Nutritional diet recommending and evaluating method based on machine learning

A technology of machine learning and evaluation methods, applied in nutrition control and other directions, can solve the problems of complex and backward dietary structure, and achieve the effect of ensuring professionalism and scientificity

Inactive Publication Date: 2018-02-09
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, the Chinese diet structure is relatively complex, so compared with foreign countries, the development of domestic nutritional diet recommendations is still a bit behind

Method used

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  • Nutritional diet recommending and evaluating method based on machine learning

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Embodiment Construction

[0019] Embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0020] A machine learning-based nutritional diet recommendation and evaluation method of the present invention, the method specifically includes the following steps:

[0021] Step 1. Obtain user information, including personal information and physical condition information;

[0022] Step 2, sending the collected user information to the intelligent data processing center;

[0023] Step 3. Integrate and process the received user information through the intelligent data processing center. In the intelligent data processing center module, the method of deep learning is adopted, and the collected personal information and physical condition information of a large number of people in different situations are used as input, and the daily intake of protein, carbohydrates, dietary fiber, water, etc. , fat and calcium, potassium, sodium, magnesium, iron...

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Abstract

The invention discloses a nutritional diet recommending and evaluating method based on machine learning, and the method comprises the steps: 1, obtaining user information which comprises personal information and physical condition information; 2, transmitting the collected user information to an intelligent data processing center; 3, enabling an intelligent data processing center to carry out theintegration and processing of the received user information; 4, generating a reference nutrient ADI (acceptable daily intake) corresponding to the user information, and generating a nutritional diet recipe which is suitable for a user; 5, recording the actual diet information of the user; 6, converting the actual diet information of the user into a specific nutrient ADI, and carrying out the dataconversion through the querying of health data; 7, carrying out the estimation of the diet of the user according to the reference nutrient ADI and the actual nutrient ADI. Through combining with the physical condition of the user, the method provides the targeted nutritional diet recommendation services for the user, and achieves a purpose of guiding and assisting the user to have a healthy diet.

Description

technical field [0001] The invention relates to the technical fields of medical diet, machine learning and intelligent data analysis, in particular to a method for recommending nutritional diet recipes and diet evaluation based on machine learning. Background technique [0002] With the gradual improvement of living standards, people's dietary requirements are also gradually increasing. Nowadays, people's dietary requirements are not only to have enough food and drink, but also to pursue the quality and health of the diet. Now, there are more and more programs and applications that provide users with healthy diet information and recipe recommendations. These applications and programs provide users with a large amount of nutritional diet information and popularize nutritional knowledge to users. However, these programs and applications Most of them do not take into account the different physical conditions of users, so the recipes and nutritional information they recommend ar...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H20/60
Inventor 刘昱蒋淮
Owner TIANJIN UNIV
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