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Diet plan decision-making method and device, computer equipment and storage medium

A decision-making method and diet technology, applied in the field of big data, can solve the problems of low degree of automation and low efficiency

Pending Publication Date: 2021-07-06
PING AN TECH (SHENZHEN) CO LTD
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Problems solved by technology

[0003] The main purpose of this application is to provide a decision-making method, device, computer equipment and storage medium for a dietary plan, aiming at solving the problem of low automation and low efficiency of current dietary advice

Method used

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  • Diet plan decision-making method and device, computer equipment and storage medium
  • Diet plan decision-making method and device, computer equipment and storage medium
  • Diet plan decision-making method and device, computer equipment and storage medium

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Experimental program
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Embodiment approach

[0066] Among them, an implementation manner of calculating the change of the physiological state data after performing an action is as follows:

[0067] The total daily energy consumption of the human body = 0.95*daily basal metabolic consumption*PAL;

[0068] Among them: energy consumption of daily basal metabolism = BMR(kcal / m^2 / h)*24H*body surface area;

[0069] PAL (Physical Activity Level) is the 24h total energy expenditure divided by the energy consumed by the 24h basal metabolism. Basal metabolic rate (BMR) refers to the basal metabolic energy consumed by the human body per square meter of body surface area per unit time. The unit is kcal / m^2 / h. Further, men's basal metabolic rate Men BMR=66.4730+(13.7516x weight in kg)+(5.0033xheight in cm)–(6.7550x age in years); women's basal metabolic rate Women BMR=655.0955+(9.5634x weight in kg)+(1.8496xheight in cm)–(4.6756x age in years); body surface area (m^2)=0.00659*height (cm)+0.0126*weight (kg)-0.1603; final: (energy i...

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Abstract

The invention relates to the field of big data processing, and discloses a diet plan decision-making method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining current physiological state data and target physiological state data of a user; taking the current physiological state data and the target physiological state data as input of a sequential decision model of reinforcement learning, and outputting a plurality of execution plans and reward values of the execution plans based on the sequential decision model of reinforcement learning; and selecting an execution plan meeting a preset condition as a target execution plan according to the reward value, and outputting the execution action and physiological state data of each day included in the target execution plan. According to the invention, the diet data of the long-term plan can be output, and the planning efficiency of the diet plan is improved.

Description

technical field [0001] This application relates to the field of big data, in particular to a decision-making method, device, computer equipment and storage medium for a diet plan. Background technique [0002] Health is an inevitable requirement for promoting the all-round development of people. People’s requirements for a healthy diet are increasing year by year. The current dietary health management tools can only identify and analyze the calories of food at a time, and inform users of the calories of food. The inventor realized that the current The diet health management tool of the company cannot provide continuous dietary advice, and the degree of automation and efficiency of dietary advice is low. Contents of the invention [0003] The main purpose of this application is to provide a decision-making method, device, computer equipment and storage medium for a dietary plan, aiming to solve the problem of low automation and low efficiency of current dietary advice. [...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H20/60G06N3/08
CPCG16H20/60G06N3/08
Inventor 袁东昇阮晓雯肖京
Owner PING AN TECH (SHENZHEN) CO LTD
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