CN105093980B - Control the method and device of smart machine start and stop - Google Patents

Abstract

The present disclosure discloses a kind of method and device for controlling smart machine start and stop, belong to technical field of intelligent equipment.Method includes：Receive startup time and/or the dwell time of smart machine operation next time for the prediction that control terminal returns；Control the smart machine out of service according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the dwell time of operation next time.The startup time of smart machine operation next time for the prediction that the disclosure is returned by receiving control terminal and/or dwell time；Control the smart machine out of service according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the dwell time of operation next time.The use habit to the operating time of smart machine according to user is realized, automatically controls smart machine startup optimization and/or out of service, the cumbersome manipulation that user sets smart machine is reduced, improves usage experience of the smart machine to user.

Description

Control the method and device of smart machine start and stop

Technical field

This disclosure relates to technical field of intelligent equipment, more particularly to a kind of method and device for controlling smart machine start and stop.

Background technology

With the development of smart machine technology, all kinds of smart machines are gradually popularized in people live.Smart machine The operating habit of user can be recorded, and is that user provides more during intelligent terminal is subsequently used according to operating habit Convenient function is recommended.

Such as：Intelligent washing machine can record user's set operational mode every time, can be after repeatedly record When user is again started up intelligent washing machine, displays for a user last time or cumulative number reaches the operational mode of predetermined number of times, and It can directly be run after user confirms with the operational mode, avoid the cumbersome behaviour that user carries out selected operational mode Make.

The content of the invention

In order to solve the problems, such as correlation technique, the embodiment of the present disclosure provide a kind of method for controlling smart machine start and stop and Device.The technical scheme is as follows：

According to the first aspect of the embodiment of the present disclosure, there is provided a kind of method for controlling smart machine start and stop, methods described should For smart machine, including：

Receive startup time and/or the dwell time of smart machine operation next time for the prediction that control terminal returns；Institute That states smart machine operation next time of prediction starts the time of time and/or dwell time by the control terminal using prediction The history start-stop time ensemble prediction of point foregoing description smart machine obtains；

According to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time The dwell time of operation controls the smart machine out of service.

Optionally, smart machine next time described in the history start-stop time ensemble prediction according to corresponding to the smart machine The startup time of operation and/or dwell time include：

It is pre- using the startup time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm Survey the startup time of operation smart machine next time；Before decaying weighting algorithm using the time point predicted according to the time The startup of n times of smart machine formula of startup time of smart machine operation next time described in time prediction is：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, and a's takes Value scope is：0<a<1；When start (t-1) is the startup of 1 time nearest operation of the time point foregoing description smart machine of prediction Between, start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t- 3) it is the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) is prediction The startup time of the nearest n-th operation of time point foregoing description smart machine；

And/or

It is pre- using the dwell time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm Survey the dwell time of operation smart machine next time；Before decaying weighting algorithm using the time point predicted according to the time The dwell time of n times of the smart machine predicts that the formula of the dwell time of operation smart machine next time is：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；End (t-1) is the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, and end (t-2) is pre- The dwell time of the 2nd time nearest operation of the time point foregoing description smart machine of survey, end (t-3) be prediction time point it The dwell time of the 3rd time nearest operation of the preceding smart machine, end (t-n) are that the time point foregoing description of prediction is intelligently set The dwell time that standby nearest n-th is run.

Optionally, after each run, the startup time of this operation is sent to the control terminal；And/or each institute State smart machine it is out of service after, by this operation dwell time send to the control terminal.

Optionally, the smart machine startup optimization according to the startup time control of operation next time, including： When time reaches the startup time of operation next time, status query request message is sent to the control terminal；If receive The online response message that the control terminal returns, then control the smart machine startup optimization.

Optionally, the smart machine startup optimization according to the startup time control of operation next time, including： Before the startup time that time reaches the operation next time during preset time, the smart machine startup optimization is controlled.

According to the second aspect of the embodiment of the present disclosure, there is provided a kind of method for controlling smart machine start and stop, methods described should For control terminal, including：

Gathered according to the history start-stop time corresponding to the smart machine, predict the startup of operation smart machine next time Time and/or dwell time；

The startup time of operation next time and dwell time are sent to the smart machine.

