WO2019169930A1

WO2019169930A1 - Method and device for determining feasibility of food material selection, and cooking appliance

Info

Publication number: WO2019169930A1
Application number: PCT/CN2018/122848
Authority: WO
Inventors: 马晓媛; 张智; 张旭凯; 徐晓斐
Original assignee: 美的集团股份有限公司
Priority date: 2018-03-07
Filing date: 2018-12-21
Publication date: 2019-09-12
Also published as: CN108461123A

Abstract

A method and device for determining feasibility of food material selection, a cooking appliance, and a computer storage medium. The method comprises: according to the content of various nutrient elements of a target food material, and an average value of standard values of preset content at all grades of the nutrient elements, determining the weight of the nutrient elements of the target food material (101); according to the content of the nutrient elements of the target food material, and the standard values of the preset content at all grades of the nutrient elements, determining membership grades of the nutrient elements of the target food material to various nutrition evaluation grades, wherein each nutrition evaluation grade corresponds to a content standard value of one grade (102); and according to the weight of the nutrient elements of the target food material, and the membership grades of the nutrient elements of the target food material to the various nutrition evaluation grades, determining feasibility of selecting the target food material on the various nutrition evaluation grades (103). Therefore, the feasibility of food material selection can be objectively and comprehensively determined.

Description

Method, device and cooking appliance for determining feasibility of selecting ingredients

Cross-reference to related applications

This application claims the priority of the invention titled "a method, device and cooking appliance for determining the feasibility of the selection of ingredients" and the Chinese patent application number "201810186554.3" submitted by Midea Group Co., Ltd. on March 07, 2018. And the full text is incorporated herein by reference.

Technical field

The invention relates to a material selection technology, and relates to a method, a device, a cooking appliance and a computer storage medium for determining the feasibility of selecting a food material.

Background technique

At present, for a given nutritional evaluation standard, when evaluating whether to select a certain food, the logic of simple judgment is usually adopted, that is, the evaluation result can only be yes or no; however, since nutrition has multiple dimensions (for example, it may include A variety of nutrients, the above-mentioned method of evaluating whether to select a certain food material through a certain indicator can not achieve a comprehensive evaluation of the nutrition of the food material, and thus the objectivity and accuracy of the evaluation method are low.

Summary of the invention

In order to solve the above technical problem, the embodiments of the present invention are intended to provide a method, a device, a cooking appliance and a computer storage medium for determining the feasibility of selecting a food material, aiming at solving the problem of low objectivity and accuracy of the existing food material evaluation method. .

The embodiment of the invention provides a method for determining the feasibility of selecting a foodstuff, the method comprising:

Determining the weight of each nutrient of the target foodstuff according to the content of each nutrient of the target foodstuff and the average value of the preset level content standard values of each nutrient;

Determining, according to the content of each nutrient of the target foodstuff, and the preset level standard value of each nutrient, the degree of membership of each nutrient of the target foodstuff for each nutritional evaluation level, wherein each nutrient The evaluation level corresponds to a standard content value of one level;

The feasibility of selecting the target food material at each nutritional evaluation level is determined according to the weight of each nutrient of the target food material and the degree of membership of each nutrient of the target food material for each evaluation level.

In the above solution, the weight of each nutrient according to the target food material, and the degree of membership of each nutrient of the target food material to each evaluation grade, determining the feasibility of selecting the target food material at each nutritional evaluation level ,include:

Normalizing the weight of each nutrient of the target food material to obtain a normalized weight of each nutrient of the target food material;

Based on the normalized weight of each nutrient of the target foodstuff, and the degree of membership of each nutrient of the target foodstuff for each evaluation grade, the feasibility of selecting the target foodstuff at each nutritional evaluation level is determined.

In the above solution, the normalized weight of each nutrient according to the target foodstuff, and the degree of membership of each nutrient of the target foodstuff for each evaluation grade are determined, and the target foodstuff is selected for each nutritional evaluation grade. The degree of feasibility, including:

The normalized weights of the various nutrients of the target food material are represented by a fuzzy matrix, and the membership degrees of the various nutrients of the target food material to the respective evaluation grades are represented by a fuzzy matrix;

Performing a composite operation of the fuzzy matrix on the normalized weights of the various nutrients of the target foodstuff represented by the fuzzy matrix and the membership degrees of the various nutrients of the target foodstuff represented by the fuzzy matrix to the respective evaluation grades The operation result is used to indicate the feasibility of selecting the target food material at each nutritional evaluation level.

