Component production optimization method and system for target composition

Abstract

The invention relates to the technical field of composition production, in particular to a component production optimization method and system of a target composition. The method comprises the following steps: acquiring an image set of each target composition sample in a target composition sample set; acquiring the wrinkle variation in the image corresponding to each target composition sample; obtaining a mapping relation between the mass percent of the components in the target composition and the wrinkle variation in the image; obtaining a priority value corresponding to each candidate density in a candidate density set of the target composition according to the mapping relationship; and determining the candidate density with the maximum priority value in the candidate density set as the target density, and determining the mass percentage of the components in the target composition with the density being the target density and the minimum wrinkle variation in the corresponding image as the target mass percentage of the components in the target composition. According to the invention, the efficiency of composition research, development and production and the accuracy of composition evaluation can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of composition production, and in particular to a method and system for optimizing the production of components of a target composition. Background Art

[0002] In the development and production of drug compositions, ingredients such as AKG (α-ketoglutarate), SOD (superoxide dismutase), and niacinamide are often used in combination. Compositions containing AKG, SOD, and niacinamide have important applications in anti-wrinkle treatments. Currently, traditional methods for optimizing the production of these compositions often rely on manual experimentation and subjective evaluation. This reliance on manual experimentation involves conducting numerous experiments with varying component weight percentages to determine the anti-wrinkle effect of each composition, consuming significant time and costs. Traditional methods rely on subjective evaluation, which involves manually observing changes in the skin of test subjects to determine anti-wrinkle effects. However, due to the high degree of subjectivity in manual observation, it is difficult to accurately quantify changes in wrinkles before and after using the composition. This reliance on manual experimentation and subjective evaluation compromises the efficiency of drug composition development and production, as well as the accuracy of composition evaluations. Summary of the Invention

[0003] The object of the present invention is to provide a method and system for optimizing the production of components of a target composition, so as to improve the efficiency of composition research and development and production and the accuracy of composition evaluation.

[0004] According to a first aspect of the present invention, there is provided a method for optimizing the production of components of a target composition, the method comprising the following steps: An image set of each target composition sample in a target composition sample set is obtained; the target composition sample set includes several target composition samples, components of any target composition sample include AKG, SOD and niacinamide, and the mass percentages of the components in different target composition samples are different; the image set of any target composition sample includes image pairs of several experimental objects, and the image pair of any experimental object includes a control image and an experimental image of the experimental object.

[0005] The amount of wrinkle changes in the image corresponding to each target composition sample is obtained based on the image set of each target composition sample in the target composition sample set; the amount of wrinkle changes in the image corresponding to any target composition sample is the average amount of wrinkle changes in the images of all experimental objects corresponding to the target composition sample, and the amount of wrinkle changes in the image of any experimental object is the difference between the wrinkle ratio of the experimental image of the experimental object and the wrinkle ratio of the control image.

[0006] A mapping relationship between the mass percentage of the components in the target composition and the wrinkle change in the image is obtained based on the wrinkle change in the image of each target composition sample in the target composition sample set; the mass percentage of AKG, the mass percentage of SOD, and the mass percentage of niacinamide in the mapping relationship are independent variables, and the wrinkle change in the image is the dependent variable.

[0007] The priority value corresponding to each candidate density in the candidate density set of the target composition is obtained according to the mapping relationship; the candidate density set includes several candidate densities, and the priority value corresponding to any candidate density is obtained according to the wrinkle change amount in the image corresponding to the target composition with the density of the candidate density.

[0008] The candidate density with the largest priority value in the candidate density set is determined as the target density, and the mass percentage of the component in the target composition with the target density and the smallest wrinkle change in the corresponding image is determined as the target mass percentage of the component in the target composition.

[0009] Furthermore, obtaining the priority value corresponding to each candidate density in the candidate density set of the target composition according to the mapping relationship includes: The wrinkle variation in the image corresponding to the target composition having a density of a specified candidate density is obtained according to the mapping relationship; the specified candidate density is any candidate density in the candidate density set.