Optionally, smart machine next time described in the history start-stop time ensemble prediction according to corresponding to the smart machine The startup time of operation and/or dwell time include：

It is pre- using the startup time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm Survey the startup time of operation smart machine next time；Before decaying weighting algorithm using the time point predicted according to the time The startup of n times of smart machine formula of startup time of smart machine operation next time described in time prediction is：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, and a's takes Value scope is：0<a<1；When start (t-1) is the startup of 1 time nearest operation of the time point foregoing description smart machine of prediction Between, start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t- 3) it is the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) is prediction The startup time of the nearest n-th operation of time point foregoing description smart machine；

And/or

It is pre- using the dwell time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm Survey the dwell time of operation smart machine next time；Before decaying weighting algorithm using the time point predicted according to the time The dwell time of n times of the smart machine predicts that the formula of the dwell time of operation smart machine next time is：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；End (t-1) is the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, and end (t-2) is pre- The dwell time of the 2nd time nearest operation of the time point foregoing description smart machine of survey, end (t-3) be prediction time point it The dwell time of the 3rd time nearest operation of the preceding smart machine, end (t-n) are that the time point foregoing description of prediction is intelligently set The dwell time that standby nearest n-th is run.

Optionally, methods described includes：When receiving the startup of this operation sent after the smart machine each run Between and/or dwell time.

Optionally, methods described also includes：By the startup time of this operation and/or dwell time in the intelligence Preserved in history start-stop time set corresponding to equipment.

According to the third aspect of the embodiment of the present disclosure, there is provided a kind of device for controlling smart machine start and stop, described device should For smart machine, including：

First receiving module, the startup time of smart machine operation next time of the prediction for receiving control terminal return And/or dwell time；The startup time of smart machine operation next time of the prediction and/or dwell time are by the control End is obtained using the history start-stop time ensemble prediction of the time point foregoing description smart machine of prediction；

Operation control module, for smart machine startup optimization described in the startup time control according to operation next time； And/or for controlling the smart machine out of service according to the dwell time of operation next time.

Optionally, the startup time of smart machine operation next time of the prediction and/or dwell time are by the control End processed is included using the history start-stop time ensemble prediction of the time point foregoing description smart machine of prediction：

The startup time of smart machine operation next time of the prediction is decayed by the control terminal according to the time to be weighted Algorithm is obtained using the startup time prediction of n times of the time point foregoing description smart machine of prediction；Decayed according to the time Weighting algorithm utilizes smart machine fortune next time described in the startup time prediction of n times of the time point foregoing description smart machine of prediction The formula of capable startup time is：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, and a's takes Value scope is：0<a<1；When start (t-1) is the startup of 1 time nearest operation of the time point foregoing description smart machine of prediction Between, start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t- 3) it is the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) is prediction The startup time of the nearest n-th operation of time point foregoing description smart machine；

And/or

The dwell time of smart machine operation next time of the prediction is decayed by the control terminal according to the time to be weighted Algorithm is predicted to obtain using the dwell time of n times of the time point foregoing description smart machine of prediction；Decayed according to the time Weighting algorithm predicts fortune smart machine next time using the dwell time of n times of the time point foregoing description smart machine of prediction The formula of capable dwell time is：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；End (t-1) is the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, and end (t-2) is pre- The dwell time of the 2nd time nearest operation of the time point foregoing description smart machine of survey, end (t-3) be prediction time point it The dwell time of the 3rd time nearest operation of the preceding smart machine, end (t-n) are that the time point foregoing description of prediction is intelligently set The dwell time that standby nearest n-th is run.

Optionally, described device also includes：

First sending module, for after each run, the startup time of this operation to be sent to the control terminal； And/or every time the smart machine it is out of service after, by this operation dwell time send to the control terminal.

Optionally, the operation control module, including：Transmitting element, for reaching opening for operation next time in the time During the dynamic time, status query request message is sent to the control terminal；First control unit, for receiving the control terminal During the online response message returned, the smart machine startup optimization is controlled.

