Optimization control method and system applied to touch screen display of multiple systems

Abstract

The invention relates to a touch screen display optimization control method and system applied to multiple systems, and the method comprises the steps: M1, a user presses a touch screen, obtains the data information of the historical working state of the touch screen, obtains the data information of a pressure signal of the touch screen and the data information of the brightness value of each pixel point of the touch screen in real time, and sends the data information to the user; and predicting the brightness value of each pixel point of the touch screen by adopting a decision tree prediction algorithm based on the touch screen pressure signal and the brightness values of the pixel points to obtain predicted data information of the brightness value of each pixel point of the touch screen. According to the method, the brightness value of each pixel point of the touch screen can be accurately controlled and adjusted, the accuracy of man-machine interaction is improved, the whole optimization process can be adaptively adjusted according to different systems, and the interaction applicability of the touch screen and the use experience of a user are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of touch screen display, and in particular to an optimized control method and system for touch screen display applied to multiple systems. Background Art

[0002] With the continuous development of technology, touch screen displays are mostly used for operation in human-computer interaction interfaces, bringing a lot of convenience to people's lives. However, during the touch display interaction process, the brightness of each pixel point on the touch screen will be fed back according to the pressure signals of different touch points. If the display brightness value of the touch screen is too large or too small during the feedback process, it is easy to generate display errors, resulting in unsmooth human-computer interaction or individual display errors, thereby reducing the accuracy of human-computer interaction. Therefore, how to precisely control the display of the touch screen has become an urgent problem for us to solve. Summary of the Invention

[0003] In view of the above problems, the present invention provides an optimized control method and system for touch screen display applied to multiple systems, which can not only precisely control and adjust the brightness values of each pixel point on the touch screen, improve the accuracy of human-computer interaction, but also the entire optimization process can be adaptively adjusted according to different systems, improving the applicability of touch screen interaction and the user experience.

[0004] To achieve the above object and other related objects, the technical solutions provided by the present invention are as follows:

[0005] An optimized control method for touch screen display applied to multiple systems, the method includes:

[0006] M1. The user presses the touch screen, obtains the data information of the historical working state of the touch screen, and simultaneously obtains the data information of the pressure signal of the touch screen and the data information of the brightness value of each pixel point on the touch screen in real time;

[0007] M2. Based on the data information of the pressure signal of the touch screen and the data information of the historical working state of the touch screen, use a decision tree prediction algorithm based on the pressure signal of the touch screen and the brightness value of the pixel point to predict the brightness value of each pixel point on the touch screen, and obtain the data information of the brightness value of each pixel point on the predicted touch screen;

[0008] M3. Based on the data information of the brightness value of each pixel point on the predicted touch screen and the data information of the brightness value of each pixel point on the touch screen, use an improved Newton-Raphson optimization algorithm to optimize the brightness value of each pixel point on the touch screen, and obtain the data information of the brightness value of each pixel point on the optimized touch screen;

[0009] M4. Based on the data information of the brightness values of each pixel of the optimized touch screen, construct an overall display effect evaluation function W of the touch screen, evaluate the overall display effect of the touch screen, and obtain the data information of the evaluation value of the overall display effect of the touch screen.

[0010] Further, in step M2, the use of the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of the pixel to predict the brightness value of each pixel of the touch screen includes:

[0011] M21. Based on the data information of the historical working state of the touch screen, extract the data information of the historical pressure signal of the touch screen and the data information of the brightness values of each pixel of the touch screen corresponding thereto;

[0012] M22. Based on the data information of the historical pressure signal of the touch screen and the data information of the brightness values of each pixel of the touch screen corresponding thereto, establish a joint probability function Q of the pressure signal and the pixel brightness value of the touch screen,

[0013]

[0014] where x is the data information of the historical pressure signal of the touch screen, y is the data information of the brightness values of each pixel of the touch screen corresponding thereto, and α1, α2, and α3 are any constant coefficients between 0 and 1, and deduce the joint probability of the pressure signal and the pixel brightness value of the touch screen to obtain the data information of the joint probability of the pressure signal and the pixel brightness value of the touch screen;

