CN109856544A - Terminal power uses time analysis method, terminal and computer readable storage medium - Google Patents
Terminal power uses time analysis method, terminal and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a kind of terminal powers to use time analysis method, terminal and computer readable storage medium, this method comprises: establishing the neural network model using the time for being used for the remaining electricity of analysing terminal；According to preset initial slope, the value of the node in the neural network model is generated；The historical record that the terminal is used according to the user, modifies to the value of the node；The neural network model is used after modification, that analyzes the electricity of the terminal residual uses the time.According to the technique and scheme of the present invention, the time of user's using terminal remaining capacity can be more accurately analyzed using the neural network model.
Description
Technical field
The present invention relates to field of mobile terminals more particularly to a kind of terminal power to use time analysis method, terminal and meter
Calculation machine readable storage medium storing program for executing.
Background technique
In modern society, mobile phone has become an important tool indispensable in user's daily life, life, work
Make, entertain the participation for all depending on mobile phone.User's long-time, high-frequency are to bring mobile phone using one problem of mobile phone bring
The increase that electricity uses, therefore the use time for analyzing mobile phone remaining capacity just becomes a critical issue, accurately analyzes hand
Machine remaining capacity uses the time, facilitates use of user's reasonable arrangement to mobile phone, avoids user when needing using mobile phone
Mobile phone but not enough power supply.
In prior art, a neural network model is usually set, and using fixed G-bar or adds
Weight average slope predicts that the prediction of remaining capacity uses the time.The problem of this method be calculation fix, result it is single, it is right
Being difficult under complicated terminal station service condition using time analysis is accurately estimated.
Therefore, it is necessary to a kind of new technical solution, more accurately the time can be used by analysing terminal remaining capacity.
Summary of the invention
It is a primary object of the present invention to propose that a kind of terminal power uses time analysis method, terminal and computer-readable
Storage medium, it is intended to the accurately use time of analysing terminal remaining capacity.
To achieve the above object, the present invention provides a kind of terminal powers to use time analysis method, comprising: foundation is used for
The neural network model using the time of the remaining electricity of analysing terminal；According to preset initial slope, the nerve net is generated
The value of node in network model；The historical record that the terminal is used according to the user, modifies to the value of the node；
The neural network model is used after modification, that analyzes the electricity of the terminal residual uses the time.
To achieve the above object, the present invention provides a kind of terminals, which is characterized in that the terminal includes processor, deposits
Reservoir, communication bus；The communication bus is for realizing the connection communication between processor and memory；The processor is used for
The terminal power that stores is executed in memory using time analysis program, the step of to realize preceding method.
To achieve the above object, the present invention provides a kind of computer readable storage medium, the computer-readable storages
Media storage has one or more program, and one or more of programs can be executed by one or more processor, with
The step of realizing preceding method.
According to above technical scheme, it is known that terminal power of the invention can using time analysis method, terminal and computer
Storage medium is read to have at least the following advantages:
According to the technique and scheme of the present invention, analysis electricity is being established using the neural network model of time, and using initial
After slope generates the node in neural network, the historical data of terminal is actually used to saving in neural network model also according to user
Point value be modified, enable each node value actual response user's using terminal power consumption actual conditions situation, base
In the neural network model of revised node more the neural network mould can be used according to the concrete condition of user's using terminal
Type can more accurately analyze the time of user's using terminal remaining capacity.
Detailed description of the invention
The hardware structural diagram of Fig. 1 mobile terminal of each embodiment to realize the present invention；
Fig. 2 is the wireless communication system schematic diagram of mobile terminal as shown in Figure 1；
Fig. 3 is the flow chart that time analysis method is used according to the terminal power of one embodiment of the present of invention；
Fig. 4 is the flow chart that time analysis method is used according to the terminal power of one embodiment of the present of invention；
Fig. 5 is the flow chart that time analysis method is used according to the terminal power of one embodiment of the present of invention；
Fig. 6 is the block diagram according to the terminal of one embodiment of the present of invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
In subsequent description, it is only using the suffix for indicating such as " module ", " component " or " unit " of element
Be conducive to explanation of the invention, itself there is no a distinctive meaning.Therefore, " module ", " component " or " unit " can mix
Ground uses.