In the above solution, the weight of each nutrient of the target foodstuff is determined according to the content of each nutrient of the target foodstuff, and the average value of the preset level standard values of each nutrient, including:

The weight of each nutrient of the target food material is divided by the average value of the preset standard level values corresponding to one nutrient, and the weight of the corresponding one nutrient of the target food material is obtained.

In the above solution, determining the membership degree of each nutrient of the target food material for each nutritional evaluation level according to the content of each nutrient of the target food material and the preset level standard value of each nutrient. ,include:

And determining the degree of membership of the corresponding nutrient of the target food material to each nutritional evaluation level according to the proximity of the content of each nutrient of the target food material to the preset standard value of the corresponding level of the corresponding nutrient.

An embodiment of the present invention also provides an apparatus for determining the feasibility of selecting a foodstuff, the apparatus comprising: a processor and a memory configured to store a computer program executable on the processor;

When the processor is configured to run the computer program, the following steps are performed:

In the above solution, the processor is specifically configured to perform the following steps when the computer program is run:

The embodiment of the invention also proposes a cooking appliance, which comprises any of the above-mentioned devices for determining the feasibility of selecting the foodstuff.

Embodiments of the present invention also provide a computer storage medium having stored thereon a computer program that, when executed by a processor, implements any of the steps of a method for determining the feasibility of selecting a food material.

In the embodiment of the present invention, the weight of each nutrient of the target foodstuff is determined according to the content of each nutrient of the target foodstuff and the average value of the preset level content standard values of each nutrient; according to the target The content of each nutrient of the foodstuff, and the preset standard level value of each nutrient, determining the degree of membership of each nutrient of the target foodstuff for each nutritional evaluation grade, wherein each nutritional evaluation grade corresponds to one a standard value of the content of the grade; determining the feasible degree of selecting the target foodstuff in each nutritional evaluation level according to the weight of each nutrient of the target foodstuff and the degree of membership of each nutrient of the target foodstuff to each evaluation grade In this way, the degree of membership can be used to describe the degree of certain nutritional evaluation grades of the ingredients, and the boundary ambiguity that exists objectively when evaluating the optionalness of the ingredients can be considered, so that the method for determining the feasibility of selecting the ingredients is more objective and scientific; In the process of selecting the feasibility of the ingredients, comprehensive consideration of each individual nutrient The role.

DRAWINGS

1 is a flow chart of a method for determining the feasibility of selecting a food material according to an embodiment of the present invention;

2 is a schematic view showing the composition and structure of an apparatus for determining the feasibility of selecting a food material according to an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described in the following with reference to the accompanying drawings.

In the embodiment of the present invention, the foodstuff may have a plurality of nutrients, and the nutrient refers to a chemical component in the food that can provide energy to the human body, constitute body and tissue repair, and has physiological regulation function. The various substances needed to maintain human health and provide growth, development and labor are called nutrients. Nutrients include, but are not limited to, proteins, lipids, sugars, vitamins, water, inorganic salts (minerals), dietary fibers (cellulose), non-essential nutrients, and the like.

It should be noted that the embodiments of the present invention can be implemented based on specific m kinds of nutrients, and the specific m kinds of nutrients can be preset according to actual needs, and m is a natural number greater than 1; for example, the embodiments of the present invention can be based on carbohydrates, fats, and Three nutrients of protein are realized.

Based on the contents of the above-described nutrients, the following examples are proposed.

First embodiment

The first embodiment of the present invention provides a method for determining the feasibility of selecting a foodstuff. FIG. 1 is a flow chart of a method for determining the feasibility of selecting a foodstuff according to an embodiment of the present invention. As shown in FIG. 1, the process may include:

Step 101: determining a weight of each nutrient of the target food material according to an average value of each nutrient of the target food material and an average value of a preset level standard content value of each nutrient;

It can be understood that the content of each nutrient of the target food material is well-known and fixed; in one example, the content of each nutrient of the target food material is determined by determining the quality of each nutrient when the quality of the target food material is the standard quality. The mass, for example, the standard mass may be 100 g, 200 g, or the like.