[0015] M23. Based on the data information of the joint probability of the pressure signal and the pixel brightness value of the touch screen and the data information of the pressure signal of the touch screen, establish a prediction function R of the brightness value of the pixel of the touch screen,

[0016]

[0017] where z is the data information of the pressure signal of the touch screen, r is the data information of the joint probability of the pressure signal and the pixel brightness value of the touch screen, and β1, β2, and β3 are weight coefficients, and predict the brightness values of each pixel of the touch screen to obtain the data information of the brightness values of each pixel of the predicted touch screen.

[0018] Further, the constraint conditions for the weight coefficients β1, β2, and β3 are

[0019]

[0020] Further, the constraint function f for the constant coefficients α1, α2, and α3 is

[0021]

[0022] Among them, the value range of the constraint function f is (0, 1).

[0023] Further, in step M3, the optimization of the brightness values of each pixel point of the touch screen by using the improved Newton - Raphson optimization algorithm includes:

[0024] M31. Based on the data information of the brightness values of each pixel point of the predicted touch screen and the data information of the brightness values of each pixel point of the touch screen, establish the solution space function P of the pixel points of the touch screen,

[0025]

[0026] Among them, h1 is the data information of the brightness values of each pixel point of the predicted touch screen, h2 is the data information of the brightness values of each pixel point of the touch screen, and δ1, δ2, and δ3 are penalty factors, which characterize the solution space of the pixel points of the touch screen to obtain the solution space data set of the pixel points of the touch screen;

[0027] M32. Based on the solution space data set of the pixel points of the touch screen, initialize the population and establish the fitness function S of the population individuals,

[0028]

[0029] Among them, p is the solution space data set of the pixel points of the touch screen, and the fitness values of the population individuals are deduced to obtain the data information of the fitness values of the population individuals;

[0030] M33. Based on the data information of the fitness values of the population individuals, establish the target optimization function F,

[0031]

[0032] Among them, g is the data information of the fitness values of the population individuals, and λ1, λ2, and λ3 are gradient change factors, which predict the brightness values of each pixel point of the touch screen to obtain the data information of the brightness values of each pixel point of the predicted touch screen.

[0033] Further, the gradient change factors λ1, λ2, and λ3 are,

[0034]

[0035] Among them, g is the data information of the fitness values of the population individuals.

[0036] Further, the penalty factors δ1, δ2, and δ3 are,

[0037]

[0038] Among them, h1 is the data information of the brightness values of each pixel point of the predicted touch screen, and h2 is the data information of the brightness values of each pixel point of the touch screen.

[0039] Further, the overall display effect evaluation function W of the touch screen is

[0040]

[0041] Among them, p i is the data information of the brightness value of the i-th pixel point of the optimized touch screen, and n is the sample size.

[0042] Further, the method further includes:

[0043] M5. Based on the data information of the evaluation value of the overall display effect of the touch screen, set a preset threshold. If the evaluation value of the overall display effect of the touch screen is less than the preset threshold, it does not meet the requirements, and return to step M3. If the evaluation value of the overall display effect of the touch screen is greater than the preset threshold, it meets the requirements, and the display screen performs data display.

[0044] To achieve the above object and other related objects, the present invention also provides an optimized control system for touch screen display applied to multiple systems, including a computer device, which is programmed or configured to execute the steps of any one of the optimized control methods for touch screen display applied to multiple systems.

[0045] The present invention has the following positive effects:

[0046] 1. By using the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of the pixel point to predict the brightness value of each pixel point of the touch screen, and combining with the improved Newton-Raphson optimization algorithm to optimize the brightness value of each pixel point of the touch screen, the present invention can not only accurately control and adjust the brightness value of each pixel point of the touch screen, improve the accuracy of human-computer interaction, but also the entire optimization process can be adaptively adjusted according to different systems, improving the applicability of touch screen interaction and the user experience.

