CN114706626A - Processing method and electronic equipment - Google Patents
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- CN114706626A CN114706626A CN202210334634.5A CN202210334634A CN114706626A CN 114706626 A CN114706626 A CN 114706626A CN 202210334634 A CN202210334634 A CN 202210334634A CN 114706626 A CN114706626 A CN 114706626A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/445—Program loading or initiating
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Abstract
The application discloses a processing method and electronic equipment, if an operation instruction of a target application program is obtained, a first operation environment is configured for the target application program based on a first configuration parameter, the operation instruction is responded, the target application program is in an operation state based on the first operation environment, the target application program is in the operation state based on the first operation environment, an actual frame rate of an operation process of a target task of the target application program is obtained, the actual frame rate is time sequence data within a time period of the target task, a second configuration parameter is determined based on the actual frame rate, and the second configuration parameter is different from the first configuration parameter.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a processing method and an electronic device.
Background
For some applications, such as a large-volume mobile terminal game, in the running process, different performance requirements may be met for different users due to different operations of different users, and if the same set of configuration policy is adopted for all users, power consumption may be increased or screens may be jammed.
Disclosure of Invention
In view of this, the present application provides a processing method and an electronic device, and the specific scheme is as follows:
a method of processing, the method comprising:
if the running instruction of the target application program is obtained, configuring a first running environment for the target application program based on a first configuration parameter;
responding to the running instruction, and enabling the target application program to be in a running state based on the first running environment;
when the target application program is in a running state based on the first running environment, obtaining an actual frame rate of a target task running process of the target application program, wherein the actual frame rate is time sequence data in a time period of the target task;
determining the second configuration parameter based on the actual frame rate, the second configuration parameter being different from the first configuration parameter.
Further, the determining the second configuration parameter based on the actual frame rate includes:
processing the actual frame rate based on a machine learning classification model to obtain a data label of the actual frame rate, wherein the data label is used for representing the severity degree of the target task in a time period;
determining the second configuration parameter based on the data tag of the actual frame rate.
Further, the obtaining an actual frame rate of a target task running process of the target application includes:
the target task operation of the target application program is positioned in a monitoring period, and the actual frame rate of the target task operation process of the target application program is obtained;
and the monitoring period comprises the actual frame rate obtained in the target task running process of the target application program every time.
Further, the determining the second configuration parameter based on the actual frame rate includes:
determining the second configuration parameter based on a plurality of data tags of the target application within the monitoring period.
Further, the method further comprises:
obtaining the use duration of the target application program in the running state each time based on the monitoring period; or the like, or, alternatively,
and recording that the target application program is in the running state each time based on the monitoring period.
Further, the determining a second configuration parameter based on the actual frame rate includes:
determining the second configuration parameter based on a plurality of data tags, a plurality of usage durations, and a number of uses of the target application within the monitoring period.
Further, the determining a second configuration parameter based on the actual frame rate includes:
determining a user representation based on a plurality of data tags, a plurality of usage durations, and a number of uses of the target application within the monitoring period;
the second configuration parameter is determined based on the user representation, with different user representations corresponding to different second configuration parameters.
Further, the method further comprises:
and when the target application program is configured to be in the running state based on the second configuration parameters, obtaining a curve of the actual frame rate of the target task running process of the target application program, and smoothing the curve of the actual frame rate of the target task running process of the target application program when the target application program is in the running state based on the first running environment.
An electronic device, the electronic device comprising:
a display output section;
the processor is used for configuring a first operation environment for the target application program based on a first configuration parameter if the operation instruction of the target application program is obtained; responding to the running instruction, and enabling the target application program to be in a running state based on the first running environment; when the target application program is in a running state based on the first running environment, obtaining an actual frame rate of a target task running process of the target application program, wherein the actual frame rate is time sequence data in a time period of the target task; determining the second configuration parameter based on the actual frame rate, the second configuration parameter being different from the first configuration parameter.
Further, the processor is configured to determine the second configuration parameter based on the actual frame rate, including:
the processor is used for processing the actual frame rate based on a machine learning classification model to obtain a data label of the actual frame rate, wherein the data label is used for representing the severity degree of the target task in a time period; determining the second configuration parameter based on the data tag of the actual frame rate;
wherein the machine learning classification model comprises:
a characteristic value obtaining module, configured to obtain a characteristic value in the actual frame rate;
the data processing module is used for carrying out standardization processing on the characteristic value;
and the classification module is used for determining a data label based on the characteristic value after the normalization processing.