Optionally, the operation control module, including：Second control unit, for reaching operation next time in the time The startup time before preset time when, control the smart machine startup optimization.

According to the fourth aspect of the embodiment of the present disclosure, there is provided a kind of device for controlling smart machine start and stop, described device should For control terminal, including：

Computing module, gather for the history start-stop time according to corresponding to the smart machine, predict the smart machine The startup time of operation next time and/or dwell time；

Second sending module, for the startup time of operation next time and/or dwell time to be sent into the intelligence Equipment.

Optionally, the set of the history start-stop time according to corresponding to the smart machine, is predicted under the smart machine The startup time of secondary operation and/or dwell time include：

It is pre- using the startup time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm Survey the startup time of operation smart machine next time；Before decaying weighting algorithm using the time point predicted according to the time The startup of n times of smart machine formula of startup time of smart machine operation next time described in time prediction is：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, and a's takes Value scope is：0<a<1；When start (t-1) is the startup of 1 time nearest operation of the time point foregoing description smart machine of prediction Between, start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t- 3) it is the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) is prediction The startup time of the nearest n-th operation of time point foregoing description smart machine；

And/or

It is pre- using the dwell time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm Survey the dwell time of operation smart machine next time；Before decaying weighting algorithm using the time point predicted according to the time The dwell time of n times of the smart machine predicts that the formula of the dwell time of operation smart machine next time is：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；End (t-1) is the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, and end (t-2) is pre- The dwell time of the 2nd time nearest operation of the time point foregoing description smart machine of survey, end (t-3) be prediction time point it The dwell time of the 3rd time nearest operation of the preceding smart machine, end (t-n) are that the time point foregoing description of prediction is intelligently set The dwell time that standby nearest n-th is run.

Optionally, described device also includes：Second receiving module, for being sent after receiving the smart machine each run This operation startup time and/or dwell time.

Optionally, described device also includes：Preserving module, for by it is described this operation the startup time and/or stopping Time is preserved in history start-stop time set corresponding to the smart machine.

According to the 5th of the embodiment of the present disclosure the aspect, there is provided a kind of device for controlling smart machine start and stop, described device should For smart machine, including：

Processor；

For storing the memory of processor-executable instruction；

Wherein, the processor is configured as：

Receive startup time and/or the dwell time of smart machine operation next time for the prediction that control terminal returns；Institute That states smart machine operation next time of prediction starts the time of time and/or dwell time by the control terminal using prediction The history start-stop time ensemble prediction of point foregoing description smart machine obtains；

According to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time The dwell time of operation controls the smart machine out of service.

According to the 6th of the embodiment of the present disclosure the aspect, there is provided a kind of device for controlling smart machine start and stop, described device should For terminal, including：

Processor；

For storing the memory of processor-executable instruction；

Wherein, the processor is configured as：

Gathered according to the history start-stop time corresponding to the smart machine, predict the startup of operation smart machine next time Time and/or dwell time；

The startup time of operation next time and/or dwell time are sent to the smart machine.

The technical scheme provided by this disclosed embodiment can include the following benefits：

When the startup time of smart machine operation next time of the prediction returned by receiving control terminal and/or stopping Between；According to smart machine startup optimization described in the startup time control of operation next time, and/or according to operation next time Dwell time controls the smart machine out of service.Realize and practised according to use of the user to the operating time of smart machine It is used, smart machine startup optimization and/or out of service is automatically controlled, the cumbersome manipulation that user sets smart machine is reduced, carries High usage experience of the smart machine to user.

Brief description of the drawings

Accompanying drawing herein is merged in specification and forms the part of this specification, shows the implementation for meeting the disclosure Example, and be used to together with specification to explain the principle of the disclosure.