[0010] An average value of wrinkle variation in an image corresponding to a target composition having a density of a designated candidate density is determined as a first value of the designated candidate density.

[0011] The variance of the wrinkle variation in the image corresponding to the target composition having the density of the designated candidate density is determined as a second value of the designated candidate density.

[0012] The priority value of the candidate density is obtained according to the first value and the second value of the specified candidate density; the priority value of the specified candidate density is negatively correlated with the first value and the second value of the specified candidate density.

[0013] Furthermore, obtaining the priority value of the candidate density according to the first value and the second value of the candidate density includes: obtaining the priority value of the candidate density according to the first value of the candidate density, the first preset weight, the second value of the candidate density, and the second preset weight.

[0014] Furthermore, the process of obtaining the target composition having a density of a specified candidate density includes: The mass percentage range of each component in the target composition is obtained, and the mass percentage corresponding to each level of any component is obtained based on the mass percentage range of any component and the preset level number.

[0015] An orthogonal table that matches the number of components and the preset number of levels included in the target composition is selected to construct a component ratio combination matrix.

[0016] The target compositions are prepared by combining the matrices according to the component ratios, and the density of each group of target compositions is obtained.

[0017] A target composition having a density of a specified candidate density is screened from the prepared target compositions.

[0018] Furthermore, setting the mass percentage corresponding to each level of any component based on the mass percentage range of the component and the preset number of levels includes: dividing the mass percentage range of any component equally according to the preset number of levels to obtain the mass percentage corresponding to each level of the component.

[0019] Furthermore, obtaining a mapping relationship between the mass percentage of a component in a target composition and the amount of wrinkle change in an image based on the amount of wrinkle change in an image of each target composition sample in the target composition sample set includes: setting a preset fitting function, performing fitting based on the mass percentage of a component in each target composition sample in the target composition sample set and the corresponding amount of wrinkle change in an image, and determining a function expression obtained by fitting as a mapping relationship between the mass percentage of a component in a target composition and the amount of wrinkle change in an image.

[0020] Furthermore, the preset fitting function is a multivariate quadratic polynomial function.

[0021] Furthermore, obtaining the amount of wrinkle change in the image corresponding to the target composition having a density of a specified candidate density according to the mapping relationship includes: substituting the mass percentage of the component in each target composition having a density of the specified candidate density into the mapping relationship, and obtaining the amount of wrinkle change in the image corresponding to each target composition having a density of the specified candidate density.

[0022] Furthermore, the wrinkle ratio of the experimental image of any experimental subject is the ratio of wrinkle pixels to the total number of pixels in the experimental image of the experimental subject, and the wrinkle ratio of the control image of any experimental subject is the ratio of wrinkle pixels to the total number of pixels in the control image of the experimental subject.

[0023] According to a second aspect of the present invention, a component production optimization system for a target composition is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned component production optimization method for the target composition when executing the computer program.

[0024] The present invention has at least the following beneficial effects: The present invention obtains a mapping relationship between the mass percentage of components in a target composition and the amount of wrinkle variation in an image based on the mass percentage of each component in a target composition sample set and the amount of wrinkle variation in an image. Based on this mapping relationship, the present invention can quickly obtain the priority value corresponding to each candidate density in a set of candidate densities for the target composition, eliminating the need for extensive experimentation to verify the amount of wrinkle variation in an image corresponding to each candidate density. This reduces the cost of blind trial and error and improves the efficiency of optimizing the production of target composition components. Furthermore, the present invention can automatically obtain the amount of wrinkle variation in experimental subjects using image processing technology. Compared to manual observation of experimental subjects, the wrinkle variation obtained by the present invention is more objective and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 This is a flow chart of a component production optimization method for a target composition provided in Example 1 of the present invention; Figure 2 A flowchart of a process for obtaining a priority value corresponding to each candidate density in a set of candidate densities of a target composition provided in the first embodiment of the present invention; Figure 3 This is a flow chart of a process for obtaining a target composition having a density of a specified candidate density provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] Example 1: According to the present invention, a method for optimizing the production of components of a target composition is provided, such as Figure 1 As shown, the method includes the following steps: S100, obtaining an image set of each target composition sample in a target composition sample set; the target composition sample set includes several target composition samples, components of any target composition sample include AKG, SOD and niacinamide, and the mass percentages of the components in different target composition samples are different; the image set of any target composition sample includes image pairs of several experimental objects, and the image pair of any experimental object includes a control image and an experimental image of the experimental object.