According to the processing method and the electronic device disclosed by the application, if the operation instruction of the target application is obtained, the first operation environment is configured for the target application based on the first configuration parameter, the operation instruction is responded, the target application is in the operation state based on the first operation environment, the actual frame rate of the target task operation process of the target application is obtained when the target application is in the operation state based on the first operation environment, the actual frame rate is time sequence data in the time period of the target task, and the second configuration parameter is determined based on the actual frame rate and is different from the first configuration parameter. In the scheme, in the running process of the target application program, the configuration parameters of the target application program are adjusted based on the actual frame rate of the target task, so that the adjusted configuration parameters are related to the actual frame rate in the running process, the running of the target application program is ensured to be performed by the configuration parameters adaptive to the actual frame rate, the configuration parameters can be adaptive to the actual operation of a user, and the phenomenon of power consumption increase or picture blockage caused by mismatching of the configuration parameters and the actual frame rate is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a processing method disclosed in an embodiment of the present application;
FIG. 2 is a flow chart of a processing method disclosed in an embodiment of the present application;
FIG. 3 is a schematic diagram of a frame rate curve representing severity as disclosed in an embodiment of the present application;
FIG. 4 is a flow chart of a processing method disclosed in an embodiment of the present application;
FIG. 5 is a flow chart of a processing method disclosed in an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The application discloses a processing method, a flow chart of which is shown in fig. 1, comprising the following steps:
step S11, if the operation instruction of the target application program is obtained, configuring a first operation environment for the target application program based on the first configuration parameter;
step S12, responding to the operation instruction, and enabling the target application program to be in an operation state based on the first operation environment;
step S13, when the target application program is in an operation state based on the first operation environment, obtaining the actual frame rate of the target task operation process of the target application program, wherein the actual frame rate is time sequence data in the time period of the target task;
step S14, determining a second configuration parameter based on the actual frame rate, wherein the second configuration parameter is different from the first configuration parameter.
Taking a target application program as an example for explanation, because different users have different operation modes, the performance requirements of different users on electronic equipment are different, if any user controls the operation of the target application program, the same set of configuration strategy is adopted, and if the performance requirements of the users are lower, the system power consumption is higher and unnecessary waste is caused by adopting a uniform configuration strategy; if the user has a high performance requirement, the adoption of a uniform configuration strategy can cause that the power consumption is not enough to support the operation of the user, thereby causing the phenomenon of picture blocking.
In order to solve the above problems, in the present solution, when the target application is in an operating state, the configuration parameters of the target application are adjusted based on the actual frame rate of the target application in the operating process, so that the configuration parameters of the target application in the operating process are related to the actual frame rate of the target application, and the actual frame rate is related to the operation mode of the user, thereby implementing configuration of different configuration parameters based on different users, and avoiding a problem of power consumption increase or picture blockage which may occur when the same set of configuration policy is adopted for all users.
And when the running instruction of the target application program is obtained, controlling the running of the target application program, namely controlling the running of the target application program when a user starts the target application program. Wherein the target application is run in a first runtime environment, the first runtime environment is configured based on a first configuration parameter, and the first configuration parameter is only used to configure the runtime environment of the target application.
For other applications, the configuration parameters corresponding to the application are used to configure the operating environment, and the application is operated in the configured operating environment, that is, different applications are operated in different operating environments, and each operating environment is configured based on the configuration parameters corresponding to the application.
The first configuration parameter may be a default configuration parameter, and the default configuration parameter may be a default configuration parameter of the target application program, that is, as long as the target application program is started, when the target application program is just started, the same operating environment is configured based on the same configuration parameter, and the target application program is started and operated in the same operating environment no matter which starting time the target application program is started, and only in the operating process, the configuration parameter is adjusted based on the actual frame rate, so that the operating environment is adjusted.
Or, the first configuration parameter may also be a configuration parameter set historically by the target application, where the first configuration parameter may be a configuration parameter set when the target application is operated at the time with the shortest interval time to the current obtained operation instruction, such as: when the target application program is operated for the first time, a second configuration parameter determined based on the actual frame rate is a configuration parameter A; when the target application program is started for the second time, configuring the first operating environment for the target application program is realized based on the configuration parameter A, and the second configuration parameter determined based on the actual frame rate at this time is the configuration parameter B; then the third time the target application is launched, configuring the first runtime environment for the target application is accomplished based on configuration parameter B. Taking the configuration parameters used in the last running process as the configuration parameters set when the next target application program is started;
in addition, the first configuration parameter may also be an average configuration parameter in the historical data, that is, the configuration parameters of the past times in the historical record are averaged to obtain an average configuration parameter, and the average configuration parameter is used as the configuration parameter for configuring the first operating environment when the target application program is started.
The configuration parameters configure resources of the system in operation, such as: the method comprises the following steps of frequency increasing or limiting of a CPU (Central processing Unit), frequency increasing or limiting of a GPU (graphics processing Unit), allocation of CPU resources, allocation of GPU resources, strategy parameters aiming at certain specific scenes and the like, wherein the allocation of the CPU resources comprises the following steps: scheduling each kernel of the CPU; policy parameters for certain specific scenarios, such as: for the stuck detection, if the frame rate is less than the frame rate which is recognized as stuck for one time, the policy parameters need to be configured.
And after the first operation environment is configured for the target application program based on the first configuration parameters, controlling the operation of the target application program so as to enable the target application program to operate in the first operation environment.
And in the running process of the target application program, acquiring the actual frame rate of the target task running process of the target application program, wherein the actual frame rate is the time sequence data in the time period of the target task. The target task of the target application program, that is, the execution of one target task in the running process of the target application program, includes: a game is played. The actual frame rate of the target task running process, that is, within the time length consumed by the target task running process, each time point obtains the corresponding actual frame rate, and then, the actual frame rate is time sequence data within a time period, which is the time length required to be consumed by the target task running process, and is a group of data rather than a single data. Such as: during a game, an actual frame rate is obtained at each time point during the game.