In practical applications, an n-level content standard value may be set in advance for each nutrient, and n is an integer greater than 1; here, the standard value of each level content may be the same as the unit of the content of each nutrient of the target food material; exemplarily, The standard value of the level 4 content can be set for the carbohydrate substance, and the standard value of the level 4 content is 100 mg, 200 mg, 300 mg, and 400 mg in descending order.

Illustratively, an optional embodiment of the present step is: dividing the content of each nutrient of the target food material by an average value of a preset level standard value corresponding to one nutrient, and obtaining the The weight of the target ingredient corresponding to a nutrient.

That is to say, the weighting of each nutrient of the target food can be calculated by the following formula:

Wherein, W _j represents the excess index of the jth nutrient based on the average standard, that is, the weight of the jth nutrient of the target food; C _j represents the content of the jth nutrient of the target food (ie, the jth nutrient of the target food) The measured concentration); S _j represents the arithmetic mean of the standard values of the preset levels of the jth nutrient of the target food.

Optionally, after the weight of each nutrient of the target food material is obtained, the weight of each nutrient of the target food material may be normalized to obtain a normalized weight of each nutrient of the target food material.

Here, the formula for normalizing the weight of each nutrient of the target food is:

Wherein, V _j represents the normalized weight of the jth nutrient of the target food;

Obviously, it can be seen that the normalized weights of the jth nutrient of the target food are between 0 and 1.

Step 102: determining a membership degree of each nutrient of the target food material for each nutritional evaluation level according to a content of each nutrient of the target food material and a preset standard value of each level of the nutrient, wherein Each nutritional evaluation level corresponds to a standard content value of one level.

Since nutrition has multiple dimensions and there is a concept of comprehensive judgment, the concept of membership can be used to describe fuzzy nutrition judgment. The degree of membership can refer to the degree of certain standards of a certain thing; for a given ingredient A, the content of five nutrients For [Ax1, Ax2, Ax3, Ax4, Ax5], if there is another ingredient B, the corresponding five nutrient contents are [Bx1, Bx2, Bx3, Bx4, Bx5]. When a certain level is reached, the acceptance degree of A is replaced. Can reach 95%.

The membership degree can be represented by a membership function, and the membership function can make a linear function or a nonlinear function; in a typical example, the membership degree ranges from [0, 1].

It can be seen that for the n-level content standard value, n nutritional evaluation levels respectively corresponding to the n-level content standard values need to be set in advance.

Optionally, determining, according to the proximity of the content of each nutrient of the target food material to the preset standard level value of the corresponding nutrient, determining the subordinate of the corresponding nutrient of the target food material to each nutritional evaluation level degree.

In one example, the preset level content standard value for each nutrient may include: a primary level standard value to an nth level standard value arranged in order from small to large.

When the content of the jth nutrient of the target food is less than or equal to the standard value of the first level of the jth nutrient, the degree of membership of the jth nutrient of the target food to the first nutritional evaluation level is determined to be 1, and the target food is The membership of the jth nutrient to the second nutritional evaluation level to the nth nutritional evaluation level is 0;

For example, the preset standard levels of the fat of the target food are: 1.0 mg, 2.0 mg, and 4.0 mg, respectively. If the fat content of the target food is 0.5 mg, the fat of the target food is determined for the first nutritional evaluation level. The degree of membership is 1, and the fat of the target food has a membership degree of 0 from the second nutritional evaluation level to the third nutritional evaluation level.

When the content of the jth nutrient of the target food is greater than or equal to the standard value of the nth nutrient of the jth nutrient, determining the degree of membership of the jth nutrient of the target food to the nth nutritional evaluation level is 1, and the target food is The degree of membership of the jth nutrient for the first nutritional evaluation level to the n-1th nutritional evaluation level is 0;

For example, the predetermined standard levels of the protein of the target food are: 200 mg, 300 mg, and 500 mg, respectively. If the protein content of the target food is 800 mg, the degree of membership of the fat of the target food to the third nutritional evaluation level is determined. 1. The fat of the target food has a membership degree of 0 from the first nutritional evaluation level to the second nutritional evaluation level.

When the content of the jth nutrient of the target food is greater than the standard value of the first level of the jth nutrient, and is less than the standard value of the nth level of the jth nutrient, first, the content standard of the jth nutrient In the value, the two-level standard value closest to the content of the j-th nutrient of the target food is determined, and the determined two-level standard value is recorded as D ₀ and D ₁ from small to large, respectively.