[0029] In this embodiment, the sum of the mass percentages of the components of the target composition is 1, and the mass percentages of the components of different target composition samples are different.

[0030] In this embodiment, target composition samples containing different mass percentages of components are obtained, and image data after each target composition sample is applied to an experimental subject is obtained. Any target composition sample is applied to multiple experimental subjects to improve the accuracy of the target composition assessment; the image set of each experimental sample includes a control image and an experimental image, wherein the control image is an image of the experimental subject before the target composition is applied, and the experimental image is an image of the experimental subject after the target composition is applied. Moreover, the control image and the experimental subject of the same subject are shot under the same conditions, including lighting, shooting angle, and shooting distance; the shooting time intervals of the control images and experimental images of different experimental subjects are equal, and the experimental subjects subjected to different target composition samples have the same characteristics, including age, skin quality, and initial state of wrinkles. As a result, the acquired image data is objective and comparable, and can truly reflect the impact of different component ratios on wrinkle changes, providing reliable raw data for subsequent analysis.

[0031] S200, obtaining the amount of wrinkle changes in the image corresponding to each target composition sample based on the image set of each target composition sample in the target composition sample set; the amount of wrinkle changes in the image corresponding to any target composition sample is the average amount of wrinkle changes in the images of all experimental objects corresponding to the target composition sample, and the amount of wrinkle changes in the image of any experimental object is the difference between the wrinkle ratio of the experimental image of the experimental object and the wrinkle ratio of the control image.

[0032] In this embodiment, the wrinkle variation in the image corresponding to the target composition sample is usually a negative value. The smaller the wrinkle variation in the image corresponding to a target composition sample is, the better the anti-wrinkle effect of the target composition is.

[0033] As a specific embodiment, the wrinkle ratio of the experimental image of any experimental subject is the ratio of wrinkle pixels to the total number of pixels in the experimental image of the experimental subject, and the wrinkle ratio of the control image of any experimental subject is the ratio of wrinkle pixels to the total number of pixels in the control image of the experimental subject. Those skilled in the art will recognize that any prior art method for obtaining wrinkle pixels in an image falls within the scope of protection of the present invention. As a specific embodiment, image processing is performed on the control image and experimental image of any experimental subject, using techniques such as edge detection, threshold segmentation, and morphological operations to identify and extract wrinkle regions in the image. The ratio of the number of wrinkle pixels to the total number of pixels in the control image is then calculated to obtain the wrinkle ratio of the control image. Similarly, the wrinkle ratio of the experimental image can also be obtained.

[0034] This embodiment utilizes image processing technology to convert wrinkle changes, which are difficult to accurately quantify with the naked eye, into calculable pixel ratio differences. Average values are then calculated to reduce the impact of individual differences in individual experimental subjects, making the results more representative. This embodiment thus achieves objective and precise quantification of wrinkle changes, avoids the errors of subjective manual evaluation, and provides an accurate quantitative indicator for the subsequent establishment of a mapping relationship between component mass percentage and anti-wrinkle effect.

[0035] S300, obtaining a mapping relationship between the mass percentage of components in the target composition and the amount of wrinkle change in the image based on the amount of wrinkle change in the image of each target composition sample in the target composition sample set; the mass percentage of AKG, the mass percentage of SOD, and the mass percentage of niacinamide in the mapping relationship are independent variables, and the amount of wrinkle change in the image is a dependent variable.