The actual frame rate is the number of frames actually displayed on the screen per second in the process of executing the target task by the target application program. The target frame number is set in advance for the target application program, and the target frame number may be related to hardware of the electronic device itself or related to the target application program, or the target frame number is set in advance for a user, so that a picture is output by the target frame number in the running process of the target application program.
Therefore, the actual frame number of the target task running process is obtained, and the operation habit or label of the user controlling the target task running process is actually determined.
After the second configuration parameter is determined based on the target frame number, because the second configuration parameter is determined based on the target frame number, and the target frame number is related to the operation habit or the label of the user, the determined second configuration parameter is actually related to the operation habit or the label of the user, that is, the configuration parameter of the target application program is adjusted based on the operation of the user, so that the configuration parameter of the target application program is related to the operation of the user, and the phenomenon of power consumption increase or picture pause caused by the mismatch of the configuration parameter and the actual frame rate is avoided.
Further, after the second configuration parameter is determined, a second operation environment is configured based on the second configuration parameter, and then the target application program is controlled to operate in the second operation environment, so that the operation of the target application program can better conform to the operation of the user, and the frame rate curve of the actual frame rate is smoother.
And after the configuration parameters are adjusted based on the actual frame rate, when the target application program runs in a second operating environment in which the configuration parameters after the adjustment are configured, the curve formed by the actual frame rate obtained by executing the target task is smoother than the curve formed by the actual frame rate obtained by executing the target task before the configuration parameters are adjusted.
Since the second operating environment is implemented based on the configuration parameter configuration adjusted by the actual frame rate, when the target application program operates in the second operating environment, as long as the operation habit of the user does not change, the actual frame rate is detected after the configuration parameter is adjusted, and the actual frame rate is smoother, that is, the change is less, compared with the actual frame rate before the configuration parameter is adjusted. When the frame rate curve is shaken up and down, or the shaking degree is large, the picture of the target task executed by the electronic device operated by the user is not smooth, and if the frame rate curve is smooth, the picture is smoother when the target task is executed, so that the configuration parameters need to be adjusted based on the actual frame rate.
The configuration parameters may be adjusted as follows: if the first configuration parameter includes an average frame rate of 2 seconds falling below 60, which is considered to be stuck, the second configuration parameter after the adjustment based on the actual frame rate may be: setting the 3 second drop to 60 or less is performed as a first pause, and the configuration parameters after adjustment are reduced by the screen pause compared with the configuration parameters before adjustment.
For each target task execution, the finally formed frame rate curve is formed based on the actual frame rate obtained after the configuration parameters are adjusted by the actual frame rate.
In the processing method disclosed in this embodiment, if an operation instruction of a target application is obtained, a first operation environment is configured for the target application based on a first configuration parameter, in response to the operation instruction, the target application is in an operation state based on the first operation environment, and when the target application is in the operation state based on the first operation environment, an actual frame rate of an operation process of a target task of the target application is obtained, where the actual frame rate is time series data within a time period of the target task, and a second configuration parameter is determined based on the actual frame rate, where the second configuration parameter is different from the first configuration parameter. According to the scheme, in the running process of the target application program, the configuration parameters of the target application program are adjusted based on the actual frame rate of the target task, so that the adjusted configuration parameters are related to the actual frame rate in the running process, the running of the target application program is ensured to be carried out by the configuration parameters adaptive to the actual frame rate, the configuration parameters can be adaptive to the actual operation of a user, and the phenomenon of power consumption increase or picture blocking caused by mismatching of the configuration parameters and the actual frame rate is avoided.
The embodiment discloses a processing method, a flowchart of which is shown in fig. 2, and the processing method includes:
step S21, if the operation instruction of the target application program is obtained, configuring a first operation environment for the target application program based on the first configuration parameter;
step S22, responding to the operation instruction, and enabling the target application program to be in an operation state based on the first operation environment;
step S23, when the target application program is in an operation state based on the first operation environment, obtaining an actual frame rate of the target task operation process of the target application program, wherein the actual frame rate is time sequence data in a time period of the target task;
step S24, processing the actual frame rate based on the machine learning classification model, and obtaining a data label of the actual frame rate, wherein the data label is used for representing the intensity degree of the target task in the time period;
step S25, determining a second configuration parameter based on the data tag of the actual frame rate, the second configuration parameter being different from the first configuration parameter.
When the actual frame rate is obtained and the second configuration parameter is determined based on the actual frame rate, the actual frame rate may be classified in a machine learning manner, specifically, the actual frame rate may be input into a machine learning classification model, an output result is obtained through the model, the output result is a data tag of the actual frame rate, and the second configuration parameter is further determined according to the data tag.
The data tag is used for representing the severity of the target task in a time period and representing the operation habit of a user when the user executes the target task, namely in the execution process of the target task, the actual frame rate of the data tag is used for indicating the frame rate corresponding to each time point, namely the actual frame rate is time sequence data in a time period, the severity of the user operation in the process of completing the target task can be determined based on the time sequence data, and the time sequence data can be displayed in a frame rate curve form.
Since the actual frame rate is a set of continuous frame rate data, the severity of the user operation can be indicated by a characteristic value such as an average value or a variance of the set of continuous frame rate data. The larger these characteristic values indicate a higher severity, and the smaller the characteristic values indicate a lower severity. For example: in the game, if a practice of hiding in a grass is adopted, the violence degree is low; if the player hits the periphery of the opposite object, the intensity is higher.