Then, the degree of membership of the jth nutrient of the target food to the nutritional evaluation level of D _{0 and the} nutritional evaluation level of D ₁ can be determined according to the following formula:

Wherein C _j represents the content of the jth nutrient of the target food, Y ₀ represents the degree of membership of the jth nutrient of the target food to the nutritional evaluation level of D ₀ , and Y ₁ represents the jth nutrient of the target food to which D ₁ belongs The degree of membership of the nutritional evaluation level.

Finally, it is determined that the j-th nutrient of the target food has a membership degree of 0 for the remaining nutritional evaluation levels.

For example, the preset standard levels of the protein of the target food are: 200 mg, 300 mg, and 500 mg, respectively. If the protein content of the target food is 420 mg, according to the above formula, the fat of the target food can be determined for the second nutritional evaluation. The membership degree of the grade is 0.4, the degree of membership of the fat of the target food to the third nutritional evaluation grade is 0.6, and the degree of membership of the fat of the target food to the first nutritional evaluation grade is 0.

In another example, if n is equal to 2, ie, there are only two nutritional evaluation levels, the preset two-level standard values of the j-th nutrient are respectively recorded as X ₀ and X ₁ , and the j-th species of the target food is The content of nutrients is recorded as X;

If X ₀ <X <X _1, the j th nutrient certain ingredients of X ₀ Rank ordinary nutrition membership Y ₀ and j th nutrient certain ingredients of membership Y ₁ relevant to nutrition evaluation level X _1, respectively, for:

If X≥X _1, subsection j kinds of nutrients goal ingredients membership of the Y ₀ X ₀ Rank belongs nutrition equals 0, j th goal of nutrients ingredients for membership Y belongs nutritional assessment level equal to X ₀ ₁ 1 .

If X≤X _0, the j th goal of nutrients ingredients for membership Y X ₀ ₀ Rank of your nutrition is equal to 1, j th goal of nutrients ingredients for membership Y belongs nutritional assessment level equal to X ₀ ₁ 0 .

It should be noted that, in the embodiment of the present invention, the execution order of step 101 and step 102 is not limited. For example, the two may be executed simultaneously, or step 101 may be performed before step 102 or may be performed after step 102. .

Step 103: Determine, according to the weight of each nutrient of the target food material, and the degree of membership of each nutrient of the target food material to each evaluation grade, the feasibility of selecting the target food material at each nutritional evaluation level.

Optionally, determining, according to the normalized weight of each nutrient of the target food material, and the membership degree of each nutrient of the target food material to each evaluation grade, determining the target food material for each nutritional evaluation grade Feasibility.

Optionally, the normalized weights of the various nutrients of the target foodstuff may be represented by a fuzzy matrix, and the membership degrees of the various nutrients of the target foodstuff to the respective evaluation grades are represented by a fuzzy matrix;

Here, the compound operation of the fuzzy matrix is similar to the general matrix multiplication. The difference is that the multiplication of the two numbers in the matrix multiplication is replaced by "·", and the operator can be recorded as "∧"; Add the two numbers in the matrix multiplication to "+" and take the big one as "and", and the operator can be called "∨".

It can be understood that the normalized weights of various nutrients of the target foodstuff are between 0 and 1, and the degree of membership of each nutrient of the target foodstuff for each evaluation grade is between 0 and 1, thus, It is convenient to realize the composite operation of the fuzzy matrix.

That is, a first fuzzy matrix can be constructed, the first fuzzy matrix is a matrix of size 1*m, and the elements of the first row and the jth column of the first fuzzy matrix are the normalized weights of the jth nutrient of the target food. It is also possible to construct a second fuzzy matrix, which is a matrix of size m*n, and the elements of the jth row and the i-th column of the second fuzzy matrix are the j-th nutrient of the target food for the i-th nutritional evaluation level. Membership.

After obtaining the first fuzzy matrix and the second fuzzy matrix, the first fuzzy matrix and the second fuzzy matrix are combined to obtain a matrix of size 1*n. In the matrix of size 1*n, the ith column The element indicates the feasibility of selecting the target ingredient for the i-th nutritional evaluation level.

Fuzzy mathematics theory is a science developed in recent years. The food in the catering is replaced by heat and nutritive value, which has high ambiguity. Therefore, the nutrition can be comprehensively evaluated through the compound operation of the fuzzy matrix described above. Breaking the previous method of using only one certain indicator to achieve a more objective and scientific evaluation of the availability of ingredients

In practical applications, steps 101 to 103 can all be implemented by a processor.