Fig. 1 is a kind of flow chart of the method for control smart machine start and stop according to an exemplary embodiment；

Fig. 2 is a kind of flow chart of the method for control smart machine start and stop according to an exemplary embodiment；

Fig. 3 is a kind of flow chart of the method for control smart machine start and stop according to an exemplary embodiment；

Fig. 4 is a kind of block diagram of the device of control smart machine start and stop according to an exemplary embodiment；

Fig. 5 be a kind of control smart machine start and stop according to an exemplary embodiment device in starting module frame Figure；

Fig. 6 is a kind of block diagram of the device of control smart machine start and stop according to an exemplary embodiment；

Fig. 7 is that a kind of block diagram of the device of control smart machine start and stop according to an exemplary embodiment (is intelligently set Standby general structure)；

Fig. 8 is a kind of block diagram (control terminal of the device of control smart machine start and stop according to an exemplary embodiment General structure)；

Fig. 9 is a kind of block diagram (control terminal of the device of control smart machine start and stop according to an exemplary embodiment General structure).

Embodiment

To make the purpose, technical scheme and advantage of the disclosure clearer, below in conjunction with accompanying drawing to disclosure embodiment party Formula is described in further detail.

The exemplary embodiment of the disclosure one provides a kind of method for controlling smart machine start and stop, this method embodiment application In smart machine, referring to Fig. 1, method flow includes：

In a step 101, startup time and/or the stopping of smart machine operation next time for the prediction that control terminal returns are received Time；Smart machine operation next time of prediction start time and/or dwell time by control terminal using prediction time point it The history start-stop time ensemble prediction of preceding smart machine obtains；

In a step 102, according to the startup time control smart machine startup optimization of operation next time, and/or according to next time The dwell time control smart machine of operation is out of service.

The disclosure is by receiving the startup time of smart machine operation next time of the prediction of control terminal return and/or stopping The only time；Transported according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time Capable dwell time controls the smart machine out of service.Realize according to use of the user to the operating time of smart machine Custom, smart machine startup optimization and/or out of service is automatically controlled, reduces the cumbersome manipulation that user sets smart machine, Improve usage experience of the smart machine to user.

Disclosure another exemplary embodiment provides a kind of method for controlling smart machine start and stop, and this method embodiment should For in control terminal, referring to Fig. 2, method flow to include：

In step 201, the history start-stop time gathers according to corresponding to smart machine, prediction smart machine operation next time Start time and/or dwell time；

In step 202, the startup time of operation next time and/or dwell time are sent to smart machine.

Wherein, control terminal can include but is not limited to：Terminal and/or server.

Disclosure history start-stop time according to corresponding to smart machine gathers, when predicting the startup of smart machine operation next time Between and/or dwell time, and by next time operation the startup time and/or dwell time return to smart machine.Realize basis User automatically controls smart machine startup optimization and/or out of service, reduction to the use habit of the operating time of smart machine User sets the cumbersome manipulation of smart machine, improves usage experience of the smart machine to user.

Disclosure another exemplary embodiment provides a kind of method for controlling smart machine start and stop, referring to Fig. 3.

In step 301, smart machine sends the startup time of this operation to control terminal after each run；With/ Or every time smart machine it is out of service after, by this operation dwell time send to control terminal.

Wherein, the embodiment of the present disclosure is described by taking intelligent air condition as an example.Intelligent air condition is being controlled manually by user every time Startup optimization and/or it is out of service when can to this operation the startup time and/or dwell time record.Wherein, user Control intelligent air condition startup optimization and/or mode out of service can be manually：User is opened by being operated in remote control equipment Close button and perform startup optimization instruction and instruction out of service；Can also be user by remote control equipment operating and setting be delayed Startup optimization instructs and the instruction out of service that is delayed, and can distinguish in the delayed startup operating instruction and delay instruction out of service Time including delay.

By taking the workaday daily schedule as an example, user is using the temporal regularity of intelligent air condition very strong, is typically going home After can by intelligent air condition start and open sleep pattern before sleeping, intelligent air condition can be according to the finger out of service that is delayed in sleep pattern Make out of service.

The each startup optimization of intelligent air condition to it is out of service be a cycle of operation, complete one when out of service The cycle of operation, now intelligent air condition can be by the radio connection between control terminal, by the current cycle of operation of record Start the time and dwell time is sent to control terminal.

