Display control method of display screen

Abstract

The invention discloses a display control method for a display screen, and belongs to the technical field of display screens, and the method comprises the following steps: S1, obtaining user perception real-time data, processing the user perception real-time data, and determining user perception feature data; s2, determining an optimal display screen display adaptive recommendation model; s3, determining a display screen suitable for the user to display an adaptive recommendation result, and intelligently controlling the display of the display screen; and S4, obtaining user interaction feedback opinions, providing personalized recommendation courses for the user, and displaying the personalized recommendation courses on a display screen. According to the method and the device, the problems that display control cannot be performed on the display screen according to the actual condition of the user, personalized course display cannot be provided for the user and the user experience feeling is poor in the prior art are solved, display control can be performed on the display screen according to the actual condition of the user, personalized course display can be provided for the user, the user experience feeling can be improved, and the user experience is improved. And user requirements can be well met.

Description

Technical Field

[0001] The present invention relates to the technical field of display screens, and in particular to a display control method of a display screen. Background Art

[0002] A screen is a device or appliance used to display images and colors. It is divided into a silver screen and a screen, also known as a display screen. It is widely used in mobile phones, computers, monitors, TVs, and devices with image or text display functions. With the continuous development of multimedia technology, the application scenarios of display screens have involved all aspects of people's work and life. Therefore, how to efficiently and accurately control the display of the display screen has become the focus of people's attention.

[0003] The Chinese patent with publication number CN110379360A discloses a display control device and system for controlling a full-color display screen, including a housing and an intelligent processing system, the intelligent processing system including a processor, a sound collection module, a high-definition camera, a database, an electromagnetic switch, an input interface and an output interface, the sound collection module and the high-definition camera are both installed on the front side of the top of the housing, the input interface and the output interface are both arranged on one side of the housing, a circuit board is installed in the housing, the processor and the database are both integrated and installed on the circuit board, and the intrusion can be identified through the establishment of a feature library, facial expression collection, sound collection, comparative analysis and processing, data source retention, and feature library optimization; however, the patent has the following defects:

[0004] The existing display screen cannot be controlled according to the actual situation of the user, and cannot provide personalized course display for the user, resulting in a poor user experience and failing to meet user needs. Summary of the invention

[0005] The purpose of the present invention is to provide a display control method for a display screen, which can control the display of the display screen according to the actual situation of the user, provide the user with personalized course display, improve the user experience, better meet the user needs, and solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A display control method for a display screen comprises the following steps:

[0008] S1: Acquire user perception real-time data, process the user perception real-time data, and determine user perception feature data;

[0009] S2: constructing a display screen display adaptive recommendation model according to the display control requirements of the display screen, testing and optimizing the display screen display adaptive recommendation model, and determining the optimal display screen display adaptive recommendation model;

[0010] S3: Analyze the user perception feature data based on the optimal display screen adaptive recommendation model, determine the display screen adaptive recommendation result suitable for the user, and intelligently control the display of the display screen;

[0011] S4: Obtain user interaction feedback, provide personalized recommended courses for users, and display the personalized recommended courses on a display screen.

[0012] Preferably, in S1, the user perceived real-time data is obtained by performing the following operations:

[0013] Real-time monitoring of whether there is a user at the display screen based on ultrasonic sensors;

[0014] When there is a user at the display screen, the display screen automatically adjusts the screen brightness and volume;

[0015] Capture the gender and age of the user at the display screen in real time to determine the user perception attribute data;

[0016] Capture the user's clothing and behavior on the display screen in real time to determine the user's perceived behavior data;

[0017] Among them, based on the user perception attribute data and the user perception behavior data, the user perception real-time data is determined.

[0018] Preferably, the display screen automatically adjusts screen brightness and volume, including:

[0019] Real-time monitoring of the brightness adjustment period of the display screen during a single brightness adjustment for automatically adjusting the screen brightness;

[0020] Extract the number of unit times contained in the brightness adjustment period; wherein the value of the unit time is 1s;

[0021] Extract the brightness adjustment amplitude corresponding to each unit time;

[0022] The brightness adjustment transition smoothness coefficient is obtained according to the brightness adjustment amplitude corresponding to each unit time; wherein the brightness adjustment transition smoothness coefficient is obtained by the following formula:

[0023]

[0024] Among them, H represents the brightness adjustment transition smoothness coefficient; L dmax and L dmin Indicates the maximum and minimum brightness adjustment amplitudes per unit time; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; T tIndicates the duration of brightness adjustment; T mx represents the average value of the interval corresponding to the maximum value of the brightness adjustment amplitude; T nx represents the average value of the occurrence interval corresponding to the minimum brightness adjustment amplitude; h represents the smoothing reference parameter;

[0025]

[0026] Wherein, h is the smoothing reference parameter; n is the number of unit times contained in the brightness adjustment period; L i represents the brightness adjustment amplitude corresponding to the i-th unit time; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range;

[0027] Comparing the brightness adjustment transition smoothing coefficient with a preset smoothing coefficient threshold;

[0028] When the brightness adjustment transition smoothness coefficient exceeds a preset smoothness coefficient threshold, the minimum allowable brightness adjustment amplitude per unit time of the brightness adjustment is adjusted.