When applying the method for determining the feasibility of the selection of the foodstuffs according to the embodiment of the present invention, the following advantages are obtained: First, the degree of membership can be used to describe the degree of a certain nutritional evaluation grade of the foodstuff, and the objective existence limit can be considered when evaluating the optionalness of the edible material. The ambiguity makes the method of determining the feasibility of the selection of ingredients more objective and scientific. Secondly, in the process of determining the feasibility of the selection of ingredients, the role of each individual nutrient is considered comprehensively; specifically, the individual nutrients are considered comprehensively. The role in the overall availability of the ingredients is evaluated; for example, for each nutrient, a corresponding weight can be set.

Second embodiment

In order to further embodies the object of the present invention, further exemplification will be made on the basis of the first embodiment of the present invention.

In the embodiment of the present invention, the method for determining the availability of the food material can be described by the following algorithm model:

The nutrition evaluation grade of the ingredients is used to evaluate the availability of the ingredients. The number of grades in the nutritional evaluation grade can be recorded as n, that is, there are n grades; suppose a certain food has m evaluation factors (nutrients), m evaluation factors The jth evaluation factor (nutrients) in (nutrients) can be written as u _j , j = 1, 2...m. There are n nutritional evaluation levels for each evaluation factor, and the i-th nutritional evaluation level of the n nutritional evaluation levels can be recorded as V _i , i=1, 2, . . . In one example, n nutritional evaluation levels may be referred to as I, II, III, IV, V, and the like in sequence.

The individual nutritional evaluation levels of the respective evaluation factors can be expressed in Table 1.

Table 1

Table 1 reflects the relationship between each nutrient and the level of nutritional evaluation. This relationship is expressed by the degree of membership and is a fuzzy relationship; that is, in Table 1, R _ji represents the jth evaluation factor (nutrient) pair The membership degree of i nutritional evaluation levels (the jth evaluation factor may be the probability of the i-th nutritional evaluation level), and each nutritional evaluation level of each evaluation factor may also be represented by a fuzzy matrix R.

It can be understood that the functions of various nutrients are different, and the status of various nutrients in determining the availability of ingredients is also different. On this basis, the weights of various nutrients can be set according to the target ingredients. Illustratively, the sum of the weights of the various nutrients of the target foodstuff is 1.

Here, the matrix A can be used to indicate the weight of various nutrients of the target foodstuff, that is,

A=(a ₁ ... a _m )

Where a _j represents the weight of the jth nutrient of the target food, exemplarily,

It can be seen that the matrix A and the matrix R are two fuzzy matrices. Therefore, for the matrix A and the matrix R, the matrix B can be obtained by the composite operation of the fuzzy matrix, that is, there is B=A·R, where “.” indicates Composite operation of fuzzy matrices.

Here, each element of the matrix B may respectively indicate the degree of feasibility of selecting the target food material at each nutritional evaluation level (that is, the degree of each nutritional evaluation level in a certain evaluation of the food material).

For example, the matrix B can be expressed as: B = (b ₁ ... b _n ). In the matrix B, the feasible degree of selecting the target food material at the first nutritional evaluation level is b ₁ , and the first nutritional evaluation level is selected. The feasible degree of the target ingredients is b ₂ , and so on, according to the matrix B, the feasibility of selecting the target ingredients at each nutritional evaluation level can be comprehensively evaluated.

The method of determining the availability of foodstuffs of the present invention is illustrated below by a specific application example.

In this application example, m is equal to 3, 3 nutrients (evaluation factors) are carbohydrates, fats, and proteins, respectively; n is equal to 5, and 5 nutritional evaluation levels are respectively recorded as I, II, III, IV, and V.

Table 2 can be derived from the standard values of the respective nutrient levels of each nutrient (standard values of preset levels of each nutrient) and the actual contents of various nutrients of the target food.

Table 2

The unit of each numerical value in Table 2 may be mg; it can be seen that in Table 2, the standard value of the preset first level content corresponding to the carbohydrate is set to the preset standard value of the fifth level content of 20 mg, 50 mg, 100 mg, respectively. , 200mg, 400mg; the corresponding standard value of the first level of the fat corresponding to the standard level of the fifth level is 0.5mg, 1.0mg, 2.0mg, 5.0mg, 10.0mg; the corresponding level 1 of the protein The standard values of the content to the preset level 5 are 50 mg, 100 mg, 200 mg, 500 mg, and 1000 mg, respectively; the actual contents of the target foods are 38 mg, 0.7 mg, and 14 mg, respectively.