[0047] 2. By constructing the overall display effect evaluation function W of the touch screen, evaluating the overall display effect of the touch screen, and setting a preset threshold to judge the overall display effect of the touch screen, the present invention can not only further improve the display effect of the touch screen, but also can monitor the process of human-computer interaction in real time, improving the quality of human-computer interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a schematic flow chart of the method of the present invention;

[0049] Figure 2 This is a schematic flowchart of the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of pixel points of the present invention;

[0050] Figure 3 This is a schematic flowchart of the improved Newton - Raphson optimization algorithm of the present invention. Detailed implementation manners

[0051] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, descriptions of well - known functions and structures are omitted below for clarity and conciseness.

[0052] Embodiment 1: As Figure 1 shown, an optimization control method for touch screen display applied to multiple systems, the method includes:

[0053] M1. The user presses the touch screen, obtains the data information of the historical working state of the touch screen, and real - time obtains the data information of the pressure signal of the touch screen and the data information of the brightness value of each pixel point of the touch screen;

[0054] M2. Based on the data information of the pressure signal of the touch screen and the data information of the historical working state of the touch screen, use the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of pixel points to predict the brightness value of each pixel point of the touch screen, and obtain the data information of the brightness value of each pixel point of the predicted touch screen;

[0055] M3. Based on the data information of the brightness value of each pixel point of the predicted touch screen and the data information of the brightness value of each pixel point of the touch screen, use the improved Newton - Raphson optimization algorithm to optimize the brightness value of each pixel point of the touch screen, and obtain the data information of the brightness value of each pixel point of the optimized touch screen;

[0056] M4. Based on the data information of the brightness value of each pixel point of the optimized touch screen, construct an overall display effect evaluation function W of the touch screen, evaluate the overall display effect of the touch screen, and obtain the data information of the evaluation value of the overall display effect of the touch screen.

[0057] In this embodiment, as Figure 2 shown, in step M2, the using the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of pixel points to predict the brightness value of each pixel point of the touch screen includes:

[0058] M21. Extract the data information of the historical pressure signal of the touch screen and the data information of the brightness values of each pixel point of the touch screen corresponding thereto based on the data information of the historical working state of the touch screen.

[0059] M22. Based on the data information of the historical pressure signal of the touch screen and the data information of the brightness values of each pixel point of the touch screen corresponding thereto, establish a joint probability function Q of the pressure signal and the pixel point brightness value of the touch screen.

[0060]

[0061] Wherein, x is the data information of the historical pressure signal of the touch screen, y is the data information of the brightness values of each pixel point of the touch screen corresponding thereto, α1, α2, and α3 are any constant coefficients between 0 and 1, and the joint probability of the pressure signal and the pixel point brightness value of the touch screen is deduced to obtain the data information of the joint probability of the pressure signal and the pixel point brightness value of the touch screen.

[0062] M23. Based on the data information of the joint probability of the pressure signal and the pixel point brightness value of the touch screen and the data information of the pressure signal of the touch screen, establish a prediction function R of the brightness value of the pixel point of the touch screen.

[0063]

[0064] Wherein, z is the data information of the pressure signal of the touch screen, r is the data information of the joint probability of the pressure signal and the pixel point brightness value of the touch screen, β1, β2, and β3 are weight coefficients, and the brightness values of each pixel point of the touch screen are predicted to obtain the data information of the brightness values of each pixel point of the predicted touch screen.

[0065] In this embodiment, the decision tree is an algorithm that classifies and predicts new data by calculating historical data. Simply put, the decision tree algorithm analyzes historical data with known results, finds features in the data, and predicts new data results based on this.

[0066] In this embodiment, the constraint conditions for the weight coefficients β1, β2, and β3 are

[0067]

[0068] In this embodiment, the constraint function f for the constant coefficients α1, α2, and α3 is

[0069]

[0070] Wherein, the value range of the constraint function f is (0, 1).