And displaying the severity of user operation when the target task is executed based on the frame rate curve of the actual frame rate, wherein the mild frame rate curve indicates that the severity is low, and the large frame rate curve indicates that the severity is high.
As shown in fig. 3, in the example, the actual frame rate of the target task execution process of 6 times acquired within one monitoring period is represented, that is, three curves of the actual frame rate of the target task execution process for the target application program with a target frame rate of 90 frames, in fig. 3, the group a of the curves of fig. 6 is flat as a whole, but the frame drop occurs at the beginning or the end, which indicates that the user invokes the setting interface at the beginning or the end, because the target frame rate of the setting interface is lower than the target frame rate of the interface of the target task execution process; the group b diagram in fig. 3 shows that a large frame rate drop occurs during the execution of the target task, indicating that the severity is high, and if the target application is a game, the position of the large frame rate drop in the group b diagram in fig. 3 is a group battle, which is high in severity and causes the frame rate drop with a large amplitude due to rapid change of the image; the large frame rate drop phenomenon in the group c diagram of fig. 3 is less than that in the group b diagram of fig. 3, but the overall frame rate curve has large jitter and has multiple sudden frame drops, which indicates that the drastic operating state is always maintained during the execution of the target task.
For the feature value, it can be extracted from the actual frame rate, and more feature values can be extracted from each of the continuous time series data, such as: and screening effective characteristic values from all the characteristic values by using the mean value, the median, the variance, the autoregressive coefficient and the like so as to classify the actual frame rate based on the effective characteristic values.
The effective characteristic value is a characteristic value effective for classifying user operation habits, and can represent the change state of a frame rate curve of time sequence data in a time period. The screening process may be: and (4) screening according to the meaning of the characteristic value, such as: time domain and frequency domain analysis parameters; determining feature values independent of the classification result based on the historical data, such as: similar data, or individuals with greater differences in all data, etc.
In this case, valid feature values can be selected from each data in the time series data in the time period, that is, valid feature values having the same meaning for different data, for example: the game has 10 minutes, each second has a frame rate value, the time period corresponding to the game has 600 frame rate values, the characteristic value of each frame rate value is extracted, and the effective characteristic values are screened respectively.
And after the effective characteristic values are screened out, carrying out standardization processing on the effective characteristic values to obtain structured data. Different normalization processes are performed for different target applications. The data standardization processing algorithm comprises min-max standardization processing, z-score standardization processing and the like.
Different normalization processes are executed for different target applications, which may be: different normalization processes are performed on different feature values based on the time period and the target frame rate of the target task of the target application, the target tasks of different target applications have different time periods, and the target frame rates of different target applications are different, which makes the normalization processes performed for different target applications different.
Such as: when the feature value related to the frame rate in one game is normalized, the following steps may be performed: dividing the sum of the detected frame rate values by the target frame rate to realize standardization, and then calculating characteristic values related to the frame rate; if the feature value related to the game duration is subjected to the standardization processing, the detected game duration can be divided by the standard duration, and after the standardization processing is realized, the feature value related to the duration is calculated.
And inputting the structured data obtained after the standardization processing into a machine learning classification model which is trained in advance to obtain the labels of the data in the time period of the target task, namely the data labels of each actual frame rate.
When model training is carried out on a machine learning classification model, feature extraction and screening are carried out based on historical data and/or inner side user data, after effective features are screened out, standardized processing is carried out to obtain structured data, machine learning clustering analysis is carried out on the structured data, an unsupervised Kmeans clustering model is adopted, the given sample set is clustered according to the distance between samples by the clustering model, points in each cluster are closely connected together, the distance between the clusters is as large as possible, the clustered structured data are labeled according to categories, and a labeled standardized structured data set is formed; and inputting the labeled structured data set into a machine learning classification model for training, wherein the classification model can adopt a supervised KNN classification model.
After the training is finished, the trained machine learning classification model can be used for processing the actual frame rate to obtain a data label, corresponding configuration parameters are further determined, the data label is determined in a model training mode, a second configuration parameter is further determined, the accuracy of the data label can be improved, and therefore the accuracy of the second configuration parameter is improved.
Different data tags correspond to different configuration parameters, a corresponding relation table of the data tags and the configuration parameters is established in advance, if the data tags of the currently detected actual frame rate are determined to be first tags, the configuration parameters corresponding to the first tags are determined to be second configuration parameters, and the operating environment of the target application program is reconfigured; and if the currently monitored data tag of the actual frame rate is determined to be the second tag, determining the configuration parameter corresponding to the second tag to be the second configuration parameter, and reconfiguring the operating environment of the target application program.
In the processing method disclosed in this embodiment, if an operation instruction of a target application is obtained, a first operation environment is configured for the target application based on a first configuration parameter, the operation instruction is responded, the target application is in an operation state based on the first operation environment, an actual frame rate of an operation process of a target task of the target application is obtained, the actual frame rate is time series data within a time period of the target task, the actual frame rate is processed based on a machine learning classification model, a data tag of the actual frame rate is obtained, the data tag is used for representing a severity degree within the time period of the target task, and a second configuration parameter is determined based on the data tag of the actual frame rate. According to the scheme, after the actual frame rate is obtained, the actual frame rate is input into the machine learning classification model to obtain the data label of the actual frame rate, and the second configuration parameter is determined based on the data label of the actual frame rate, so that the configuration parameter is determined and adjusted in a user-based operation and machine learning mode, the accuracy of adjusting the configuration parameter based on the actual frame rate is improved, and the phenomenon of power consumption increase or picture blocking caused by mismatching of the configuration parameter and the actual frame rate is avoided.