Thereafter, according to the description of the first embodiment of the present invention, the degree of membership of each nutrient of the target food material for each nutritional evaluation level can be obtained. Taking fat as an example, the content of the target food material is 0.7, adjacent to the fat content of the target food material. The two-level standard values are X ₀ = 0.5 (Class I) and X ₁ = 1.0 (Class II), which can be derived: the degree of membership of the target food fat to the first nutritional evaluation level (Class I) Y _I for:

The degree of membership of the target food fat to the second nutritional evaluation level (Level III) Y _II is:

That is to say, for fat alone, the target food belongs to the first nutritional evaluation level with a membership of 60%, and the target food belongs to the second nutritional evaluation level with a membership of 40%. Obviously, for fat alone, the target ingredients cannot be classified into the third nutritional evaluation level to the fifth nutritional evaluation level, so the target ingredients belong to the third nutritional evaluation level to the fifth nutritional evaluation level. Both are 0.

In the same way, the degree of membership of the carbohydrate of the target food for each nutritional evaluation level and the degree of membership of the protein of the target food to each nutritional evaluation level can be obtained. A fuzzy matrix R having a size of 3*5 can be constructed by using the various nutrients of the target ingredients for the membership degree of each nutritional evaluation level.

Here, it is also possible to derive the normalized weights of various nutrients of the target food material according to the description of the first embodiment of the present invention.

Specifically, according to the description of the first embodiment of the present invention, for the carbohydrate, the arithmetic mean value of the preset standard value of the 5-level content is: 154, as can be seen from Table 2, the value 154 is between the third nutrition. Between the evaluation grade and the fourth nutritional evaluation grade, the arithmetic mean of the preset standard value of the 5-level content of fat is 3.7, and the arithmetic mean value of the standard 5-level standard value of the protein is 370.

The target food has a carbohydrate weight of 0.25, the target food has a fat weight of 0.19, and the target food has a protein weight of 0.05.

According to the calculation formula of the normalized weights of various nutrients of the target foods described above, it can be concluded that the normalized weight of the carbohydrate of the target food is 0.52, and the normalized weight of the fat of the target food is 0.40, the target food. The normalized weight of the protein is 0.08.

In the present embodiment, the calculation process of the normalized weights of various nutrients of the target food material can be explained using Table 3.

项目project	II	IIII	IIIIII	IVIV	VV	C _j C _j	S _j S _j	W _j W _j	V _j V _j
碳水化合物Carbohydrate	2020	5050	100100	200200	400400	3838	154154	0.250.25	0.520.52
脂肪fat	0.50.5	1.01.0	2.02.0	5.05.0	10.010.0	0.70.7	3.73.7	0.190.19	0.400.40
蛋白质protein	5050	100100	200200	500500	10001000	1414	370370	0.040.04	0.080.08

table 3

In Table 3, a column corresponding to C _j represents the content of carbohydrate, fat and protein of the target food (ie, the measured concentration of the jth nutrient of the target food), and a column corresponding to S _j represents the carbohydrate and fat of the target food, respectively. And the arithmetic mean of the standard values of the preset levels of the protein, the column corresponding to W _j represents the weight of the carbohydrate, fat and protein of the target food, respectively, and the column corresponding to V _j represents the carbohydrate, fat and protein of the target food respectively. Normalized weights.

Using the normalized weights of carbohydrates, fats, and proteins of the target ingredients, a matrix A of size 1*3 can be constructed, A = (0.52, 0.40, 0.08).

For the matrix A and the matrix R, the matrix B can be obtained by the composite operation of the fuzzy matrix, that is, there is B=A·R. According to the composite operation method of the fuzzy matrix described above, the first column element b _{1 of the} matrix B is equal to (0.52). ∧0.40)∨(0.40∧0.60)∨(0.08∧1.0), since “∧” means that the small one is “product”, “∨” means that the largest one is “and”, thus b ₁ =0.40∨0.40 ∨0.08=0.4;

Similarly, the second column element b ₂ of matrix B is equal to 0.52, and the third column element b ₃ , the fourth column element b ₄ and the fifth column element b _{5 of} matrix B are both equal to 0, then:

B=(0.4,0.52,0,0,0)

It can be seen that the comprehensive evaluation results of the optional ingredients of the target ingredients include: the feasible degree of selecting the target ingredients in the first nutritional evaluation level is 0.4, and the feasible degree of selecting the target ingredients in the second nutritional evaluation level is 0.52, the first The feasible degree of selecting the target ingredients from the three nutritional evaluation levels to the fifth nutritional evaluation level is 0.