[0071] In this embodiment, as Figure 3 shown, in step M3, the optimization of the brightness values of each pixel of the touch screen by using the improved Newton-Raphson optimization algorithm includes:

[0072] M31. Based on the data information of the brightness values of each pixel of the predicted touch screen and the data information of the brightness values of each pixel of the touch screen, establish the solution space function P of the pixels of the touch screen,

[0073]

[0074] where h1 is the data information of the brightness values of each pixel of the predicted touch screen, h2 is the data information of the brightness values of each pixel of the touch screen, and δ1, δ2, and δ3 are penalty factors, which characterize the solution space of the pixels of the touch screen to obtain the solution space data set of the pixels of the touch screen;

[0075] M32. Based on the solution space data set of the pixels of the touch screen, initialize the population and establish the fitness function S of the population individuals,

[0076]

[0077] where p is the solution space data set of the pixels of the touch screen, and the fitness values of the population individuals are deduced to obtain the data information of the fitness values of the population individuals;

[0078] M33. Based on the data information of the fitness values of the population individuals, establish the target optimization function F,

[0079]

[0080] where g is the data information of the fitness values of the population individuals, and λ1, λ2, and λ3 are gradient change factors, which predict the brightness values of each pixel of the touch screen to obtain the data information of the brightness values of each pixel of the predicted touch screen.

[0081] In this embodiment, the gradient change factors λ1, λ2, and λ3 are

[0082]

[0083] where g is the data information of the fitness values of the population individuals.

[0084] In this embodiment, the penalty factors δ1, δ2, and δ3 are

[0085]

[0086]

[0087] Among them, h1 is the data information of the brightness values of each pixel point of the touch screen after prediction, and h2 is the data information of the brightness values of each pixel point of the touch screen.

[0088] In this embodiment, by using the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of the pixel point to predict the brightness value of each pixel point of the touch screen, and combining with the improved Newton-Raphson optimization algorithm to optimize the brightness value of each pixel point of the touch screen, not only can the brightness value of each pixel point of the touch screen be accurately controlled and adjusted, improving the accuracy of human-computer interaction, but also the entire optimization process can be adaptively adjusted according to different systems, improving the applicability of touch screen interaction and the user experience.

[0089] Embodiment 2: On the basis of an optimization control method for touch screen display applied to multiple systems in Embodiment 1, the present invention will be further described and explained below.

[0090] As Figure 1 shown, an optimization control method for touch screen display applied to multiple systems, the method includes:

[0091] M1. The user presses the touch screen, obtains the data information of the historical working state of the touch screen, and simultaneously obtains the data information of the pressure signal of the touch screen and the data information of the brightness values of each pixel point of the touch screen in real time;

[0092] M2. Based on the data information of the pressure signal of the touch screen and the data information of the historical working state of the touch screen, use the decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of the pixel point to predict the brightness values of each pixel point of the touch screen, and obtain the data information of the brightness values of each pixel point of the predicted touch screen;

[0093] M3. Based on the data information of the brightness values of each pixel point of the predicted touch screen and the data information of the brightness values of each pixel point of the touch screen, use the improved Newton-Raphson optimization algorithm to optimize the brightness values of each pixel point of the touch screen, and obtain the data information of the brightness values of each pixel point of the optimized touch screen;

[0094] M4. Based on the data information of the brightness values of each pixel point of the optimized touch screen, construct an overall display effect evaluation function W of the touch screen, evaluate the overall display effect of the touch screen, and obtain the data information of the evaluation value of the overall display effect of the touch screen.

[0095] In this embodiment, the overall display effect evaluation function W of the touch screen is

[0096]

[0097] Among them, p i is the data information of the brightness value of the i-th pixel point of the optimized touch screen, and n is the sample size.

[0098] In this embodiment, the method further includes:

[0099] M5. Based on the data information of the evaluation value of the overall display effect of the touch screen, set a preset threshold. If the evaluation value of the overall display effect of the touch screen is less than the preset threshold, it does not meet the requirements, and return to step M3. If the evaluation value of the overall display effect of the touch screen is greater than the preset threshold, it meets the requirements, and the display screen performs data display.