[0036] This embodiment performs fitting based on the mass percentage of the components in each target composition sample and the corresponding wrinkle variation, establishing a mapping relationship with the component percentage in the target composition as the independent variable and the corresponding wrinkle variation in the image as the dependent variable. As a specific embodiment, obtaining the mapping relationship between the mass percentage of the components in the target composition and the wrinkle variation in the image based on the wrinkle variation in the image of each target composition sample in the target composition sample set includes: setting a preset fitting function, performing fitting based on the mass percentage of the components in each target composition sample in the target composition sample set and the corresponding wrinkle variation in the image, and determining the resulting fitted function expression as the mapping relationship between the mass percentage of the components in the target composition and the wrinkle variation in the image.

[0037] In one specific embodiment, a multivariate quadratic polynomial function is pre-set as the fitting function. The component mass percentages of each target composition sample and the corresponding wrinkle variation in the image are substituted into this multivariate quadratic polynomial function. Using a fitting method such as the least squares method, the coefficients are calculated to obtain the fitted function expression, i.e., the target mapping relationship. This multivariate quadratic polynomial function can effectively describe the potential nonlinear relationship between the mass percentages of multiple components and the corresponding wrinkle variation in the image. By fitting and establishing a mathematical model, it is possible to predict the anti-wrinkle effect from the component ratios.

[0038] The mapping relationship constructed in this embodiment can more accurately reflect the intrinsic relationship between the mass percentage of each component in the target composition and the anti-wrinkle effect, providing a basis for subsequent prediction of the wrinkle change under different component ratios, and facilitating efficient component optimization.

[0039] S400, obtaining a priority value corresponding to each candidate density in a candidate density set of the target composition according to the mapping relationship; the candidate density set includes a plurality of candidate densities, and the priority value corresponding to any candidate density is obtained according to an amount of wrinkle variation in an image corresponding to the target composition having the candidate density.

[0040] In this embodiment, the candidate density set of the target composition is preset and known.

[0041] In this embodiment, based on the established mapping relationship, the priority value corresponding to each candidate density in the candidate density set is calculated to quantitatively evaluate the priority value of each candidate density, providing a basis for screening the optimal target density. As a specific implementation method, Figure 2 As shown, obtaining the priority value corresponding to each candidate density in the candidate density set of the target composition according to the mapping relationship includes: S410 , obtaining, according to the mapping relationship, a wrinkle variation in an image corresponding to a target composition having a density of a specified candidate density; the specified candidate density is any candidate density in a candidate density set.

[0042] In this embodiment, obtaining the amount of wrinkle change in the image corresponding to the target composition having a density of the specified candidate density according to the mapping relationship includes: substituting the mass percentage of the component in each target composition having a density of the specified candidate density into the mapping relationship, and obtaining the amount of wrinkle change in the image corresponding to each target composition having a density of the specified candidate density.

[0043] As a specific embodiment, Figure 3 As shown, the process of obtaining the target composition with a density of a specified candidate density includes: S411, obtaining the mass percentage range of each component in the target composition, and obtaining the mass percentage corresponding to each level of any component based on the mass percentage range of any component and a preset number of levels.

[0044] In this embodiment, the mass percentage range of each component in the target composition is preset and known.

[0045] Optionally, the preset level number is an empirical value. It should be understood that the larger the preset level number is, the more mass percentages are obtained by dividing the mass percentage of each component, and the greater the number of target compositions configured subsequently.

[0046] As a specific embodiment, setting the mass percentage corresponding to each level of any component based on the mass percentage range of the component and the preset number of levels includes: equally dividing the mass percentage range of the component according to the preset number of levels to obtain the mass percentage corresponding to each level of the component. It should be understood that equally dividing the mass percentage range of the component by the preset number of levels yields discrete mass percentages of the preset number of levels, with any two adjacent mass percentages being equidistant.

[0047] S412, selecting an orthogonal table that matches the number of components and the preset number of levels included in the target composition to construct a component ratio combination matrix.

[0048] Those skilled in the art know that orthogonal arrays are prior art and will not be described in detail here.

[0049] S413, preparing target compositions by combining the matrix according to the component ratios, and obtaining the density of each group of target compositions.

[0050] In this embodiment, if the sum of the mass percentages of the components of a certain combination in the component ratio combination matrix is not 1, the mass percentages of the components of the combination can be adjusted proportionally so that the sum of the mass percentages of the components of the combination after adjustment is 1.