Terminal can be implemented in a variety of manners.For example, terminal described in the present invention may include such as mobile phone, plate
Computer, laptop, palm PC, personal digital assistant (Personal Digital Assistant, PDA), portable
Media player (Portable Media Player, PMP), navigation device, wearable device, Intelligent bracelet, pedometer etc. move
The fixed terminals such as dynamic terminal, and number TV, desktop computer.
It will be illustrated by taking mobile terminal as an example in subsequent descriptions, it will be appreciated by those skilled in the art that in addition to special
Except element for moving purpose, the construction of embodiment according to the present invention can also apply to the terminal of fixed type.
Referring to Fig. 1, a kind of hardware structural diagram of its mobile terminal of each embodiment to realize the present invention, the shifting
Dynamic terminal 100 may include: RF (Radio Frequency, radio frequency) unit 101, WiFi module 102, audio output unit
103, A/V (audio/video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit
108, the components such as memory 109, processor 110 and power supply 111.It will be understood by those skilled in the art that shown in Fig. 1
Mobile terminal structure does not constitute the restriction to mobile terminal, and mobile terminal may include components more more or fewer than diagram,
Perhaps certain components or different component layouts are combined.
It is specifically introduced below with reference to all parts of the Fig. 1 to mobile terminal:
Radio frequency unit 101 can be used for receiving and sending messages or communication process in, signal sends and receivees, specifically, by base station
Downlink information receive after, to processor 110 handle；In addition, the data of uplink are sent to base station.In general, radio frequency unit 101
Including but not limited to antenna, at least one amplifier, transceiver, coupler, low-noise amplifier, duplexer etc..In addition, penetrating
Frequency unit 101 can also be communicated with network and other equipment by wireless communication.Any communication can be used in above-mentioned wireless communication
Standard or agreement, including but not limited to GSM (Global System of Mobile communication, global system for mobile telecommunications
System), GPRS (General Packet Radio Service, general packet radio service), CDMA2000 (Code
Division Multiple Access 2000, CDMA 2000), WCDMA (Wideband Code Division
Multiple Access, wideband code division multiple access), TD-SCDMA (Time Division-Synchronous Code
Division Multiple Access, TD SDMA), FDD-LTE (Frequency Division
Duplexing-Long Term Evolution, frequency division duplex long term evolution) and TDD-LTE (Time Division
Duplexing-Long Term Evolution, time division duplex long term evolution) etc..
WiFi belongs to short range wireless transmission technology, and mobile terminal can help user to receive and dispatch electricity by WiFi module 102
Sub- mail, browsing webpage and access streaming video etc., it provides wireless broadband internet access for user.Although Fig. 1 shows
Go out WiFi module 102, but it is understood that, and it is not belonging to must be configured into for mobile terminal, it completely can be according to need
It to omit within the scope of not changing the essence of the invention.
Audio output unit 103 can be in call signal reception pattern, call mode, record mould in mobile terminal 100
When under the isotypes such as formula, speech recognition mode, broadcast reception mode, by radio frequency unit 101 or WiFi module 102 it is received or
The audio data stored in memory 109 is converted into audio signal and exports to be sound.Moreover, audio output unit 103
Audio output relevant to the peculiar function that mobile terminal 100 executes can also be provided (for example, call signal receives sound, disappears
Breath receives sound etc.).Audio output unit 103 may include loudspeaker, buzzer etc..
A/V input unit 104 is for receiving audio or video signal.A/V input unit 104 may include graphics processor
(Graphics Processing Unit, GPU) 1041 and microphone 1042, graphics processor 1041 is in video acquisition mode
Or the image data of the static images or video obtained in image capture mode by image capture apparatus (such as camera) carries out
Reason.Treated, and picture frame may be displayed on display unit 106.Through graphics processor 1041, treated that picture frame can be deposited
Storage is sent in memory 109 (or other storage mediums) or via radio frequency unit 101 or WiFi module 102.Mike
Wind 1042 can connect in telephone calling model, logging mode, speech recognition mode etc. operational mode via microphone 1042
Quiet down sound (audio data), and can be audio data by such acoustic processing.Audio that treated (voice) data can
To be converted to the format output that can be sent to mobile communication base station via radio frequency unit 101 in the case where telephone calling model.