The embodiment discloses a processing method, a flowchart of which is shown in fig. 4, and includes:
step S41, if the operation instruction of the target application program is obtained, configuring a first operation environment for the target application program based on the first configuration parameter;
step S42, responding to the operation instruction, and enabling the target application program to be in an operation state based on the first operation environment;
step S43, when the target application program is in an operating state based on the first operating environment and the target task operation of the target application program is in a monitoring period, obtaining an actual frame rate of the target task operation process of the target application program, wherein the actual frame rate is time sequence data in the time period of the target task, and the monitoring period comprises the actual frame rate obtained in the target task operation process of the target application program each time;
step S44, determining a second configuration parameter based on the actual frame rate, wherein the second configuration parameter is different from the first configuration parameter.
And setting a monitoring period for the target application program, running the target application program in the monitoring period, and executing the target task. In other words, in a monitoring period, the target application may be run only once, multiple times of the target application may be run, or multiple times of the target tasks may be run.
Such as: a target task of a target application has a time period of 10 minutes, that is, 10 minutes, to complete the running of the target task, and a monitoring period may be 1 day or 1 week, so that the target task in the target application may be run only 1 time, may be run multiple times, or may not be run 1 time within 1 day or 1 week, which is related to the frequency or times of running the target task of the target application by the user.
In the monitoring period, only one target task is operated once, an actual frame rate is obtained, when a plurality of target tasks are operated, a plurality of actual frame rates are obtained, each actual frame rate represents a group of time sequence data in the time period of the target task, and then when the target tasks are operated for a plurality of times in the monitoring period to obtain a plurality of actual frame rates, a plurality of groups of time sequence data are actually obtained.
When determining the second configuration parameter based on the obtained multiple actual frame rates, firstly, inputting each actual frame rate to a machine learning classification model trained in advance, and outputting the machine learning classification model as a data tag of the actual frame rate. When a plurality of actual frame rates are obtained in a monitoring period, each actual frame rate is respectively input into the machine learning classification model, each actual frame rate can obtain a corresponding data label, a plurality of data labels are finally obtained, and a second configuration parameter is determined based on the obtained plurality of data labels.
Each data tag corresponds to a group of configuration parameters, after a plurality of data tags in a monitoring period are determined, the plurality of data tags need to be counted, one tag is finally determined to serve as a data tag representing the running severity of a target task in the monitoring period, and a second configuration parameter is determined through the finally determined tag, namely, the configuration parameter corresponding to the finally determined tag is selected to serve as the second configuration parameter.
Finally determining a tag for representing the running severity of the target task in the monitoring period from the multiple data tags, wherein the determination mode of the tag may be as follows: and determining in a ratio mode, namely determining the ratio of the number of each data tag in the plurality of data tags obtained in the monitoring period to the number of the types of all the data tags obtained in the monitoring period, and selecting the data tag with the highest ratio to represent the running severity of the target task in the monitoring period.
For example: obtaining 5 actual frame rates in a monitoring period, wherein a data tag corresponding to a 1 st actual frame rate is a 1 st tag, a data tag corresponding to a 2 nd actual frame rate is a 2 nd tag, a data tag corresponding to a 3 rd actual frame rate is a 2 nd tag, a data tag corresponding to a 4 th actual frame rate is a 2 nd tag, a data tag corresponding to a 5 th actual frame rate is a 1 st tag, the 1 st tag is 2 in total, the 2 nd tag is 3, 2/5 is less than 3/5, and the 2 nd tag is determined as a tag capable of representing the severity of the operation of a target task in the monitoring period.
Or, only when the occupation ratio reaches a certain preset value, the corresponding data tags are selected, and if the occupation ratios of all the data tags do not reach the preset value, the monitoring period can be prolonged, so that the number of the data tags is increased.
Alternatively, the following may be used: determining a plurality of actual frame rates obtained in a monitoring period, extracting corresponding characteristic values from each actual frame rate respectively, calculating an average value of each characteristic value in the actual frame rates to obtain each average characteristic value, determining a corresponding data tag based on all the average characteristic values, representing the intensity of a target task operated in the monitoring period through the data tag, and further determining a second configuration parameter, so that after the configuration of the configuration parameter is completed in a second operation environment, a target application program can be operated based on the reconfigured second operation environment, and the configuration parameter is matched with the operation habit of a user.
In the processing method disclosed in this embodiment, if an operation instruction of a target application is obtained, a first operation environment is configured for the target application based on a first configuration parameter, in response to the operation instruction, the target application is in an operation state based on the first operation environment, and when the target application is in the operation state based on the first operation environment, an actual frame rate of an operation process of a target task of the target application is obtained, where the actual frame rate is time series data within a time period of the target task, and a second configuration parameter is determined based on the actual frame rate, where the second configuration parameter is different from the first configuration parameter. In the scheme, in the running process of the target application program, the configuration parameters of the target application program are adjusted based on the actual frame rate of the target task, so that the adjusted configuration parameters are related to the actual frame rate in the running process, the running of the target application program is ensured to be performed by the configuration parameters adaptive to the actual frame rate, the configuration parameters can be adaptive to the actual operation of a user, and the phenomenon of power consumption increase or picture blockage caused by mismatching of the configuration parameters and the actual frame rate is avoided.