[0051] Those skilled in the art know that the process of obtaining density is an existing technology and will not be described in detail here.

[0052] S414 , screening a target composition having a density of a specified candidate density from the prepared target compositions.

[0053] Based on S411 - S414 , this embodiment can obtain a target composition having a density that is a specified candidate density.

[0054] S420 : Determine an average value of wrinkle variation in the image corresponding to the target composition having a density equal to the designated candidate density as a first value of the designated candidate density.

[0055] In this embodiment, the first value of the designated candidate density is used to reflect the average anti-wrinkle effect of the target composition at the designated candidate density.

[0056] S430 : Determine the variance of the wrinkle variation in the image corresponding to the target composition having the density of the designated candidate density as a second value of the designated candidate density.

[0057] In this embodiment, the second value of the designated candidate density is used to reflect the difference in anti-wrinkle effects of different mass percentage combinations under the designated candidate density.

[0058] It should be understood that if the second value of the designated candidate density is small, it indicates that the wrinkle variation in the image corresponding to the target composition with different mass percentage combinations at the designated candidate density is relatively small. If the mass percentages of the components are adjusted while the density remains unchanged, the resulting anti-wrinkle effect will be relatively similar to that before the adjustment, which helps ensure the stability of the anti-wrinkle effect of the target composition. Adjusting the mass percentages of the components while the density remains unchanged is intended to ensure that the volume of the target composition of the same mass remains unchanged after the adjustment, which has the advantage of not requiring changes to the container in which the target composition is stored.

[0059] S440: Obtain a priority value of the candidate density according to the first value and the second value of the specified candidate density; the priority value of the specified candidate density is negatively correlated with both the first value and the second value of the specified candidate density.

[0060] In this embodiment, the smaller the first value of the candidate density, the smaller the second value of the candidate density, the better the anti-wrinkle effect of the target composition at the candidate density and the smaller the difference in anti-wrinkle effect of different mass percentage combinations at the candidate density. As a specific embodiment, obtaining the priority value of the candidate density according to the first value and the second value of the candidate density includes: obtaining the priority value of the candidate density according to the first value of the candidate density, the first preset weight, the second value of the candidate density, and the second preset weight. Optionally, the first preset weight and the second preset weight are empirical values, the sum of the first preset weight and the second preset weight is 1, and the priority value of the candidate density is: -w1×a-w2×b, where w1 and w2 are the first preset weight and the second preset weight, respectively, a is the first value of the specified candidate density after normalization, and b is the second value of the specified candidate density after normalization. Those skilled in the art know that the normalization process is a prior art and will not be described in detail here.

[0061] This example utilizes an orthogonal experimental design method to efficiently obtain sample compositions of varying densities. This method predicts their anti-wrinkle effects through mapping relationships, and then comprehensively evaluates candidate densities based on both effectiveness and variability, combining mean and variance. Weightings are assigned to reflect the different emphasis on effectiveness and variability. This method thus achieves a quantitative assessment and ranking of candidate densities, avoiding the randomness and inefficiency of traditional trial-and-error methods. It can quickly identify and screen candidate densities with good average anti-wrinkle effects and minimal variability.

[0062] S500, determining the candidate density with the largest priority value in the candidate density set as the target density, and determining the mass percentage of the component in the target composition having the target density and the smallest wrinkle change in the corresponding image as the target mass percentage of the component in the target composition.

[0063] In this example, the priority values of each candidate density in the candidate density set are compared, and the candidate density with the highest priority value is found and determined as the target density. For all target compositions with the target density, the wrinkle variation in their corresponding images is compared. The composition with the smallest wrinkle variation is selected, and the mass percentage of the components in this composition is determined as the target mass percentage of the target composition.