[0100] In this embodiment, the present invention provides an optimized control system for touch screen display applied to multiple systems, including a computer device, which is programmed or configured to execute the steps of any one of the optimized control methods for touch screen display applied to multiple systems.

[0101] In this embodiment, the system includes:

[0102] A data acquisition module, configured to acquire the data information of the historical working state of the touch screen, and acquire in real time the data information of the pressure signal of the touch screen and the data information of the brightness value of each pixel point of the touch screen;

[0103] A prediction module for each pixel point of the touch screen, connected to the data acquisition module, and configured to predict the brightness value of each pixel point of the touch screen by using a decision tree prediction algorithm based on the pressure signal and the brightness value of the pixel point of the touch screen, so as to obtain the data information of the brightness value of each pixel point of the predicted touch screen;

[0104] An optimization module for each pixel point of the touch screen, connected to the prediction module for each pixel point of the touch screen, and configured to optimize the brightness value of each pixel point of the touch screen by using an improved Newton-Raphson optimization algorithm, so as to obtain the data information of the brightness value of each pixel point of the optimized touch screen;

[0105] An overall display effect evaluation module for the touch screen, connected to the optimization module for each pixel point of the touch screen, and configured to construct an overall display effect evaluation function W of the touch screen, evaluate the overall display effect of the touch screen, and obtain the data information of the evaluation value of the overall display effect of the touch screen;

[0106] The overall display effect threshold judgment module of the touch screen, which is connected to the overall display effect evaluation module of the touch screen, is used to set a preset threshold. If the evaluation value of the overall display effect of the touch screen is less than the preset threshold, it does not meet the requirements; if the evaluation value of the overall display effect of the touch screen is greater than the preset threshold, it meets the requirements, and the display screen performs data display.

[0107] In this embodiment, the present invention also provides a computer-readable storage medium, on which a computer program is stored that is programmed or configured to execute the optimization control method for touch screen display applied to multiple systems described in any one of the above.

[0108] Any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application may include non-volatile and / or volatile memories. Non-volatile memories may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0109] In summary, the present invention can not only accurately control and adjust the brightness values of each pixel point of the touch screen, improving the accuracy of human-computer interaction, but also the entire optimization process can be adaptively adjusted according to different systems, improving the applicability of touch screen interaction and the user experience.

[0110] The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. An optimization control method for touch screen display applied to multiple systems, characterized in that: The method comprises: M1. The user presses the touch screen to obtain data information about the historical working status of the touch screen, and obtains data information about the pressure signal of the touch screen and the brightness value of each pixel of the touch screen in real time; M2. Based on the data information of the pressure signal of the touch screen and the data information of the historical working status of the touch screen, the brightness value of each pixel of the touch screen is predicted by using a decision tree prediction algorithm based on the pressure signal of the touch screen and the brightness value of the pixel, and the data information of the brightness value of each pixel of the touch screen after the prediction is obtained; M3. Based on the predicted data information of the brightness value of each pixel of the touch screen and the data information of the brightness value of each pixel of the touch screen, the brightness value of each pixel of the touch screen is optimized by using an improved Newton-Raphson optimization algorithm to obtain the optimized data information of the brightness value of each pixel of the touch screen; M4. Based on the data information of the brightness value of each pixel point of the optimized touch screen, construct an overall display effect evaluation function W of the touch screen, evaluate the overall display effect of the touch screen, and obtain data information of the evaluation value of the overall display effect of the touch screen.