[0029] Preferably, when the brightness adjustment transition smoothness coefficient exceeds a preset smoothness coefficient threshold, the minimum allowable brightness adjustment amplitude per unit time of the brightness adjustment is adjusted, including:

[0030] When the brightness adjustment transition smoothing coefficient exceeds a preset smoothing coefficient threshold, extracting a maximum allowable brightness adjustment amplitude and a minimum allowable brightness adjustment amplitude corresponding to the current brightness adjustment;

[0031] Using the brightness adjustment amplitude corresponding to each unit time and the maximum allowable brightness adjustment amplitude, obtaining an amplitude difference between the brightness adjustment amplitude corresponding to each unit time and the maximum allowable brightness adjustment amplitude as first difference data;

[0032] Using the brightness adjustment amplitude corresponding to each unit time and the minimum allowable brightness adjustment amplitude, obtaining an amplitude difference between the brightness adjustment amplitude corresponding to each unit time and the minimum allowable brightness adjustment amplitude as second difference data;

[0033] The adjusted minimum allowable brightness adjustment range is obtained by using the first difference data and the second difference data; wherein the adjusted minimum allowable brightness adjustment range is obtained by the following formula:

[0034] L tmin =ΔL+L cmin

[0035] Among them, L tminIndicates the minimum allowable brightness adjustment range after adjustment; L cmin represents the minimum allowable brightness adjustment amplitude corresponding to the current brightness adjustment amplitude; ΔL represents the adjustment amplitude compensation amount, and the ΔL adjustment amplitude compensation amount is obtained by the following formula:

[0036]

[0037] Among them, ΔL represents the adjustment amplitude compensation; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; n indicates the number of unit times included in the brightness adjustment period; L i represents the brightness adjustment amplitude corresponding to the i-th unit time; T g represents the average time interval between the maximum value and the minimum value of the brightness adjustment amplitude that appear adjacently in the brightness adjustment period; T t Indicates the duration of brightness adjustment.

[0038] Preferably, in S1, the user perceived real-time data is processed by performing the following operations:

[0039] Obtain real-time data on user perception;

[0040] Based on the sequential retrieval method, the user-perceived real-time data is retrieved;

[0041] Check the consistency of user-perceived real-time data;

[0042] Check whether the user-perceived real-time data meets the requirements based on the reasonable value range and mutual relationship of each parameter in the user-perceived real-time data;

[0043] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the user's perceived real-time data;

[0044] Process invalid and missing values ​​of user-perceived real-time data;

[0045] Remove invalid and missing data that is of no value to display control in real-time user perception data;

[0046] Determine the real-time user perception data that is valuable for display control of the display screen;

[0047] Extract features from valuable real-time user-perceived data for display control;

[0048] Determine user perception feature data.

[0049] Preferably, in S2, a display screen display adaptive recommendation model is constructed, and the following operations are performed:

[0050] According to the display control requirements of the display screen, collect a large amount of user perception history data that can reflect the display control characteristics of the display screen;

[0051] Select user perception historical data to determine the training set and test set;

[0052] According to the display control requirements of the display screen, select a model architecture suitable for the display control of the display screen;

[0053] Based on the training set, the selected model architecture suitable for display control of the display screen is trained;

[0054] Determine a display screen display adaptive recommendation model;

[0055] Based on the test set, the performance of the display screen display adaptive recommendation model is tested;

[0056] Determine the performance test results of the display-based adaptive recommendation model;

[0057] Mining and analyzing the performance test results of the display-based adaptive recommendation model;

[0058] Determine an optimization adjustment plan based on the display screen display adaptive recommendation model;

[0059] Optimize and adjust the display screen display adaptive recommendation model based on the optimization adjustment scheme;

[0060] Determine the optimal display screen display adaptive recommendation model.