[0064] In this embodiment, the candidate density with the highest priority value comprehensively considers both the average anti-wrinkle effect and the variability in anti-wrinkle effect among different mass percentage combinations. Based on this, the composition with the smallest wrinkle variation is selected, ensuring that the final component mass percentages achieve optimal anti-wrinkle effect. Thus, this embodiment, through a dual screening mechanism of maximum priority value and minimum wrinkle variation, determines the preferred component mass percentages for the target composition, achieving optimal anti-wrinkle effect and facilitating adjustment of component mass percentages during production. (When the mass percentages of the components in the target composition are at the target mass percentages, if the density of the target composition is maintained, the resulting anti-wrinkle effect after adjustment is minimal, ensuring the adjusted anti-wrinkle effect.) This achieves the goal of optimizing the production of the target composition.

[0065] This embodiment obtains a mapping relationship between the mass percentage of components in the target composition and the wrinkle variation in the image, based on the mass percentage of each component in the target composition sample set and the wrinkle variation in the image. Based on this mapping relationship, this embodiment can quickly obtain the priority value corresponding to each candidate density in the target composition candidate density set, eliminating the need for extensive experimentation to verify the wrinkle variation in the image corresponding to each candidate density. This reduces the cost of blind trial and error and improves the efficiency of optimizing the production of target composition components. Furthermore, this embodiment can automatically obtain the wrinkle variation of experimental subjects based on image processing technology. Compared with manual observation of experimental subjects, the wrinkle variation obtained by this embodiment is more objective and accurate.

[0066] Example 2: This embodiment provides a component production optimization system for a target composition, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented: An image set of each target composition sample in a target composition sample set is obtained; the target composition sample set includes several target composition samples, components of any target composition sample include AKG, SOD and niacinamide, and the mass percentages of the components in different target composition samples are different; the image set of any target composition sample includes image pairs of several experimental objects, and the image pair of any experimental object includes a control image and an experimental image of the experimental object.

[0067] The amount of wrinkle changes in the image corresponding to each target composition sample is obtained based on the image set of each target composition sample in the target composition sample set; the amount of wrinkle changes in the image corresponding to any target composition sample is the average amount of wrinkle changes in the images of all experimental objects corresponding to the target composition sample, and the amount of wrinkle changes in the image of any experimental object is the difference between the wrinkle ratio of the experimental image of the experimental object and the wrinkle ratio of the control image.

[0068] A mapping relationship between the mass percentage of the components in the target composition and the wrinkle change in the image is obtained based on the wrinkle change in the image of each target composition sample in the target composition sample set; the mass percentage of AKG, the mass percentage of SOD, and the mass percentage of niacinamide in the mapping relationship are independent variables, and the wrinkle change in the image is the dependent variable.

[0069] The priority value corresponding to each candidate density in the candidate density set of the target composition is obtained according to the mapping relationship; the candidate density set includes several candidate densities, and the priority value corresponding to any candidate density is obtained according to the wrinkle change amount in the image corresponding to the target composition with the density of the candidate density.

[0070] The candidate density with the largest priority value in the candidate density set is determined as the target density, and the mass percentage of the component in the target composition with the target density and the smallest wrinkle change in the corresponding image is determined as the target mass percentage of the component in the target composition.

[0071] Although some specific embodiments of the present invention have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A method for optimizing the production of components of a target composition, characterized in that: The method comprises the following steps: Obtaining an image set of each target composition sample in a target composition sample set; the target composition sample set includes a plurality of target composition samples, wherein components of any target composition sample include AKG, SOD, and niacinamide, and the mass percentages of the components in different target composition samples are different; the image set of any target composition sample includes image pairs of a plurality of experimental objects, wherein the image pair of any experimental object includes a control image and an experimental image of the experimental object; Obtaining, based on the image set of each target composition sample in the target composition sample set, an amount of wrinkle variation in an image corresponding to each target composition sample; the amount of wrinkle variation in an image corresponding to any target composition sample is the average amount of wrinkle variation in images of all experimental subjects corresponding to the target composition sample; and the amount of wrinkle variation in an image of any experimental subject is the difference between the wrinkle ratio of the experimental image of the experimental subject and the wrinkle ratio of the control image; Obtaining a mapping relationship between the mass percentage of the components in the target composition and the amount of wrinkle change in the image of each target composition sample in the target composition sample set based on the amount of wrinkle change in the image; wherein the mass percentage of AKG, the mass percentage of SOD, and the mass percentage of niacinamide in the mapping relationship are independent variables, and the amount of wrinkle change in the image is a dependent variable; Obtaining a priority value corresponding to each candidate density in a candidate density set of the target composition according to the mapping relationship; the candidate density set includes a plurality of candidate densities, and the priority value corresponding to any candidate density is obtained based on a wrinkle variation in an image corresponding to the target composition having the candidate density; The candidate density with the largest priority value in the candidate density set is determined as the target density, and the mass percentage of the component in the target composition with the target density and the smallest wrinkle change in the corresponding image is determined as the target mass percentage of the component in the target composition.