The present embodiment discloses a processing method, a flowchart of which is shown in fig. 5, and the processing method includes:
step S51, if the operation instruction of the target application program is obtained, configuring a first operation environment for the target application program based on the first configuration parameter;
step S52, responding to the operation instruction, and enabling the target application program to be in an operation state based on the first operation environment;
step S53, when the target application program is in an operating state based on the first operating environment, the target task operation of the target application program is located in a monitoring period, obtaining an actual frame rate of the target task operation process of the target application program, wherein the actual frame rate is time series data in the time period of the target task, and the monitoring period comprises the actual frame rate obtained in the target task operation process of the target application program each time;
step S54, determining a second configuration parameter based on the plurality of data tags, the plurality of usage durations, and the number of usage times of the target application in the monitoring period, wherein the second configuration parameter is different from the first configuration parameter.
Multiple target tasks can be operated in one monitoring period, and the operation of the multiple target tasks can be realized on the basis of operating the target application program once or on the basis of operating the target application programs for multiple times.
When the target tasks are operated for multiple times in one monitoring period, the actual frame rate can be obtained once when the target tasks are operated for each time, and the actual frame rates can be obtained by operating the target tasks for multiple times. When the target task is operated, the system can obtain the actual frame rate and at least comprises the time length for operating the target task, and can record the operating state of the target task.
Recording the running state of the target task, namely recording the running state of the target task every time, so as to obtain the use times of the target task in the monitoring period; the system obtains the use time length of each target task in operation so as to obtain the use time length and the use times of each target task in operation in the monitoring period.
And after determining the number of times of use, the use duration and the actual frame rate in each operation of the target task in the monitoring period, determining a data tag based on each actual frame rate, and determining a second configuration parameter based on the plurality of data tags, the plurality of use durations and the number of times of use.
If the service time of each target task is long, the influence of the power consumption of the target task running for a long time on the cruising ability of the equipment needs to be considered when parameter configuration is carried out; if the target task is operated for a plurality of times in the monitoring period, the influence of the power consumption of the target task which is operated for a plurality of times on the cruising ability of the equipment also needs to be considered when the parameter configuration is carried out; if the service time of each running target task in the monitoring period is short and the times are few, even if the power consumption is high, the cruising ability of the equipment cannot be obviously influenced.
Therefore, when determining the second configuration parameter, not only the data tag capable of representing the severity of the target task in operation needs to be determined, but also the usage duration and the usage times in the monitoring period need to be determined together, so as to ensure that when the target task is configured in the second operation environment based on the finally generated second configuration parameter, the phenomenon of high power consumption or image blockage caused by mismatching of the configuration parameter and the actual frame rate does not occur.
Further, determining the second configuration parameter based on the actual frame rate includes: determining a user portrait based on a plurality of data tags, a plurality of usage durations and usage times of the target application within the monitoring period, determining second configuration parameters based on the user portrait, different user portraits corresponding to different second configuration parameters.
Configuring different configuration parameters for different user figures, wherein the user figures are determined based on a plurality of data labels, a plurality of use durations and use times in a monitoring period, and the user figures represent characteristics of different users in running the target tasks, and the characteristics comprise whether the users are fierce or not, whether the users run the target tasks for a long time or not, or whether the users run the target tasks for a plurality of times.
For example: the target task is a game, the monitoring period is 1 week, the total playing time length in one monitoring period is determined, and the total playing time length is determined as an attribute A; determining the average game duration of each game in a monitoring period, and determining the average game duration as an attribute B; determining the frequency of game playing each day according to the number of game playing times in a monitoring period, and determining the frequency as an attribute C; and determining a data tag of a preset number of games in a monitoring period as an attribute D.
If the first user plays games, the frequency of the games is high, namely the attribute C is high, the duration of the games is long, namely the attribute A is long, and the data tag of each game shows that the shaking of the frame rate of the games is large and the games are violent, the first user can be considered as a first type player, wherein the first type player is a player who plays games frequently and each game likes violent playing methods;
if the second user plays the game, the frequency of the game is high, namely the attribute C is high, the duration of the game is long, namely the attribute A is long, but the data tag of each game shows that the frame rate of the game is gentle and the game is not fierce, the second user can be considered as a second type player, wherein the second type player is a player who plays the game frequently, but likes the strategy to win and dislikes fierce playing;
if the third user plays games, the frequency of the games is low, namely the attribute C is low, the duration of the games is short, namely the attribute A is short, but the data tag of each game shows that the frame rate of the games is greatly jittered and the games are violent, the third user can be considered as a third type player, wherein the third type player is a player who does not play games frequently but likes violent playing methods for each game;
if the fourth user plays the game, the frequency of the game is low, i.e., the attribute C is low, the duration of the game is short, i.e., the attribute a is short, and the data tag of each game shows that the frame rate of the game is gentle and the game is not violent, the fourth user can be considered as a fourth type player, wherein the fourth type player is a player who does not play the game frequently or like violent playing and belongs to a relatively Buddha family.