[0061] Preferably, in S3, the user perception feature data is analyzed and the following operations are performed:

[0062] Obtain the optimal display screen display adaptive recommendation model;

[0063] Obtain user perception feature data;

[0064] Inputting user perception feature data into the optimal display screen display adaptive recommendation model;

[0065] Analyze user perception feature data based on the optimal display screen display adaptive recommendation model;

[0066] Determine the display screen that is suitable for the user to display the adaptive recommendation results.

[0067] Preferably, in S3, the display of the display screen is intelligently controlled by performing the following operations:

[0068] Obtaining a display screen suitable for the user to display adaptive recommendation results;

[0069] Conduct in-depth mining and relevant analysis on the adaptive recommendation results displayed on the display screen suitable for the user;

[0070] Determine the display control scheme of the display screen;

[0071] Intelligently control the display of the display screen based on the display screen control solution.

[0072] Preferably, in S4, to provide the user with personalized recommended courses, the following operations are performed:

[0073] Automatically adjust display content, background color and animation effects to display adaptive recommended courses for users;

[0074] Obtain user interactive feedback on adaptively recommended courses and determine user interactive feedback opinions;

[0075] Based on user interaction feedback, optimize the adaptive recommended courses displayed to users;

[0076] Determine the optimized personalized recommended courses;

[0077] The optimized personalized recommended courses are displayed in real time on the display screen to provide users with personalized recommended courses.

[0078] Preferably, in S4, personalized recommended courses are provided to the user, and the following operations are further performed:

[0079] Get feedback from user interactions;

[0080] Get personalized recommended courses for users;

[0081] Categorize and store user interaction feedback and personalized recommended courses;

[0082] Based on user interaction feedback and personalized recommended courses, the optimal display screen adaptive recommendation model is continuously optimized to make the recommended courses accurate and improve user satisfaction.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] 1. The present invention obtains user perception real-time data, processes the user perception real-time data, determines user perception feature data, constructs a display screen display adaptive recommendation model according to the display control requirements of the display screen, tests and optimizes the display screen display adaptive recommendation model, determines the optimal display screen display adaptive recommendation model, analyzes the user perception feature data based on the optimal display screen display adaptive recommendation model, determines the display screen display adaptive recommendation result suitable for the user, and performs intelligent control on the display of the display screen.

[0085] 2. The present invention obtains user interaction feedback, and based on the user interaction feedback, provides personalized recommended courses for users, displays personalized recommended courses on a display screen, and continuously optimizes the optimal display screen display adaptive recommendation model to make recommended courses accurate and improve user satisfaction. The display screen can be controlled according to the user's actual situation, and personalized course display can be provided for users, thereby improving user experience and better meeting user needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 The present invention is a flow chart of a display control method of a display screen. DETAILED DESCRIPTION

[0087] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0088] In order to solve the existing problem that the display screen cannot be controlled according to the actual situation of the user, cannot provide personalized course display for the user, resulting in poor user experience and failure to meet user needs, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0089] A display control method for a display screen comprises the following steps:

[0090] S1: Acquire user perception real-time data, process the user perception real-time data, and determine user perception feature data;

[0091] In this embodiment, as a preferred technical solution of the present invention, to obtain user perceived real-time data, the following operations are performed:

[0092] Real-time monitoring of whether there is a user at the display screen based on ultrasonic sensors;

[0093] When there is a user at the display screen, the display screen automatically adjusts the screen brightness and volume;

[0094] It should be noted that ultrasonic sensors are sensors that convert ultrasonic signals into other energy signals. Ultrasonic waves are mechanical waves with a vibration frequency higher than 20kHz. They have the characteristics of high frequency, short wavelength, small diffraction phenomenon, and especially good directionality, and the ability to become rays and propagate in a directional manner. Ultrasonic waves have a strong ability to penetrate liquids and solids, especially in solids that are opaque to sunlight. When ultrasonic waves encounter impurities or interfaces, they will produce significant reflections to form reflected echoes, and when they encounter moving objects, they can produce a Doppler effect. Ultrasonic sensors are widely used in industry, national defense, biomedicine, etc.

[0095] Therefore, the ultrasonic sensor can be used to monitor in real time whether there is a user at the display screen. When it is detected in real time that there is a user at the display screen, the display screen automatically adjusts the screen brightness and volume to achieve the best display effect. At the same time, when it is detected in real time that there is no user at the display screen, the display screen adjusts the screen brightness and volume to achieve energy-saving effects.

