehensive analysis and intelligent adjustment decisions, solving the technical problem of low efficiency in current catering management. In actual situations, more data and contextual information may be needed to make specific decisions and optimize solutions.

[0023] In addition, the formulas involved above are all calculated by removing the dimension and taking their numerical values. They are obtained by collecting a large amount of data and performing software simulations to get a formula that is closest to the actual situation. The proportionality coefficient in the formula and each preset threshold in the analysis process are set by those skilled in the art according to the actual situation or obtained through a large amount of data simulations; the size of the proportionality coefficient is a specific value obtained by quantifying each parameter for the convenience of subsequent comparison. Regarding the size of the proportionality coefficient, it depends on the amount of sample data and the processing coefficients initially set by those skilled in the art for each group of sample data; as long as the proportional relationship between the parameters and the quantified values is not affected.

[0024] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key points of each embodiment are to illustrate the differences from other embodiments. In particular, for the device embodiments, since they are basically based on the method embodiments, they are described relatively simply, and for the relevant parts, reference can be made to the corresponding descriptions in the method embodiments.

[0025] For the convenience of description, when describing the above device, it is divided into various units according to functions for separate description. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0026] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0027] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0028] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one process or more processes and / or one block or more blocks of the process Figure 1 one process or more processes and / or Figure 1 one block or more blocks.

[0029] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process or more processes and / or one block or more blocks of the process Figure 1 one process or more processes and / or Figure 1 one block or more blocks.

[0030] Second: In the attached drawings of the disclosed embodiments of the present invention, only the structures related to the disclosed embodiments are involved. For other structures, reference may be made to the general design. Without conflict, the same embodiment and different embodiments of the present invention may be combined with each other; Finally: The above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and all should be covered by the protection scope of the present invention.

Claims

1. A catering management method based on healthy diet, characterized by: Step 1: Collect and integrate user information to obtain basic information about the user's diet; divide the diet strategy based on the basic information about the user's diet, and observe the dynamic changes of the basic information about the user's diet by allocating monitoring cycles; Step 2: Generate an initial recipe based on the dynamic changes of the user's basic dietary information, process the generated initial recipe to obtain a personalized recipe, and optimize the recipe recommendation strategy based on user feedback; Step 3: Based on the optimized recipe recommendation strategy, the smart diet plan is evaluated, the side dishes and cooking operations are completed, and the user is notified to pick up the meal; Step 4: Analyze the restaurant’s financial information and optimize cost control.

2. The catering management method based on healthy diet according to claim 1, characterized in that: In the step 1, user information is collected and integrated to obtain basic dietary information of the user; The process of dividing the diet strategy based on the basic diet information of the user and observing the dynamic changes of the basic diet information of the user by allocating monitoring cycles includes: Combined with wearable device data, the Bayesian network model in probability statistics is used to comprehensively collect users' health status, behavioral lifestyle, and tableware needs, and conduct accurate user information integration and analysis to ultimately obtain basic information about users' diets. Taking into account the basic information of users' diet, cluster analysis and discriminant analysis in multivariate statistical analysis are used to divide diet strategies, thereby generating various types of user diet strategies; The logistic map in chaos theory is introduced to allocate monitoring cycles. The dynamic changes of users' basic dietary information are recorded and observed periodically, and the dynamic change results are used as input information for personalized recipes.

3. The catering management method based on healthy diet according to claim 2 is characterized in that: The various types of user diet strategies include children's diet, adolescent diet, adult male diet, adult female diet, women's diet during menstruation period, diet for people with chronic diseases, diet for four seasons of spring, summer, autumn and winter, personalized taste diet, diet to avoid allergens and diet planning based on note information.

4. The catering management method based on healthy diet according to claim 1, characterized in that: In step 2, according to the dynamic changes of the user's basic dietary information, an initial recipe is generated, the generated initial recipe is processed to obtain a personalized recipe, and the recipe recommendation strategy is optimized according to user feedback, including: According to the dynamic changes of the user's basic dietary information, a linear programming model is used to preliminarily design a recipe that meets the nutritional needs and generate the initial recipe; Taking into account the dietary preferences and special circumstances of customers, the matrix decomposition technology is used to screen and adjust the initial recipes in a personalized way, and finally generate personalized recipes with detailed nutritional information. Combining user feedback on personalized recipes, the Markov decision process and Q-learning algorithm are used to continuously optimize the recipe recommendation strategy, aiming to maximize the diversity of recipes and determine intelligent diet plans.

5. The catering management method based on healthy diet according to claim 1, characterized in that: In step 3, based on the optimized recipe recommendation strategy, the intelligent diet plan is evaluated, the preparation and cooking operations are completed, and the user is notified to pick up the meal. The process includes: Obtain user personalized recipe information in real time through the API interface, and use the entropy concept in information theory to evaluate the accuracy and completeness of the information of the smart diet plan; Apply the vehicle routing problem algorithm in operations research to achieve accurate tracking of ingredients and intelligent side dishes, and optimize the cooking process; Introducing fuzzy sets and fuzzy logic in fuzzy mathematics to analyze the uncertainty factors in the cooking process and improve the accuracy and controllability of cooking; Use the M / M / 1 queue model in queuing theory to automatically distribute tableware, and use SMS or APP push notifications to notify users to pick up their meals.

6. The catering management method based on healthy diet according to claim 1, characterized in that: In step 4, the process of analyzing the restaurant's financial information and optimizing cost control includes: Blockchain technology is used to record transaction information. After the user checks out, the account information is automatically counted and archived. Hash functions are used to ensure that the account is transparent and cannot be tampered with. Use association rules to conduct in-depth mining of restaurant operation data, regularly count restaurant expenses, and generate financial cost control reports.

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