Third embodiment

Based on the method for determining the feasibility of selecting a foodstuff proposed in the foregoing embodiment, the third embodiment of the present invention provides a device for determining the feasibility of selecting a foodstuff.

2 is a schematic structural diagram of a device for determining the feasibility of selecting a food material according to an embodiment of the present invention. As shown in FIG. 2, the device 20 includes a processor 201 and a memory 202 configured to store a computer program capable of running on a processor; among them,

The feasibility of selecting the target food material at each nutritional evaluation level is determined according to the weight of each nutrient of the target food material and the degree of membership of each nutrient of the target food material to each evaluation level.

In practical applications, the memory 202 may be a volatile memory, such as a random access memory (RAM), or a non-volatile memory, such as a read only memory. (ROM, Read-Only Memory), flash memory, hard disk (HDD, Hard Disk Drive) or solid state drive (SSD, Solid-State Drive); or a combination of the above types of memory, and to the processor 201 Provide instructions and data.

The processor 201 may be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), or a Programmable Logic Device (PLD). At least one of a Programmable Logic Device, a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor. It is to be understood that, for different devices, the electronic device configured to implement the second processor function may be other, which is not specifically limited in the embodiment of the present invention.

Illustratively, the processor 201 is specifically configured to perform the following steps when the computer program is run:

Fourth embodiment

A fourth embodiment of the present invention provides a cooking appliance comprising any one of the third embodiments for determining the feasibility of selecting a foodstuff.

Fifth embodiment

The fifth embodiment of the present invention provides a computer readable medium based on the same technical concept as the foregoing embodiment; the technical solution of the foregoing embodiment is essentially or a part contributing to the prior art or all of the technical solution. Or a portion may be embodied in the form of a software product stored in a computer readable storage medium, including instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) or processing The apparatus performs all or part of the steps of the method described in this embodiment. The foregoing storage medium includes: a U disk, a mobile hard disk, a read only memory (ROM), a RAM, a magnetic disk, or an optical disk, and the like, which can store program codes.

Specifically, the computer program instruction corresponding to the method for determining the feasibility of selecting the food material in the embodiment may be stored on a storage medium such as an optical disk, a hard disk, a U disk, or the like, and the storage medium is feasible with a certain selection of the food material. When the computer program instructions corresponding to the method are read or executed by an electronic device, the at least one processor is caused to perform the steps described in any one of the foregoing embodiments of the present invention for determining the feasibility of selecting the food material.

The serial numbers of the embodiments of the present invention are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk, The optical disc includes a number of instructions for causing a terminal (which may be a cell phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present invention.

The embodiments of the present invention have been described above with reference to the drawings, but the present invention is not limited to the specific embodiments described above, and the specific embodiments described above are merely illustrative and not restrictive, and those skilled in the art In the light of the present invention, many forms may be made without departing from the spirit and scope of the invention as claimed.

Claims

A method for determining the feasibility of selecting a foodstuff, wherein the method comprises:

Determining the weight of each nutrient of the target foodstuff according to the content of each nutrient of the target foodstuff and the average value of the preset level content standard values of each nutrient;

Determining, according to the content of each nutrient of the target foodstuff, and the preset level standard value of each nutrient, the degree of membership of each nutrient of the target foodstuff for each nutritional evaluation level, wherein each nutrient The evaluation level corresponds to a standard content value of one level;

The feasibility of selecting the target food material at each nutritional evaluation level is determined according to the weight of each nutrient of the target food material and the degree of membership of each nutrient of the target food material for each evaluation level.
The method according to claim 1, wherein said weighting of each nutrient according to said target food material, and the degree of membership of each nutrient of said target food material for each evaluation level are determined for each nutritional evaluation level The feasibility of the target foodstuff includes:

Normalizing the weight of each nutrient of the target food material to obtain a normalized weight of each nutrient of the target food material;