In the processing method disclosed in this embodiment, if an operation instruction of a target application is obtained, a first operation environment is configured for the target application based on a first configuration parameter, in response to the operation instruction, the target application is in an operation state based on the first operation environment, and when the target application is in the operation state based on the first operation environment, an actual frame rate of an operation process of a target task of the target application is obtained, where the actual frame rate is time series data within a time period of the target task, and a second configuration parameter is determined based on the actual frame rate, where the second configuration parameter is different from the first configuration parameter. In the scheme, in the running process of the target application program, the configuration parameters of the target application program are adjusted based on the actual frame rate of the target task, so that the adjusted configuration parameters are related to the actual frame rate in the running process, the running of the target application program is ensured to be performed by the configuration parameters adaptive to the actual frame rate, the configuration parameters can be adaptive to the actual operation of a user, and the phenomenon of power consumption increase or picture blockage caused by mismatching of the configuration parameters and the actual frame rate is avoided.
The embodiment discloses an electronic device, a schematic structural diagram of which is shown in fig. 6, and the electronic device includes:
a display output unit 61 and a processor 62.
The processor 62 is configured to configure a first operation environment for the target application based on the first configuration parameter when obtaining the operation instruction of the target application; responding to the running instruction, and enabling the target application program to be in a running state based on the first running environment; when the target application program is in an operating state based on the first operating environment, acquiring an actual frame rate of a target task operating process of the target application program, wherein the actual frame rate is time sequence data in a time period of the target task; a second configuration parameter is determined based on the actual frame rate, the second configuration parameter being different from the first configuration parameter.
Further, the processor determines a second configuration parameter based on the actual frame rate, including: the processor processes the actual frame rate based on the machine learning classification model, obtains a data tag of the actual frame rate, the data tag is used for representing the severity degree of the target task in the time period, and determines a second configuration parameter based on the data tag of the actual frame rate.
Wherein, the machine learning classification model includes:
the characteristic value acquisition module is used for acquiring a characteristic value in the actual frame rate;
the data processing module is used for carrying out standardization processing on the characteristic values;
and the classification module is used for determining the data label based on the characteristic value after the standardization processing.
The feature value obtaining module includes a time-series mining and analyzing module, and performs feature value extraction on a real-time frame rate curve collected by each game through the time-series mining and analyzing module, that is, the real-time status of any one actual frame rate of any one of the groups a, b, and c in fig. 3 is embodied, and the actual frame rate of the target task operation process is a group of data (for example, a frame rate curve of one game) of a temporally continuous actual frame rate. The characteristic value obtaining module also comprises a characteristic value screening module, and the characteristic value screening module screens the characteristic value of the group of data, and the characteristic value can effectively describe the change state of the frame rate curve so as to reflect the intensity of user operation. Some of these feature values focus on the continuous low valley in the frame rate curve (roughly corresponding to the fierce fighting scene in the game), and some focus on the fluctuation condition of the whole frame rate curve (corresponding to whether the interaction operation such as clicking the screen in the game is frequent). Namely, the extracted characteristic values can reflect the operation habits of the user to the maximum extent,
and the data processing module is used for carrying out standardization processing on the screened characteristic values. Unlike these conventional data normalization processing methods, the present patent performs different data normalization processing on different characteristic value data according to information such as game duration information and target frame rate. The data such as mean, maximum and minimum are normalized in combination with the target frame rate, and the data such as distant _ strike, number _ of _ peaks _ n are normalized in combination with the game duration and output a structured data set
Wherein the classification module comprises a cluster analysis module. The cluster analysis module performs machine learning cluster analysis on the normalized feature value structured data and outputs a labeled structured data set. The classification module further comprises a classification model training module. And receiving the labeled structured data set by the classification model training module, and outputting a classification label, for example, obtaining the classification label by using a frame rate curve of a game.
Further, the processor obtains an actual frame rate of a target task running process of the target application, and the method includes:
the target task operation of the target application program is in the monitoring period, and the processor obtains the actual frame rate of the target task operation process of the target application program; the monitoring period comprises an actual frame rate obtained in the target task running process of each target application program.
Further, the processor determines a second configuration parameter based on the actual frame rate, including:
the processor determines a second configuration parameter based on the plurality of data tags of the target application within the monitoring period.
Further, the processor is further configured to:
obtaining the use duration of the target application program in the running state every time based on the monitoring period; or, recording that the target application program is in the running state every time based on the monitoring period.
Further, the processor determines a second configuration parameter based on the actual frame rate, including:
the processor determines a second configuration parameter based on the plurality of data tags, the plurality of usage durations, and the number of uses of the target application within the monitoring period.
Further, the processor determines a second configuration parameter based on the actual frame rate, including:
the processor determining a user representation based on a plurality of data tags, a plurality of usage durations, and a number of uses of the target application within the monitoring period; a second configuration parameter is determined based on the user representation, different user representations corresponding to different second configuration parameters.
Further, the processor is further configured to:
and configuring the second operation environment to be in the operation state based on the second configuration parameters at the target application program, and obtaining a curve of the actual frame rate of the target task operation process of the target application program, wherein the curve is smoother than the curve of the actual frame rate of the target task operation process of the target application program when the target application program is in the operation state based on the first operation environment.