Microphone 1042 can be implemented various types of noises elimination (or inhibition) algorithms and send and receive sound to eliminate (or inhibition)
The noise generated during frequency signal or interference.
Mobile terminal 100 further includes at least one sensor 105, such as optical sensor, motion sensor and other biographies
Sensor.Specifically, optical sensor includes ambient light sensor and proximity sensor, wherein ambient light sensor can be according to environment
The light and shade of light adjusts the brightness of display panel 1061, and proximity sensor can close when mobile terminal 100 is moved in one's ear
Display panel 1061 and/or backlight.As a kind of motion sensor, accelerometer sensor can detect in all directions (general
For three axis) size of acceleration, it can detect that size and the direction of gravity when static, can be used to identify the application of mobile phone posture
(such as horizontal/vertical screen switching, dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, percussion) etc.；
The fingerprint sensor that can also configure as mobile phone, pressure sensor, iris sensor, molecule sensor, gyroscope, barometer,
The other sensors such as hygrometer, thermometer, infrared sensor, details are not described herein.
Display unit 106 is for showing information input by user or being supplied to the information of user.Display unit 106 can wrap
Display panel 1061 is included, liquid crystal display (Liquid Crystal Display, LCD), Organic Light Emitting Diode can be used
Forms such as (Organic Light-Emitting Diode, OLED) configure display panel 1061.
User input unit 107 can be used for receiving the number or character information of input, and generate the use with mobile terminal
Family setting and the related key signals input of function control.Specifically, user input unit 107 may include touch panel 1071 with
And other input equipments 1072.Touch panel 1071, also referred to as touch screen collect the touch operation of user on it or nearby
(for example user uses any suitable objects or attachment such as finger, stylus on touch panel 1071 or in touch panel 1071
Neighbouring operation), and corresponding attachment device is driven according to preset formula.Touch panel 1071 may include touch detection
Two parts of device and touch controller.Wherein, the touch orientation of touch detecting apparatus detection user, and detect touch operation band
The signal come, transmits a signal to touch controller；Touch controller receives touch information from touch detecting apparatus, and by it
It is converted into contact coordinate, then gives processor 110, and order that processor 110 is sent can be received and executed.In addition, can
To realize touch panel 1071 using multiple types such as resistance-type, condenser type, infrared ray and surface acoustic waves.In addition to touch panel
1071, user input unit 107 can also include other input equipments 1072.Specifically, other input equipments 1072 can wrap
It includes but is not limited in physical keyboard, function key (such as volume control button, switch key etc.), trace ball, mouse, operating stick etc.
It is one or more, specifically herein without limitation.
Further, touch panel 1071 can cover display panel 1061, when touch panel 1071 detect on it or
After neighbouring touch operation, processor 110 is sent to determine the type of touch event, is followed by subsequent processing device 110 according to touch thing
The type of part provides corresponding visual output on display panel 1061.Although in Fig. 1, touch panel 1071 and display panel
1061 be the function that outputs and inputs of realizing mobile terminal as two independent components, but in certain embodiments, it can
The function that outputs and inputs of mobile terminal is realized so that touch panel 1071 and display panel 1061 is integrated, is not done herein specifically
It limits.
Interface unit 108 be used as at least one external device (ED) connect with mobile terminal 100 can by interface.For example,
External device (ED) may include wired or wireless headphone port, external power supply (or battery charger) port, wired or nothing
Line data port, memory card port, the port for connecting the device with identification module, audio input/output (I/O) end
Mouth, video i/o port, ear port etc..Interface unit 108 can be used for receiving the input from external device (ED) (for example, number
It is believed that breath, electric power etc.) and the input received is transferred to one or more elements in mobile terminal 100 or can be with
For transmitting data between mobile terminal 100 and external device (ED).