Based on the normalized weight of each nutrient of the target foodstuff, and the degree of membership of each nutrient of the target foodstuff for each evaluation grade, the feasibility of selecting the target foodstuff at each nutritional evaluation level is determined.
The method according to claim 2, wherein said individualized weights of each nutrient according to said target foodstuff, and the degree of membership of each nutrient of said target foodstuff for each evaluation grade are determined for each nutritional evaluation The degree of feasibility of selecting the target ingredients in the grade, including:

The normalized weights of the various nutrients of the target food material are represented by a fuzzy matrix, and the membership degrees of the various nutrients of the target food material to the respective evaluation grades are represented by a fuzzy matrix;

Performing a composite operation of the fuzzy matrix on the normalized weights of the various nutrients of the target foodstuff represented by the fuzzy matrix, and the membership degrees of the various nutrients of the target foodstuff represented by the fuzzy matrix to the respective evaluation grades The operation result is used to indicate the feasibility of selecting the target food material at each nutritional evaluation level.
The method according to claim 1, wherein said each nutrient of said target food is determined based on an average of a content of each nutrient of the target foodstuff and an average value of a predetermined level of each of said nutrients Weights, including:

The weight of each nutrient of the target food material is divided by the average value of the preset standard level values corresponding to one nutrient, and the weight of the corresponding one nutrient of the target food material is obtained.
The method according to claim 1, wherein said determining each nutrient pair of said target food material based on a content of each nutrient of said target food material and a predetermined level standard value value of said each nutrient The membership of each nutritional evaluation level, including:

And determining the degree of membership of the corresponding nutrient of the target food material to each nutritional evaluation level according to the proximity of the content of each nutrient of the target food material to the preset standard value of the corresponding level of the corresponding nutrient.
An apparatus for determining the viability of a foodstuff selection, wherein the apparatus comprises: a processor and a memory configured to store a computer program executable on the processor;

When the processor is configured to run the computer program, the following steps are performed:

Determining the weight of each nutrient of the target foodstuff according to the content of each nutrient of the target foodstuff and the average value of the preset level content standard values of each nutrient;

Determining, according to the content of each nutrient of the target foodstuff, and the preset level standard value of each nutrient, the degree of membership of each nutrient of the target foodstuff for each nutritional evaluation level, wherein each nutrient The evaluation level corresponds to a standard content value of one level;

The feasibility of selecting the target food material at each nutritional evaluation level is determined according to the weight of each nutrient of the target food material and the degree of membership of each nutrient of the target food material for each evaluation level.
The apparatus of claim 6 wherein said processor is specifically configured to: when said computer program is executed, perform the following steps:

Normalizing the weight of each nutrient of the target food material to obtain a normalized weight of each nutrient of the target food material;

Based on the normalized weight of each nutrient of the target foodstuff, and the degree of membership of each nutrient of the target foodstuff for each evaluation grade, the feasibility of selecting the target foodstuff at each nutritional evaluation level is determined.
The apparatus of claim 7, wherein the processor is specifically configured to perform the following steps when the computer program is executed:

The normalized weights of the various nutrients of the target food material are represented by a fuzzy matrix, and the membership degrees of the various nutrients of the target food material to the respective evaluation grades are represented by a fuzzy matrix;

Performing a composite operation of the fuzzy matrix on the normalized weights of the various nutrients of the target foodstuff represented by the fuzzy matrix and the membership degrees of the various nutrients of the target foodstuff represented by the fuzzy matrix to the respective evaluation grades The operation result is used to indicate the feasibility of selecting the target food material at each nutritional evaluation level.
The apparatus of claim 6 wherein said processor is specifically configured to: when said computer program is executed, perform the following steps:

The weight of each nutrient of the target food material is divided by the average value of the preset standard level values corresponding to one nutrient, and the weight of the corresponding one nutrient of the target food material is obtained.
The apparatus of claim 6 wherein said processor is specifically configured to: when said computer program is executed, perform the following steps:

And determining the degree of membership of the corresponding nutrient of the target food material to each nutritional evaluation level according to the proximity of the content of each nutrient of the target food material to the preset standard value of the corresponding level of the corresponding nutrient.
A cooking appliance, wherein the cooking appliance comprises the apparatus for determining the feasibility of selecting a foodstuff according to any one of claims 6 to 10.
A computer storage medium having stored thereon a computer program, wherein the computer program is executed by a processor to perform the steps of the method of any one of claims 1 to 5.