[0096] Specifically, the display automatically adjusts screen brightness and volume, including:

[0097] Real-time monitoring of the brightness adjustment period of the display screen during a single brightness adjustment for automatically adjusting the screen brightness;

[0098] Extract the number of unit times contained in the brightness adjustment period; wherein the value of the unit time is 1s;

[0099] Extract the brightness adjustment amplitude corresponding to each unit time;

[0100] The brightness adjustment transition smoothness coefficient is obtained according to the brightness adjustment amplitude corresponding to each unit time; wherein the brightness adjustment transition smoothness coefficient is obtained by the following formula:

[0101]

[0102] Among them, H represents the brightness adjustment transition smoothness coefficient; L dmax and L dmin Indicates the maximum and minimum brightness adjustment amplitudes per unit time; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; T t Indicates the duration of brightness adjustment; T mx represents the average value of the interval corresponding to the maximum value of the brightness adjustment amplitude; T nx represents the average value of the occurrence interval corresponding to the minimum brightness adjustment amplitude; h represents the smoothing reference parameter;

[0103]

[0104] Wherein, h is the smoothing reference parameter; n is the number of unit times contained in the brightness adjustment period; L i represents the brightness adjustment amplitude corresponding to the i-th unit time; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range;

[0105] Comparing the brightness adjustment transition smoothing coefficient with a preset smoothing coefficient threshold;

[0106] When the brightness adjustment transition smoothness coefficient exceeds a preset smoothness coefficient threshold, the minimum allowable brightness adjustment amplitude per unit time of the brightness adjustment is adjusted.

[0107] The technical effect of the above technical solution is: by real-time monitoring and adjusting the screen brightness of the display screen, the technical solution can ensure that the change of screen brightness is smoother and more gradual, avoiding the discomfort caused to the user's vision by sudden changes in brightness. This is especially important for users who use the display screen for a long time, and can significantly improve the comfort and satisfaction of use. By calculating the brightness adjustment transition smoothness coefficient (H), the scheme can quantitatively evaluate the degree of smoothness in the brightness adjustment process. This coefficient comprehensively considers multiple factors such as the maximum and minimum values ​​of the brightness adjustment amplitude, the allowable range of the current brightness adjustment amplitude, the adjustment duration, and the frequency of changes in the brightness adjustment amplitude, so as to more accurately guide the optimization of the brightness adjustment strategy.

[0108] When the brightness adjustment transition smoothing coefficient exceeds the preset smoothing coefficient threshold, the system can automatically adjust the minimum allowable brightness adjustment amplitude per unit time of brightness adjustment. This adaptive adjustment mechanism enables the system to dynamically adjust the brightness adjustment strategy according to different scenarios and user needs to achieve the best visual effects and user experience. Through more sophisticated and intelligent brightness adjustment strategies, this technical solution also helps to reduce unnecessary energy consumption. For example, automatically reducing the screen brightness when the ambient light is dim can not only protect the user's eyesight, but also effectively extend the battery life of the device. By real-time monitoring and evaluation of various parameters in the brightness adjustment process, the technical solution can promptly detect and correct possible abnormalities or instabilities, thereby enhancing the overall stability and reliability of the system.

[0109] In summary, this technical solution, by introducing the concept of brightness adjustment transition smoothness coefficient and combining it with an adaptive adjustment mechanism, achieves a more intelligent and precise adjustment of the display screen brightness, significantly improving user experience and system performance.

[0110] Specifically, when the brightness adjustment transition smoothing coefficient exceeds a preset smoothing coefficient threshold, the minimum allowable brightness adjustment amplitude per unit time of the brightness adjustment is adjusted, including:

[0111] When the brightness adjustment transition smoothing coefficient exceeds a preset smoothing coefficient threshold, extracting a maximum allowable brightness adjustment amplitude and a minimum allowable brightness adjustment amplitude corresponding to the current brightness adjustment;

[0112] Using the brightness adjustment amplitude corresponding to each unit time and the maximum allowable brightness adjustment amplitude, obtaining an amplitude difference between the brightness adjustment amplitude corresponding to each unit time and the maximum allowable brightness adjustment amplitude as first difference data;

[0113] Using the brightness adjustment amplitude corresponding to each unit time and the minimum allowable brightness adjustment amplitude, obtaining an amplitude difference between the brightness adjustment amplitude corresponding to each unit time and the minimum allowable brightness adjustment amplitude as second difference data;

[0114] The adjusted minimum allowable brightness adjustment range is obtained by using the first difference data and the second difference data; wherein the adjusted minimum allowable brightness adjustment range is obtained by the following formula:

[0115] L tmin =ΔL+L cmin

[0116] Among them, L tmin Indicates the minimum allowable brightness adjustment range after adjustment; L cmin represents the minimum allowable brightness adjustment amplitude corresponding to the current brightness adjustment amplitude; ΔL represents the adjustment amplitude compensation amount, and the ΔL adjustment amplitude compensation amount is obtained by the following formula:

[0117]

[0118] Among them, ΔL represents the adjustment amplitude compensation; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; n indicates the number of unit times included in the brightness adjustment period; L i represents the brightness adjustment amplitude corresponding to the i-th unit time; T g represents the average time interval between the maximum value and the minimum value of the brightness adjustment amplitude that appear adjacently in the brightness adjustment period; T t Indicates the duration of brightness adjustment.