Memory 109 can be used for storing software program and various data.Memory 109 can mainly include storing program area
The storage data area and, wherein storing program area can (such as the sound of application program needed for storage program area, at least one function
Sound playing function, image player function etc.) etc.；Storage data area can store according to mobile phone use created data (such as
Audio data, phone directory etc.) etc..In addition, memory 109 may include high-speed random access memory, it can also include non-easy
The property lost memory, a for example, at least disk memory, flush memory device or other volatile solid-state parts.
Processor 110 is the control centre of mobile terminal, utilizes each of various interfaces and the entire mobile terminal of connection
A part by running or execute the software program and/or module that are stored in memory 109, and calls and is stored in storage
Data in device 109 execute the various functions and processing data of mobile terminal, to carry out integral monitoring to mobile terminal.Place
Managing device 110 may include one or more processing units；Preferably, processor 110 can integrate application processor and modulatedemodulate is mediated
Manage device, wherein the main processing operation system of application processor, user interface and application program etc., modem processor is main
Processing wireless communication.It is understood that above-mentioned modem processor can not also be integrated into processor 110.
Mobile terminal 100 can also include the power supply 111 (such as battery) powered to all parts, it is preferred that power supply 111
Can be logically contiguous by power-supply management system and processor 110, to realize management charging by power-supply management system, put
The functions such as electricity and power managed.
Although Fig. 1 is not shown, mobile terminal 100 can also be including bluetooth module etc., and details are not described herein.
Embodiment to facilitate the understanding of the present invention, the communications network system that mobile terminal of the invention is based below into
Row description.
Referring to Fig. 2, Fig. 2 is a kind of communications network system architecture diagram provided in an embodiment of the present invention, the communication network system
System is the LTE system of universal mobile communications technology, which includes UE (User Equipment, the use of successively communication connection
Family equipment) (the land Evolved UMTS Terrestrial Radio Access Network, evolved UMTS 201, E-UTRAN
Ground wireless access network) 202, EPC (Evolved Packet Core, evolved packet-based core networks) 203 and operator IP operation
204。
Specifically, UE201 can be above-mentioned terminal 100, and details are not described herein again.
E-UTRAN202 includes eNodeB2021 and other eNodeB2022 etc..Wherein, eNodeB2021 can be by returning
Journey (backhaul) (such as X2 interface) is connect with other eNodeB2022, and eNodeB2021 is connected to EPC203,
ENodeB2021 can provide the access of UE201 to EPC203.
EPC203 may include MME (Mobility Management Entity, mobility management entity) 2031, HSS
(Home Subscriber Server, home subscriber server) 2032, other MME2033, SGW (Serving Gate Way,
Gateway) 2034, PGW (PDN Gate Way, grouped data network gateway) 2035 and PCRF (Policy and
Charging Rules Function, policy and rate functional entity) 2036 etc..Wherein, MME2031 be processing UE201 and
The control node of signaling, provides carrying and connection management between EPC203.HSS2032 is all to manage for providing some registers
Such as the function of home location register (not shown) etc, and preserves some related service features, data rates etc. and use
The dedicated information in family.All customer data can be sent by SGW2034, and PGW2035 can provide the IP of UE 201
Address distribution and other functions, PCRF2036 are strategy and the charging control strategic decision-making of business data flow and IP bearing resource
Point, it selects and provides available strategy and charging control decision with charge execution function unit (not shown) for strategy.
IP operation 204 may include internet, Intranet, IMS (IP Multimedia Subsystem, IP multimedia
System) or other IP operations etc..
Although above-mentioned be described by taking LTE system as an example, those skilled in the art should know the present invention is not only
Suitable for LTE system, be readily applicable to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA with
And the following new network system etc., herein without limitation.
Based on above-mentioned mobile terminal hardware configuration and communications network system, each embodiment of the method for the present invention is proposed.
As shown in figure 3, providing a kind of terminal power in one embodiment of the present of invention uses time analysis method, packet
It includes:
Step S310 establishes the neural network model using the time for being used for the remaining electricity of analysing terminal.