Wherein, incidence relation is pre-established between smart machine and control terminal.Establishing the mode of incidence relation can be：It is logical The wireless transmission method specified certified transmission code between smart machine and control terminal is crossed to be matched, and the intelligence after successful matching The mark of other side can be recorded between equipment and control terminal respectively.Wherein, wireless transmission method can be Bluetooth transmission mode, WiFi (WIreless-Fidelity, Wireless Fidelity) transmission means etc..

In step 302, control terminal receive smart machine each run after send this operation startup time and/or Dwell time.

In step 303, control terminal is going through startup time that this runs and/or dwell time corresponding to smart machine Preserved in the set of history start-stop time.

In step 304, the history start-stop time gathers according to corresponding to smart machine, prediction smart machine operation next time Start time and/or dwell time.

Optionally, the startup time of smart machine operation next time of prediction is sharp according to time decay weighting algorithm by control terminal Obtained with the startup time prediction of n times of smart machine before the time point of prediction；Optionally, smart machine fortune next time of prediction Capable dwell time is stopped by control terminal according to time weighting algorithm of decaying using n times of smart machine before the time point of prediction Only time prediction obtains；

It has recorded in the set of history start-stop time and start the time corresponding to each cycle of operation of smart machine feedback and stop The only time, it can be designated as respectively：Start and end data.Accordingly, the history startup time can be respectively：start(1),…, start(t-1)；History dwell time can be respectively：end(1),…,end(t-1).Need fortune next time that prediction is calculated The capable startup time is start (t) and dwell time is end (t).

During user uses smart machine, the influence of the last startup time and dwell time is bigger, distance The influence of current time more remote startup time and dwell time is smaller.Therefore can be declined by setting one in weighting algorithm Subtracting coefficient, in the startup time of prediction operation next time and during dwell time, embody according to start time and dwell time with it is current The influence of time distance.

Wherein, decayed the startup time of n time of the weighting algorithm using smart machine before the time point of prediction according to the time The formula of startup time of prediction smart machine operation next time is：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；The startup time of 1 time nearest operation of smart machine, start before the time point that start (t-1) is prediction (t-2) be the startup time of the 2nd time nearest operation of smart machine before the time point of prediction, start (t-3) be prediction when Between put before nearest the 3rd operation of smart machine the startup time, intelligence is set before the time point that start (t-n) is prediction The startup time that standby nearest n-th is run；

Intelligence is predicted using the dwell time of n times of smart machine before the time point of prediction according to time decay weighting algorithm Can the formula of dwell time of equipment operation next time be：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；The dwell time of 1 time nearest operation of smart machine, end (t-2) are prediction before the time point that end (t-1) is prediction The dwell time of the 2nd time nearest operation of smart machine before time point, intelligence is set before the time point that end (t-3) is prediction The dwell time of standby the 3rd time nearest operation, the nearest n-th operation of smart machine before the time point that end (t-n) is prediction Dwell time.

Further, because the time is not a numerical value, such as：19:00.Therefore need that time or stopping will be started Time is converted to numerical value, and above-mentioned formula of bringing into that can be easier is predicted calculating.

Optionally, converting the time into the mode of numerical value can be：

Time is changed in seconds, such as：00:10, it can be converted to 600 seconds.

Optionally, converting the time into the mode of numerical value can also be：

Time is changed in units of minute, such as：00:10, it can be converted to 60 minutes.

Accordingly, when calculating the startup time of operation next time and dwell time, by the startup time of operation next time and stop Only each in time and the set of history start-stop time starts time and dwell time and is converted to numerical value, and brings above-mentioned public affairs into Formula is predicted calculating.

In step 305, the startup time of operation next time and/or dwell time are sent to smart machine.

Within step 306, startup time and/or the stopping of smart machine operation next time for the prediction that control terminal returns are received Time；Smart machine operation next time of prediction start time and/or dwell time by control terminal using prediction time point it The history start-stop time ensemble prediction of preceding smart machine obtains.

In step 307, according to the startup time control smart machine startup optimization of operation next time.