[0119] The technical effect of the above technical solution is: when the brightness adjustment transition smoothness coefficient exceeds the preset threshold, it means that the current brightness adjustment process may not be smooth enough and there is a large brightness change fluctuation. By adjusting the minimum allowable brightness adjustment amplitude per unit time, this fluctuation can be reduced, making the brightness adjustment process smoother and more continuous, thereby improving the user's visual experience.

[0120] By calculating the difference between the brightness adjustment amplitude corresponding to each unit time and the maximum and minimum allowable brightness adjustment amplitudes (i.e., the first difference data and the second difference data), the deviation degree of the current brightness adjustment can be understood more accurately. Based on these difference data, the minimum allowable brightness adjustment amplitude is adjusted by using the adjustment amplitude compensation amount (ΔL), which can ensure that the brightness adjustment is always kept within a reasonable range to avoid over-adjustment or under-adjustment. This technical solution not only considers the smoothness of brightness adjustment, but also considers the duration of brightness adjustment and the time interval between adjacent brightness adjustment amplitude changes. By introducing parameters such as the average time interval (Tg) and the total adjustment duration (Tt), the efficiency and effect of brightness adjustment can be more comprehensively evaluated, thereby optimizing the overall brightness adjustment strategy. By real-time monitoring and adjusting the brightness adjustment parameters, the technical solution can quickly respond to changes in ambient light or user usage needs to ensure that the screen brightness is always kept in the best state. At the same time, through a fine adjustment strategy, the waste of system resources can be reduced and the overall stability and response speed of the system can be improved. Ultimately, the accumulation of the above technical effects will significantly enhance the user experience when using the display screen. Whether reading documents, watching videos or performing other visual tasks, users can enjoy a more comfortable, stable and efficient screen brightness adjustment experience.

[0121] In summary, this technical solution achieves more precise and intelligent control of the brightness adjustment process by adjusting the minimum allowable brightness adjustment amplitude per unit time of brightness adjustment and introducing multiple parameters for comprehensive evaluation and optimization, thereby improving user experience and system performance.

[0122] Capture the gender and age of the user at the display screen in real time to determine the user perception attribute data;

[0123] Capture the user's clothing and behavior on the display screen in real time to determine the user's perceived behavior data;

[0124] Among them, based on the user perception attribute data and the user perception behavior data, the user perception real-time data is determined.

[0125] It should be noted that the gender, age, clothing and behavior of the user at the display screen are captured in real time through a 360-degree panoramic camera to obtain user perception attribute data and user perception behavior data, and then determine the user perception real-time data.

[0126] Among them, the 360-degree panoramic camera can monitor without blind spots and covers an area of ​​about 400 square meters. It is equipped with a fisheye lens and has a 360-degree panoramic view. A 360-degree panoramic camera can replace multiple ordinary cameras, achieving seamless monitoring and realizing new monitoring applications. It is used in various fields, including prisons, government agencies, banks, social security, public places and cultural places.

[0127] In this embodiment, as a preferred technical solution of the present invention, the user perceived real-time data is processed, and the following operations are performed:

[0128] Obtain real-time data on user perception;

[0129] Based on the sequential retrieval method, the user-perceived real-time data is retrieved;

[0130] Check the consistency of user-perceived real-time data;

[0131] Check whether the user-perceived real-time data meets the requirements based on the reasonable value range and mutual relationship of each parameter in the user-perceived real-time data;

[0132] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the user's perceived real-time data;

[0133] Process invalid and missing values ​​of user-perceived real-time data;

[0134] Remove invalid and missing data that is of no value to display control in real-time user perception data;

[0135] Determine the real-time user perception data that is valuable for display control of the display screen;

[0136] Extract features from valuable real-time user-perceived data for display control;

[0137] Determine user perception feature data.