In the present embodiment, neural network (Neural Networks, NN) (is claimed by a large amount of, simple processing unit
For neuron) widely interconnect and the complex networks system that is formed, it reflects many essential characteristics of human brain function, is
One highly complex non-linear dynamic learning system.In the present embodiment, to the concrete form of neural network model without
Limitation, neural network model in the prior art are suitable for the technical solution of the present embodiment.
Step S320 generates the value of the node in neural network model according to preset initial slope.
In the present embodiment, the specific value of initial slope is not limited, to the node in neural network model
Number amount and type are also not limited.
Step S330 modifies to the value of node according to the historical record of user's using terminal.
In the present embodiment, data used in historical record are not limited, it is, for example, possible to use the work of terminal
Mode, current power consumption condition etc..The value of node after being modified according to user's usage history record, having reacted user makes
With the habit of terminal, so the neural network model can be analyzed according to the use habit of user.
Step S340, uses neural network model after modification, the remaining electricity of analysing terminal uses the time.
According to the technical solution of the present embodiment, the neural network model of time is used establishing analysis electricity, and use just
After beginning slope generates the node in neural network, the historical data of terminal is actually used in neural network model also according to user
The value of node is modified, enable each node value actual response user's using terminal power consumption actual conditions situation,
Neural network model based on revised node more can use the neural network according to the concrete condition of user's using terminal
Model can more accurately analyze the time of user's using terminal remaining capacity.
As shown in figure 4, providing a kind of terminal power in one embodiment of the present of invention uses time analysis method, packet
It includes:
Step S410 obtains the factor that electricity service efficiency is influenced in terminal, when factor is multiple, analyzes Multiple factors
The influence degree of electricity service efficiency screens Multiple factors according to influence degree height.
In the present embodiment, since the factor for including in the historical record of user in terminal is more, and some types because
Element is smaller without influencing or influencing on terminal electricity loss, such factor is also excluded, using only the factor of larger impact
The Value Types of each node in neural network model are set, this helps reducing the same of the computational complexity of neural network model
When, it is ensured that neural network model analyzes the accuracy that electricity uses the time.
The type of the value of node is arranged according to factor by step S420.
In the present embodiment, since the performance of terminal is limited always, it is therefore necessary to reduce neural network model
Computational complexity, therefore screened according to influence degree height of the Multiple factors to electricity service efficiency, reduce nodal value
Quantity, while retaining the factor that is affected to electricity service efficiency, to guarantee the accuracy of neural network model.
In the present embodiment, factor includes the operating mode of present terminal, the application opened, and/or real-time discharge power.
Step S430 establishes the neural network model using the time for being used for the remaining electricity of analysing terminal.
Step S440 generates the value of the node in neural network model according to preset initial slope.
Step S450, the current load of detection terminal.
Step S460, according to the type of the value of node, chooses corresponding when load is lower than preset standard from historical record
Value of the value of type as node.
In the present embodiment, inevitable if modifying the value of each node of neural network model again when the load of terminal is higher
Other work that will affect terminal execute, so only selecting to modify nodal value in the case where loading lower situation.
Step S470, uses neural network model after modification, the remaining electricity of analysing terminal uses the time.
It is as follows according to the technical solution of the present embodiment specific example: to establish BP (error backpropagation algorithm) nerve
Network model constantly learns the use habit of user, predicts that residue uses the time according to the use habit of user.Specific stream
Journey: step 1: establishing neutral net mathematical model, establish number of nodes, node type used.Step 2: setting initial slope, and root
Each nodal value of neural network is generated according to initial slope.Step 3: record each time point user use pattern, including open
Using and use the time, and record the real-time discharge power of battery under the mode.Step 4: according to the true service condition of user
Remove amendment each nodal value of neural network.Step 5: with the neural network prediction remaining capacity up time generated.
According to the technical solution of the present embodiment, the prediction remaining capacity up time is gone more to stick on by neural network model
The actual use habit for sharing family, is not fixed mathematical formulae.
As shown in figure 5, providing a kind of terminal power in one embodiment of the present of invention uses time analysis method, packet
It includes:
The number of the value of node is arranged according to the calculated performance of terminal in step S510.