2. The optimization control method for touch screen display applied to multiple systems according to claim 1, characterized in that: In step M2, predicting the brightness value of each pixel point of the touch screen by using a decision tree prediction algorithm based on the touch screen pressure signal and the brightness value of the pixel point includes: M21. Based on the data information of the historical working state of the touch screen, extract the data information of the historical pressure signal of the touch screen and the data information of the brightness value of each pixel of the touch screen corresponding thereto; M22. Based on the data information of the historical pressure signal of the touch screen and the corresponding data information of the brightness value of each pixel of the touch screen, a joint probability function Q of the pressure signal and the brightness value of the pixel of the touch screen is established. Wherein, x is the data information of the historical pressure signal of the touch screen, y is the data information of the brightness value of each pixel point of the touch screen corresponding thereto, α1, α2 and α3 are any constant coefficients between 0 and 1, and the joint probability of the pressure signal of the touch screen and the brightness value of the pixel point is calculated to obtain the data information of the joint probability of the pressure signal of the touch screen and the brightness value of the pixel point; M23. Based on the data information of the joint probability of the pressure signal of the touch screen and the brightness value of the pixel point and the data information of the pressure signal of the touch screen, a prediction function R of the brightness value of the pixel point of the touch screen is established, Among them, z is the data information of the pressure signal of the touch screen, r is the data information of the joint probability of the pressure signal of the touch screen and the brightness value of the pixel point, β1, β2 and β3 are weight coefficients, and the brightness value of each pixel point of the touch screen is predicted to obtain the data information of the brightness value of each pixel point of the touch screen after prediction.

3. The optimization control method for touch screen display applied to multiple systems according to claim 2, characterized in that: The constraints of the weight coefficients β1, β2 and β3 are:

4. The optimization control method for touch screen display applied to multiple systems according to claim 2 is characterized in that: The constraint function f of the constant coefficients α1, α2 and α3 is, The value range of the constraint function f is (0,1).

5. The optimization control method for touch screen display applied to multiple systems according to claim 1, characterized in that: In step M3, the optimization of the brightness value of each pixel of the touch screen by using the improved Newton-Raphson optimization algorithm includes: M31. Based on the predicted data information of the brightness value of each pixel of the touch screen and the data information of the brightness value of each pixel of the touch screen, establish a solution space function P of the pixel of the touch screen, Among them, h1 is the data information of the brightness value of each pixel of the touch screen after prediction, h2 is the data information of the brightness value of each pixel of the touch screen, δ1, δ2 and δ3 are penalty factors, which characterize the solution space of the pixel points of the touch screen to obtain the solution space data set of the pixel points of the touch screen; M32. Based on the solution space data set of the pixel points of the touch screen, the population is initialized and the fitness function S of the population individuals is established. Wherein, p is the solution space data set of the pixel points of the touch screen, and the fitness values ​​of the individuals in the population are calculated to obtain the data information of the fitness values ​​of the individuals in the population; M33. Based on the data information of the fitness values ​​of the individuals in the population, establish a target optimization function F, Among them, g is the data information of the fitness value of the population individual, λ1, λ2 and λ3 are gradient change factors, and the brightness value of each pixel point of the touch screen is predicted to obtain the data information of the brightness value of each pixel point of the touch screen after prediction.

6. The optimization control method for touch screen display applied to multiple systems according to claim 5, characterized in that: The gradient change factors λ1, λ2 and λ3 are, Among them, g is the data information of the fitness value of the individuals in the population.

7. The optimization control method for touch screen display applied to multiple systems according to claim 5, characterized in that: The penalty factors δ1, δ2 and δ3 are, Among them, h1 is the data information of the brightness value of each pixel point of the touch screen after prediction, and h2 is the data information of the brightness value of each pixel point of the touch screen.

8. The optimization control method for touch screen display applied to multiple systems according to claim 1, characterized in that: The overall display effect evaluation function W of the touch screen is: Among them, p i is the data information of the brightness value of the i-th pixel point of the optimized touch screen, and n is the sample capacity.

9. The optimization control method for touch screen display applied to multiple systems according to claim 1, characterized in that: The method further comprises: M5. Based on the data information of the evaluation value of the overall display effect of the touch screen, a preset threshold is set. If the evaluation value of the overall display effect of the touch screen is less than the preset threshold, it does not meet the requirements, and returns to step M3. If the evaluation value of the overall display effect of the touch screen is greater than the preset threshold, it meets the requirements, and the display screen displays data.

10. An optimization control system for touch screen display applied to multiple systems, comprising a computer device, characterized in that: The computer device is programmed or configured to execute the steps of the optimization control method for touch screen display applied to multiple systems as claimed in any one of claims 1 to 9.

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