[0138] It should be noted that by searching the user-perceived real-time data, the user-perceived real-time data that is valuable for display screen control can be determined, the processing accuracy and speed of the user-perceived real-time data can be improved, and by extracting features from the user-perceived real-time data, the user-perceived feature data can be determined, which is convenient for subsequent analysis of the user-perceived feature data, and the display screen adaptive recommendation results suitable for the user are determined, so as to display adaptive recommended courses for the user.

[0139] S2: constructing a display screen display adaptive recommendation model according to the display control requirements of the display screen, testing and optimizing the display screen display adaptive recommendation model, and determining the optimal display screen display adaptive recommendation model;

[0140] In this embodiment, as a preferred technical solution of the present invention, a display screen display adaptive recommendation model is constructed, and the following operations are performed:

[0141] According to the display control requirements of the display screen, collect a large amount of user perception history data that can reflect the display control characteristics of the display screen;

[0142] Select user perception historical data to determine the training set and test set;

[0143] According to the display control requirements of the display screen, select a model architecture suitable for the display control of the display screen;

[0144] Based on the training set, the selected model architecture suitable for display control of the display screen is trained;

[0145] Determine a display screen display adaptive recommendation model;

[0146] Based on the test set, the performance of the display screen display adaptive recommendation model is tested;

[0147] Determine the performance test results of the display-based adaptive recommendation model;

[0148] Mining and analyzing the performance test results of the display-based adaptive recommendation model;

[0149] Determine an optimization adjustment plan based on the display screen display adaptive recommendation model;

[0150] Optimize and adjust the display screen display adaptive recommendation model based on the optimization adjustment scheme;

[0151] Determine the optimal display screen display adaptive recommendation model.

[0152] It should be noted that by constructing a display screen adaptive recommendation model and testing and optimizing the display screen adaptive recommendation model, the optimal display screen adaptive recommendation model is determined, which facilitates the subsequent analysis of user perception feature data, determines the display screen adaptive recommendation results suitable for the user, and displays adaptive recommended courses for the user.

[0153] S3: Analyze the user perception feature data based on the optimal display screen adaptive recommendation model, determine the display screen adaptive recommendation result suitable for the user, and intelligently control the display of the display screen;

[0154] In this embodiment, as a preferred technical solution of the present invention, the user perception feature data is analyzed and the following operations are performed:

[0155] Obtain the optimal display screen display adaptive recommendation model;

[0156] Obtain user perception feature data;

[0157] Inputting user perception feature data into the optimal display screen display adaptive recommendation model;

[0158] Analyze user perception feature data based on the optimal display screen display adaptive recommendation model;

[0159] Determine the display screen that is suitable for the user to display the adaptive recommendation results.

[0160] It should be noted that the user perception feature data is analyzed through the optimal display screen display adaptive recommendation model to determine the display screen display adaptive recommendation results suitable for the user, and the adaptive recommended courses are displayed to the user.

[0161] In this embodiment, as a preferred technical solution of the present invention, the display of the display screen is intelligently controlled, and the following operations are performed:

[0162] Obtaining a display screen suitable for the user to display adaptive recommendation results;

[0163] Conduct in-depth mining and relevant analysis on the adaptive recommendation results displayed on the display screen suitable for the user;

[0164] Determine the display control scheme of the display screen;

[0165] Intelligently control the display of the display screen based on the display screen control solution.

[0166] Therefore, by acquiring real-time user perception data, processing the real-time user perception data, determining the user perception feature data, and building a display screen display adaptive recommendation model according to the display control requirements of the display screen, the display screen display adaptive recommendation model is tested and optimized to determine the optimal display screen display adaptive recommendation model, and based on the optimal display screen display adaptive recommendation model, the user perception feature data is analyzed to determine the display screen display adaptive recommendation results suitable for the user, and the display of the display screen is intelligently controlled.

[0167] S4: Obtain user interaction feedback, provide personalized recommended courses for users, and display the personalized recommended courses on a display screen.

[0168] In this embodiment, as a preferred technical solution of the present invention, to provide personalized recommended courses for users, the following operations are performed:

[0169] Automatically adjust display content, background color and animation effects to display adaptive recommended courses for users;

[0170] Obtain user interactive feedback on adaptively recommended courses and determine user interactive feedback opinions;

[0171] Based on user interaction feedback, optimize the adaptive recommended courses displayed to users;

[0172] Determine the optimized personalized recommended courses;

[0173] The optimized personalized recommended courses are displayed in real time on the display screen to provide users with personalized recommended courses.

[0174] It should be noted that by obtaining user interaction feedback, the adaptive recommended courses displayed to the user are optimized based on the user interaction feedback, and the optimized personalized recommended courses are displayed in real time on the display screen to provide users with personalized recommended courses.