2. The component production optimization method of the target composition according to claim 1, characterized in that: Obtaining the priority value corresponding to each candidate density in the candidate density set of the target composition according to the mapping relationship includes: Obtaining, according to the mapping relationship, a wrinkle variation in an image corresponding to a target composition having a density of a specified candidate density; the specified candidate density being any candidate density in a candidate density set; determining an average value of wrinkle variation in an image corresponding to a target composition having a density of a specified candidate density as a first value of the specified candidate density; determining a variance of a wrinkle variation in an image corresponding to a target composition having a density of a specified candidate density as a second value of the specified candidate density; The priority value of the candidate density is obtained according to the first value and the second value of the specified candidate density; the priority value of the specified candidate density is negatively correlated with the first value and the second value of the specified candidate density.

3. The component production optimization method of the target composition according to claim 2, characterized in that: Acquiring a priority value of the candidate density according to the first value and the second value of the candidate density includes acquiring the priority value of the candidate density according to the first value of the candidate density, a first preset weight, the second value of the candidate density, and the second preset weight.

4. The component production optimization method of the target composition according to claim 2, characterized in that: The process of obtaining a target composition having a density of a specified candidate density includes: Obtaining a mass percentage range of each component in the target composition, and obtaining a mass percentage corresponding to each level of any component based on the mass percentage range and a preset number of levels of the component; An orthogonal table matching the number of components and the preset number of levels included in the target composition is selected to construct a component ratio combination matrix; preparing target compositions by combining the matrix according to the component ratios, and obtaining the density of each group of target compositions; A target composition having a density of a specified candidate density is screened from the prepared target compositions.

5. The component production optimization method of the target composition according to claim 4, characterized in that: Setting the mass percentage corresponding to each level of any component based on the mass percentage range of the component and the preset number of levels includes: dividing the mass percentage range of any component equally according to the preset number of levels to obtain the mass percentage corresponding to each level of the component.

6. The component production optimization method of the target composition according to claim 1, characterized in that: Obtaining a mapping relationship between the mass percentage of a component in a target composition and the amount of wrinkle change in an image based on the amount of wrinkle change in an image of each target composition sample in a target composition sample set includes: setting a preset fitting function, performing fitting based on the mass percentage of a component in each target composition sample in the target composition sample set and the corresponding amount of wrinkle change in the image, and determining a function expression obtained by the fitting as a mapping relationship between the mass percentage of a component in the target composition and the amount of wrinkle change in the image.

7. The method for optimizing component production of the target composition according to claim 6, characterized in that: The default fitting function is a multivariate quadratic polynomial function.

8. The method for optimizing component production of the target composition according to claim 2, characterized in that: Obtaining the amount of wrinkle change in the image corresponding to the target composition having a density of the specified candidate density according to the mapping relationship includes: substituting the mass percentage of the component in each target composition having a density of the specified candidate density into the mapping relationship, and obtaining the amount of wrinkle change in the image corresponding to each target composition having a density of the specified candidate density.

9. The method for optimizing component production of a target composition according to claim 1, wherein: The wrinkle ratio of the experimental image of any experimental subject is the ratio of wrinkle pixels to the total number of pixels in the experimental image of the experimental subject, and the wrinkle ratio of the control image of any experimental subject is the ratio of wrinkle pixels to the total number of pixels in the control image of the experimental subject.

10. A component production optimization system for a target composition, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the component production optimization method of the target composition according to any one of claims 1 to 9 is implemented.

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