Mode according to the startup time control smart machine startup optimization of operation next time can be following two modes：

First way：

Smart machine is when reaching for the second startup time, it is necessary to judge whether user is in smart machine identical space In, such as：Intelligent air condition judges whether user is in, if it is determined that just can startup optimization when user is in.Accordingly, step 307 can be realized by following steps：

In step 3071, when the startup time of operation next time is reached in the time, status query request is sent to control terminal Message；

In step 3072, if receiving the online response message of control terminal return, control smart machine starts fortune OK.

The second way：

Smart machine pre-actuates before the startup time of operation next time is reached.Such as：User is 5 points before coming home from work Clock starts intelligent air condition, then the temperature when user is to family in family has declined due to intelligent air condition pre-cooling, in family Environment can enter comfort conditions when user is to family.Accordingly, step 307 can be realized by following steps：

In step 3073, before the time reaches the startup time of operation next time during preset time, smart machine is controlled Startup optimization.

In step 308, control smart machine out of service according to the dwell time of operation next time.

The disclosure is by receiving the startup time of smart machine operation next time of the prediction of control terminal return and/or stopping The only time；Transported according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time Capable dwell time controls the smart machine out of service.Realize according to use of the user to the operating time of smart machine Custom, smart machine startup optimization and/or out of service is automatically controlled, reduces the cumbersome manipulation that user sets smart machine, Improve usage experience of the smart machine to user.

In addition, the history start-stop time according to corresponding to smart machine gathers, when predicting the startup of smart machine operation next time Between and/or dwell time, and by next time operation the startup time and/or dwell time return to smart machine.Realize basis User automatically controls smart machine startup optimization and/or out of service, reduction to the use habit of the operating time of smart machine User sets the cumbersome manipulation of smart machine, improves usage experience of the smart machine to user.

In the disclosure, optionally, the startup time of smart machine operation next time can be only predicted, can only predict that intelligence is set The dwell time of standby operation next time, startup time and the dwell time of smart machine operation next time can also be predicted simultaneously.Only When predicting the startup time of smart machine operation next time, step 308 can not be performed.Only predicting smart machine operation next time During dwell time, step 307 can not be performed.Startup time and the dwell time of smart machine operation next time are predicted at the same time When, perform step 307 and step 308.

The method of the control smart machine start and stop provided corresponding to above-mentioned example embodiment, disclosure another exemplary are real Apply example and provide a kind of device for controlling smart machine start and stop, the device is applied to smart machine, and referring to Fig. 4, the device includes：

First receiving module 401, the startup time of smart machine operation next time of the prediction for receiving control terminal return And/or dwell time；Start time and/or the dwell time of smart machine operation next time of prediction utilize prediction by control terminal The history start-stop time ensemble prediction of smart machine obtains before time point；

Operation control module 402, for the startup time control smart machine startup optimization according to operation next time；And/or For controlling smart machine out of service according to the dwell time of operation next time.

Optionally, wherein, the startup time of smart machine operation next time of prediction and/or dwell time are utilized by control terminal The history start-stop time ensemble prediction of smart machine is included before the time point of prediction：

The startup time of smart machine operation next time of prediction utilizes prediction by control terminal according to time decay weighting algorithm Time point before the startup time prediction of n times of smart machine obtain；

The startup time prediction intelligence of n times according to time decay weighting algorithm using smart machine before the time point of prediction Can the formula of startup time of equipment operation next time be：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；The startup time of 1 time nearest operation of smart machine, start before the time point that start (t-1) is prediction (t-2) be the startup time of the 2nd time nearest operation of smart machine before the time point of prediction, start (t-3) be prediction when Between put before nearest the 3rd operation of smart machine the startup time, intelligence is set before the time point that start (t-n) is prediction The startup time that standby nearest n-th is run；

And/or

Optionally, the dwell time of smart machine operation next time of prediction is sharp according to time decay weighting algorithm by control terminal Predict to obtain with the dwell time of n times of smart machine before the time point of prediction；Weighting algorithm is decayed using in advance according to the time The formula of the dwell time of prediction smart machine operation next time of the dwell time of n times of smart machine is before the time point of survey：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；The dwell time of 1 time nearest operation of smart machine, end (t-2) are prediction before the time point that end (t-1) is prediction The dwell time of the 2nd time nearest operation of smart machine before time point, intelligence is set before the time point that end (t-3) is prediction The dwell time of standby the 3rd time nearest operation, the nearest n-th operation of smart machine before the time point that end (t-n) is prediction Dwell time.