In the present embodiment, since neural network model interior joint is worth number to directly affect computational complexity, in order to
Avoid terminal analysis electricity too high using load when the time, so nodal value is rationally arranged previously according to the calculated performance of terminal
Quantity, avoid influence terminal other work.
Step S520 establishes the neural network model using the time for being used for the remaining electricity of analysing terminal.
Step S530 generates the value of the node in neural network model according to preset initial slope.
Step S540 identifies the identity of user according to the account information that the fingerprint of user and/or user use.
In the present embodiment, the whether fingerprint of user or user's registration terminal system or the account information of application,
It can identify the identity of the user of currently used terminal.
Step S550, according to the number of the value of node, is selected when the identity of user meets preset condition from historical record
Take the value of corresponding number as the value of node.
In the present embodiment, due to using terminal there may be multiple people, and the use habit of multiple people is different, so
Can not according to it is multiple it is humanoid at historical record modification neural network model nodal value.In the present embodiment, it identifies first
The identity of user, the owner that can only to some user, such as terminal, setting neural network model simultaneously modify corresponding value.
Step S560, uses neural network model after modification, the remaining electricity of analysing terminal uses the time.
According to the technical solution of the present embodiment, the neural network model of time is used establishing analysis electricity, and use just
After beginning slope generates the node in neural network, the historical data of terminal is actually used in neural network model also according to user
The value of node is modified, enable each node value actual response user's using terminal power consumption actual conditions situation,
Neural network model based on revised node more can use the neural network according to the concrete condition of user's using terminal
Model can more accurately analyze the time of user's using terminal remaining capacity.
As shown in fig. 6, providing a kind of terminal in one embodiment of the present of invention, terminal includes processor 610, memory
620, communication bus 630；Communication bus 630 is for realizing the connection communication between processor 610 and memory 620；Processor
610 for executing the terminal power stored in memory 620 using time analysis program, to perform the steps of
Establish the neural network model using the time for being used for the remaining electricity of analysing terminal.
In the present embodiment, neural network (Neural Networks, NN) (is claimed by a large amount of, simple processing unit
For neuron) widely interconnect and the complex networks system that is formed, it reflects many essential characteristics of human brain function, is
One highly complex non-linear dynamic learning system.In the present embodiment, to the concrete form of neural network model without
Limitation, neural network model in the prior art are suitable for the technical solution of the present embodiment.
According to preset initial slope, the value of the node in neural network model is generated.
In the present embodiment, the specific value of initial slope is not limited, to the node in neural network model
Number amount and type are also not limited.
According to the historical record of user's using terminal, modify to the value of node.
In the present embodiment, data used in historical record are not limited, it is, for example, possible to use the work of terminal
Mode, current power consumption condition etc..The value of node after being modified according to user's usage history record, having reacted user makes
With the habit of terminal, so the neural network model can be analyzed according to the use habit of user.
Neural network model is used after modification, the remaining electricity of analysing terminal uses the time.
According to the technical solution of the present embodiment, the neural network model of time is used establishing analysis electricity, and use just
After beginning slope generates the node in neural network, the historical data of terminal is actually used in neural network model also according to user
The value of node is modified, enable each node value actual response user's using terminal power consumption actual conditions situation,
Neural network model based on revised node more can use the neural network according to the concrete condition of user's using terminal
Model can more accurately analyze the time of user's using terminal remaining capacity.
As shown in fig. 6, providing a kind of terminal in one embodiment of the present of invention, terminal includes processor 610, memory
620, communication bus 630；Communication bus 630 is for realizing the connection communication between processor 610 and memory 620；Processor
610 for executing the terminal power stored in memory 620 using time analysis program, to perform the steps of
The factor that electricity service efficiency is influenced in terminal is obtained, when factor is multiple, analysis Multiple factors make electricity
Multiple factors are screened according to influence degree height with the influence degree of efficiency.
In the present embodiment, since the factor for including in the historical record of user in terminal is more, and some types because
Element is smaller without influencing or influencing on terminal electricity loss, such factor is also excluded, using only the factor of larger impact
The Value Types of each node in neural network model are set, this helps reducing the same of the computational complexity of neural network model
When, it is ensured that neural network model analyzes the accuracy that electricity uses the time.