[0175] In this embodiment, as a preferred technical solution of the present invention, personalized recommended courses are provided to users, and the following operations are further performed:

[0176] Get feedback from user interactions;

[0177] Get personalized recommended courses for users;

[0178] Categorize and store user interaction feedback and personalized recommended courses;

[0179] Based on user interaction feedback and personalized recommended courses, the optimal display screen adaptive recommendation model is continuously optimized to make the recommended courses accurate and improve user satisfaction.

[0180] Therefore, by obtaining user interaction feedback, personalized recommended courses are provided to users based on the user interaction feedback, and personalized recommended courses are displayed on the display screen. The optimal display screen display adaptive recommendation model is continuously optimized to make the recommended courses accurate and improve user satisfaction. The display screen can be controlled according to the user's actual situation, and personalized course display can be provided to users, which can improve user experience and better meet user needs.

[0181] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0182] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A display control method for a display screen, It is characterized in that The steps include: S1: Acquire user perception real-time data, process the user perception real-time data, and determine user perception feature data; S2: constructing a display screen display adaptive recommendation model according to the display control requirements of the display screen, testing and optimizing the display screen display adaptive recommendation model, and determining the optimal display screen display adaptive recommendation model; S3: Analyze the user perception feature data based on the optimal display screen adaptive recommendation model, determine the display screen adaptive recommendation result suitable for the user, and intelligently control the display of the display screen; S4: Obtain user interaction feedback, provide personalized recommended courses for users, and display the personalized recommended courses on a display screen.

2. A display control method for a display screen according to claim 1, It is characterized in that In S1, the real-time data perceived by the user is obtained, and the following operations are performed: Real-time monitoring of whether there is a user at the display screen based on ultrasonic sensors; When there is a user at the display screen, the display screen automatically adjusts the screen brightness and volume; Capture the gender and age of the user at the display screen in real time to determine the user perception attribute data; Capture the user's clothing and behavior on the display screen in real time to determine the user's perceived behavior data; Among them, based on the user perception attribute data and the user perception behavior data, the user perception real-time data is determined.

3. A display control method for a display screen according to claim 2, It is characterized in that The display automatically adjusts screen brightness and volume, including: Real-time monitoring of the brightness adjustment period of the display screen during a single brightness adjustment for automatically adjusting the screen brightness; Extract the number of unit times contained in the brightness adjustment period; wherein the value of the unit time is 1s; Extract the brightness adjustment amplitude corresponding to each unit time; The brightness adjustment transition smoothness coefficient is obtained according to the brightness adjustment amplitude corresponding to each unit time; wherein the brightness adjustment transition smoothness coefficient is obtained by the following formula: Among them, H represents the brightness adjustment transition smoothness coefficient; L dmax and L dmin Indicates the maximum and minimum brightness adjustment amplitudes per unit time; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; T t Indicates the duration of brightness adjustment; T mx represents the average value of the interval corresponding to the maximum value of the brightness adjustment amplitude; T nx represents the average value of the occurrence interval corresponding to the minimum brightness adjustment amplitude; h represents the smoothing reference parameter; Wherein, h is the smoothing reference parameter; n is the number of unit times contained in the brightness adjustment period; L i represents the brightness adjustment amplitude corresponding to the i-th unit time; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; Comparing the brightness adjustment transition smoothing coefficient with a preset smoothing coefficient threshold; When the brightness adjustment transition smoothness coefficient exceeds a preset smoothness coefficient threshold, the minimum allowable brightness adjustment amplitude per unit time of the brightness adjustment is adjusted.