The electronic device disclosed in this embodiment is implemented on the basis of the processing method disclosed in the above embodiment, and is not described herein again.
In the electronic device disclosed in this embodiment, if an operation instruction of the target application is obtained, a first operation environment is configured for the target application based on the first configuration parameter, in response to the operation instruction, the target application is in an operation state based on the first operation environment, and when the target application is in the operation state based on the first operation environment, an actual frame rate of an operation process of a target task of the target application is obtained, where the actual frame rate is time series data within a time period of the target task, and a second configuration parameter is determined based on the actual frame rate, where the second configuration parameter is different from the first configuration parameter. In the scheme, in the running process of the target application program, the configuration parameters of the target application program are adjusted based on the actual frame rate of the target task, so that the adjusted configuration parameters are related to the actual frame rate in the running process, the running of the target application program is ensured to be performed by the configuration parameters adaptive to the actual frame rate, the configuration parameters can be adaptive to the actual operation of a user, and the phenomenon of power consumption increase or picture blockage caused by mismatching of the configuration parameters and the actual frame rate is avoided.
The embodiment of the present application further provides a readable storage medium, where a computer program is stored, and the computer program is loaded and executed by a processor to implement each step of the processing method, where a specific implementation process may refer to descriptions of corresponding parts in the foregoing embodiment, and details are not described in this embodiment.
The present application also proposes a computer program product or a computer program comprising computer instructions stored in a computer readable storage medium. The processor of the electronic device reads the computer instruction from the computer-readable storage medium, and executes the computer instruction, so that the electronic device executes the methods provided in the various optional implementation manners in the aspect of the processing method or the aspect of the processing system, and the specific implementation process may refer to the description of the corresponding embodiment, which is not described again.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of processing, the method comprising:
if the running instruction of the target application program is obtained, configuring a first running environment for the target application program based on a first configuration parameter;
responding to the running instruction, and enabling the target application program to be in a running state based on the first running environment;
when the target application program is in a running state based on the first running environment, obtaining an actual frame rate of a target task running process of the target application program, wherein the actual frame rate is time sequence data in a time period of the target task;
determining the second configuration parameter based on the actual frame rate, the second configuration parameter being different from the first configuration parameter.
2. The method of claim 1, wherein the determining the second configuration parameter based on the actual frame rate comprises:
processing the actual frame rate based on a machine learning classification model to obtain a data label of the actual frame rate, wherein the data label is used for representing the severity degree of the target task in a time period;
determining the second configuration parameter based on the data tag of the actual frame rate.
3. The method of claim 2, wherein the obtaining an actual frame rate of a target task running process of the target application comprises:
the target task operation of the target application program is positioned in a monitoring period, and the actual frame rate of the target task operation process of the target application program is obtained;
and the monitoring period comprises the actual frame rate obtained in the target task running process of the target application program every time.
4. The method of claim 3, wherein the determining the second configuration parameter based on the actual frame rate comprises:
determining the second configuration parameter based on a plurality of data tags of the target application within the monitoring period.
5. The method of claim 3, wherein the method further comprises:
obtaining the use duration of the target application program in the running state each time based on the monitoring period; or the like, or, alternatively,
and recording that the target application program is in a running state each time based on the monitoring period.
6. The method of claim 5, wherein said determining a second configuration parameter based on said actual frame rate comprises:
determining the second configuration parameter based on a plurality of data tags, a plurality of usage durations, and a number of uses of the target application within the monitoring period.
7. The method of claim 5, wherein the determining a second configuration parameter based on the actual frame rate comprises:
determining a user representation based on a plurality of data tags, a plurality of usage durations, and a number of uses of the target application within the monitoring period;
the second configuration parameter is determined based on the user representation, with different user representations corresponding to different second configuration parameters.
8. The method of claim 1, wherein the method further comprises:
and when the target application program is configured to be in the running state based on the second configuration parameters, obtaining a curve of the actual frame rate of the target task running process of the target application program, and smoothing the curve of the actual frame rate of the target task running process of the target application program when the target application program is in the running state based on the first running environment.
9. An electronic device, the electronic device comprising:
a display output section;
the processor is used for configuring a first operation environment for the target application program based on a first configuration parameter if the operation instruction of the target application program is obtained; responding to the running instruction, and enabling the target application program to be in a running state based on the first running environment; when the target application program is in a running state based on the first running environment, obtaining an actual frame rate of a target task running process of the target application program, wherein the actual frame rate is time sequence data in a time period of the target task; determining the second configuration parameter based on the actual frame rate, the second configuration parameter being different from the first configuration parameter.
10. The device of claim 9, wherein the processor is configured to determine the second configuration parameter based on the actual frame rate, comprising:
the processor is used for processing the actual frame rate based on a machine learning classification model to obtain a data label of the actual frame rate, wherein the data label is used for representing the severity degree of the target task in a time period; determining the second configuration parameter based on the data tag of the actual frame rate;
wherein the machine learning classification model comprises:
a characteristic value obtaining module, configured to obtain a characteristic value in the actual frame rate;
the data processing module is used for carrying out standardization processing on the characteristic value;
and the classification module is used for determining a data label based on the characteristic value after the normalization processing.
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