The type of the value of node is set according to factor.
In the present embodiment, since the performance of terminal is limited always, it is therefore necessary to reduce neural network model
Computational complexity, therefore screened according to influence degree height of the Multiple factors to electricity service efficiency, reduce nodal value
Quantity, while retaining the factor that is affected to electricity service efficiency, to guarantee the accuracy of neural network model.
In the present embodiment, factor includes the operating mode of present terminal, the application opened, and/or real-time discharge power.
Establish the neural network model using the time for being used for the remaining electricity of analysing terminal.
According to preset initial slope, the value of the node in neural network model is generated.
Detect the current load of terminal.
When load is lower than preset standard, according to the type of the value of node, the value of respective type is chosen from historical record
Value as node.
In the present embodiment, inevitable if modifying the value of each node of neural network model again when the load of terminal is higher
Other work that will affect terminal execute, so only selecting to modify nodal value in the case where loading lower situation.
Neural network model is used after modification, the remaining electricity of analysing terminal uses the time.
It is as follows according to the technical solution of the present embodiment specific example: to establish BP (error backpropagation algorithm) nerve
Network model constantly learns the use habit of user, predicts that residue uses the time according to the use habit of user.Specific stream
Journey: step 1: establishing neutral net mathematical model, establish number of nodes, node type used.Step 2: setting initial slope, and root
Each nodal value of neural network is generated according to initial slope.Step 3: record each time point user use pattern, including open
Using and use the time, and record the real-time discharge power of battery under the mode.Step 4: according to the true service condition of user
Remove amendment each nodal value of neural network.Step 5: with the neural network prediction remaining capacity up time generated.
According to the technical solution of the present embodiment, the prediction remaining capacity up time is gone more to stick on by neural network model
The actual use habit for sharing family, is not fixed mathematical formulae.
As shown in fig. 6, providing a kind of terminal in one embodiment of the present of invention, terminal includes processor 610, memory
620, communication bus 630；Communication bus 630 is for realizing the connection communication between processor 610 and memory 620；Processor
610 for executing the terminal power stored in memory 620 using time analysis program, to perform the steps of
According to the calculated performance of terminal, the number of the value of node is set.
In the present embodiment, since neural network model interior joint is worth number to directly affect computational complexity, in order to
Avoid terminal analysis electricity too high using load when the time, so nodal value is rationally arranged previously according to the calculated performance of terminal
Quantity, avoid influence terminal other work.
Establish the neural network model using the time for being used for the remaining electricity of analysing terminal.
According to preset initial slope, the value of the node in neural network model is generated.
According to the account information that the fingerprint of user and/or user use, the identity of user is identified.
In the present embodiment, the whether fingerprint of user or user's registration terminal system or the account information of application,
It can identify the identity of the user of currently used terminal.
When the identity of user meets preset condition, according to the number of the value of node, corresponding is chosen from historical record
Value of several values as node.
In the present embodiment, due to using terminal there may be multiple people, and the use habit of multiple people is different, so
Can not according to it is multiple it is humanoid at historical record modification neural network model nodal value.In the present embodiment, it identifies first
The identity of user, the owner that can only to some user, such as terminal, setting neural network model simultaneously modify corresponding value.
Neural network model is used after modification, the remaining electricity of analysing terminal uses the time.
According to the technical solution of the present embodiment, the neural network model of time is used establishing analysis electricity, and use just
After beginning slope generates the node in neural network, the historical data of terminal is actually used in neural network model also according to user
The value of node is modified, enable each node value actual response user's using terminal power consumption actual conditions situation,
Neural network model based on revised node more can use the neural network according to the concrete condition of user's using terminal
Model can more accurately analyze the time of user's using terminal remaining capacity.
A kind of computer readable storage medium is provided in one embodiment of the present of invention, computer readable storage medium is deposited
One or more program is contained, one or more program can be executed by one or more processor, to realize following step
It is rapid:
Establish the neural network model using the time for being used for the remaining electricity of analysing terminal.