4. A display control method for a display screen according to claim 3, It is characterized in that When the brightness adjustment transition smoothness coefficient exceeds a preset smoothness coefficient threshold, the minimum allowable brightness adjustment amplitude per unit time of the brightness adjustment is adjusted, including: When the brightness adjustment transition smoothing coefficient exceeds a preset smoothing coefficient threshold, extracting a maximum allowable brightness adjustment amplitude and a minimum allowable brightness adjustment amplitude corresponding to the current brightness adjustment; Using the brightness adjustment amplitude corresponding to each unit time and the maximum allowable brightness adjustment amplitude, obtaining an amplitude difference between the brightness adjustment amplitude corresponding to each unit time and the maximum allowable brightness adjustment amplitude as first difference data; Using the brightness adjustment amplitude corresponding to each unit time and the minimum allowable brightness adjustment amplitude, obtaining an amplitude difference between the brightness adjustment amplitude corresponding to each unit time and the minimum allowable brightness adjustment amplitude as second difference data; The adjusted minimum allowable brightness adjustment range is obtained by using the first difference data and the second difference data; wherein the adjusted minimum allowable brightness adjustment range is obtained by the following formula: L tmin =ΔL+L cmin Among them, L tmin Indicates the minimum allowable brightness adjustment range after adjustment; L cmin represents the minimum allowable brightness adjustment amplitude corresponding to the current brightness adjustment amplitude; ΔL represents the adjustment amplitude compensation amount, and the ΔL adjustment amplitude compensation amount is obtained by the following formula: Among them, ΔL represents the adjustment amplitude compensation; L cmax and L cmin Indicates the maximum allowable brightness adjustment range and the minimum allowable brightness adjustment range corresponding to the current brightness adjustment range; n indicates the number of unit times included in the brightness adjustment period; L i represents the brightness adjustment amplitude corresponding to the i-th unit time; T g represents the average time interval between the maximum value and the minimum value of the brightness adjustment amplitude that appear adjacently in the brightness adjustment period; T t Indicates the duration of brightness adjustment.

5. A display control method for a display screen according to claim 2, It is characterized in that In S1, the user-perceived real-time data is processed and the following operations are performed: Obtain real-time data on user perception; Based on the sequential retrieval method, the user-perceived real-time data is retrieved; Check the consistency of user-perceived real-time data; Check whether the user-perceived real-time data meets the requirements based on the reasonable value range and mutual relationship of each parameter in the user-perceived real-time data; Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the user's perceived real-time data; Process invalid and missing values ​​of user-perceived real-time data; Remove invalid and missing data that is of no value to display control in real-time user perception data; Determine the real-time user perception data that is valuable for display control of the display screen; Extract features from valuable real-time user-perceived data for display control; Determine user perception feature data.

6. A display control method for a display screen according to claim 3, It is characterized in that In S2, a display screen display adaptive recommendation model is constructed, and the following operations are performed: According to the display control requirements of the display screen, collect a large amount of user perception history data that can reflect the display control characteristics of the display screen; Select user perception historical data to determine the training set and test set; According to the display control requirements of the display screen, select a model architecture suitable for the display control of the display screen; Based on the training set, the selected model architecture suitable for display control of the display screen is trained; Determine a display screen display adaptive recommendation model; Based on the test set, the performance of the display screen display adaptive recommendation model is tested; Determine the performance test results of the display-based adaptive recommendation model; Mining and analyzing the performance test results of the display-based adaptive recommendation model; Determine an optimization adjustment plan based on the display screen display adaptive recommendation model; Optimize and adjust the display screen display adaptive recommendation model based on the optimization adjustment scheme; Determine the optimal display screen display adaptive recommendation model.

7. A display control method for a display screen according to claim 4, It is characterized in that In S3, the user perception feature data is analyzed and the following operations are performed: Obtain the optimal display screen display adaptive recommendation model; Obtain user perception feature data; Inputting user perception feature data into the optimal display screen display adaptive recommendation model; Analyze user perception feature data based on the optimal display screen display adaptive recommendation model; Determine the display screen that is suitable for the user to display the adaptive recommendation results.

8. A display control method for a display screen according to claim 5, It is characterized in that In S3, the display of the display screen is intelligently controlled, and the following operations are performed: Obtaining a display screen suitable for the user to display adaptive recommendation results; Conduct in-depth mining and relevant analysis on the adaptive recommendation results displayed on the display screen suitable for the user; Determine the display control scheme of the display screen; Intelligently control the display of the display screen based on the display screen control solution.

9. A display control method for a display screen according to claim 6, It is characterized in that In S4, personalized recommended courses are provided to users by performing the following operations: Automatically adjust display content, background color and animation effects to display adaptive recommended courses for users; Obtain user interactive feedback on adaptively recommended courses and determine user interactive feedback opinions; Based on user interaction feedback, optimize the adaptive recommended courses displayed to users; Determine the optimized personalized recommended courses; The optimized personalized recommended courses are displayed in real time on the display screen to provide users with personalized recommended courses.

10. A display control method for a display screen according to claim 7, It is characterized in that In S4, personalized recommended courses are provided to users, and the following operations are also performed: Get feedback from user interactions; Get personalized recommended courses for users; Categorize and store user interaction feedback and personalized recommended courses; Based on user interaction feedback and personalized recommended courses, the optimal display screen adaptive recommendation model is continuously optimized to make the recommended courses accurate and improve user satisfaction.

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