In the present embodiment, neural network (Neural Networks, NN) (is claimed by a large amount of, simple processing unit
For neuron) widely interconnect and the complex networks system that is formed, it reflects many essential characteristics of human brain function, is
One highly complex non-linear dynamic learning system.In the present embodiment, to the concrete form of neural network model without
Limitation, neural network model in the prior art are suitable for the technical solution of the present embodiment.
According to preset initial slope, the value of the node in neural network model is generated.
In the present embodiment, the specific value of initial slope is not limited, to the node in neural network model
Number amount and type are also not limited.
According to the historical record of user's using terminal, modify to the value of node.
In the present embodiment, data used in historical record are not limited, it is, for example, possible to use the work of terminal
Mode, current power consumption condition etc..The value of node after being modified according to user's usage history record, having reacted user makes
With the habit of terminal, so the neural network model can be analyzed according to the use habit of user.
Neural network model is used after modification, the remaining electricity of analysing terminal uses the time.
According to the technical solution of the present embodiment, the neural network model of time is used establishing analysis electricity, and use just
After beginning slope generates the node in neural network, the historical data of terminal is actually used in neural network model also according to user
The value of node is modified, enable each node value actual response user's using terminal power consumption actual conditions situation,
Neural network model based on revised node more can use the neural network according to the concrete condition of user's using terminal
Model can more accurately analyze the time of user's using terminal remaining capacity.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the device that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or device.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal (can be mobile phone, computer, service
Device, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, all of these belong to the protection of the present invention.
Claims (10)
1. a kind of terminal power uses time analysis method characterized by comprising
Establish the neural network model using the time for being used for the remaining electricity of analysing terminal；
According to preset initial slope, the value of the node in the neural network model is generated；
The historical record that the terminal is used according to the user, modifies to the value of the node；
The neural network model is used after modification, that analyzes the electricity of the terminal residual uses the time.
2. the method according to claim 1, wherein generating the mind according to preset initial slope described
Before value through the node in network model, further includes:
The factor for influencing electricity service efficiency in the terminal is obtained, the type of the value of the node is set according to the factor；
The historical record that the terminal is used according to the user, modifies to the value of the node, comprising:
According to the type of the value of the node, value of the value of respective type as the node is chosen from the historical record.
3. according to the method described in claim 2, it is characterized in that, described obtain influences electricity service efficiency in the terminal
Factor, further includes:
When the factor is multiple, multiple factors are analyzed to the influence degree of electricity service efficiency, according to the influence
Degree height, screens multiple factors.
4. according to the method described in claim 2, it is characterized in that,
The factor includes the operating mode of present terminal, the application opened, and/or real-time discharge power.
5. the method according to claim 1, wherein generating the mind according to preset initial slope described
Before value through the node in network model, further includes:
According to the calculated performance of the terminal, the number of the value of the node is set；
The historical record that the terminal is used according to the user, modifies to the value of the node, comprising:
According to the number of the value of the node, value of the value of corresponding number as the node is chosen from the historical record.
6. the method according to claim 1, wherein in the history for using the terminal according to the user
Record, before modifying to the value of the node, further includes:
The identity for identifying the user, when the identity of the user meets preset condition, execution is described to be made according to the user
With the historical record of the terminal, modify to the value of the node.
7. according to the method described in claim 6, it is characterized in that, the identity of the identification user, comprising:
According to the account information that the fingerprint of the user and/or the user use, the identity of the user is identified.
8. the method according to claim 1, wherein being remembered according to the user using the history of the terminal
Record, before modifying to the value of the node, further includes:
The current load of the terminal is detected, when the load is lower than preset standard, is executed described according to user use
The historical record of the terminal modifies to the value of the node.
9. a kind of terminal, which is characterized in that the terminal includes processor, memory, communication bus；The communication bus is used for
Realize the connection communication between processor and memory；The processor is used to execute the terminal power stored in memory and uses
Time analysis program, the step of to realize method described in any item of the claim 1 to 8.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage have one or
Multiple programs, one or more of programs can be executed by one or more processor, to realize in claim 1 to 8
The step of described in any item methods.
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Cited By (1)
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