Wherein, device also includes：

First sending module 404, for after each run, the startup time of this operation to be sent to control terminal；With/ Or every time smart machine it is out of service after, by this operation dwell time send to control terminal.

Wherein, as shown in figure 5, operation control module 402, including：

Transmitting element 4021, for when the time reaching the startup time that next time is run, status inquiry to be sent to control terminal Request message；

First control unit 4022, for when receiving the online response message of control terminal return, controlling smart machine Startup optimization.

Wherein, as shown in figure 5, operation control module 402, including：

Second control unit 4023, before the startup time for reaching operation next time in the time during preset time, control Smart machine startup optimization.

The disclosure is by receiving the startup time of smart machine operation next time of the prediction of control terminal return and/or stopping The only time；Transported according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time Capable dwell time controls the smart machine out of service.Realize according to use of the user to the operating time of smart machine Custom, smart machine startup optimization and/or out of service is automatically controlled, reduces the cumbersome manipulation that user sets smart machine, Improve usage experience of the smart machine to user.

The method of the control smart machine start and stop provided corresponding to above-mentioned example embodiment, disclosure another exemplary are real Apply example and provide a kind of device for controlling smart machine start and stop, the device is applied to control terminal, and referring to Fig. 6, the device includes：

Computing module 601, gather for the history start-stop time according to corresponding to smart machine, prediction smart machine fortune next time Capable startup time and/or dwell time；

Second sending module 602, for the startup time of operation next time and/or dwell time to be sent into smart machine.

Wherein, computing module 601 is used for：

The startup time prediction intelligence of n times according to time decay weighting algorithm using smart machine before the time point of prediction Can the equipment next startup time run；N according to time decay weighting algorithm using smart machine before the time point of prediction The formula of the startup time of secondary operation startup time prediction smart machine next time is：

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；The startup time of 1 time nearest operation of smart machine, start before the time point that start (t-1) is prediction (t-2) be the startup time of the 2nd time nearest operation of smart machine before the time point of prediction, start (t-3) be prediction when Between put before nearest the 3rd operation of smart machine the startup time, intelligence is set before the time point that start (t-n) is prediction The startup time that standby nearest n-th is run；

And/or

Intelligence is predicted using the dwell time of n times of smart machine before the time point of prediction according to time decay weighting algorithm Can the next dwell time run of equipment；N according to time decay weighting algorithm using smart machine before the time point of prediction Secondary dwell time predicts that the formula of the dwell time of smart machine operation next time is：

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a< 1；The dwell time of 1 time nearest operation of smart machine, end (t-2) are prediction before the time point that end (t-1) is prediction The dwell time of the 2nd time nearest operation of smart machine before time point, intelligence is set before the time point that end (t-3) is prediction The dwell time of standby the 3rd time nearest operation, the nearest n-th operation of smart machine before the time point that end (t-n) is prediction Dwell time.

Wherein, device also includes：

Second receiving module 603, for receive this operation sent after smart machine each run startup time and/ Or dwell time.

Wherein, device also includes：

Preserving module 604, for the startup time for running this and/or dwell time in history corresponding to smart machine Preserved in start-stop time set.

Disclosure history start-stop time according to corresponding to smart machine gathers, when predicting the startup of smart machine operation next time Between and/or dwell time, and by next time operation the startup time and/or dwell time return to smart machine.Realize basis User automatically controls smart machine startup optimization and/or out of service, reduction to the use habit of the operating time of smart machine User sets the cumbersome manipulation of smart machine, improves usage experience of the smart machine to user.

The control device of the wireless access points provided corresponding to above-mentioned example embodiment, disclosure another exemplary Embodiment provides a kind of smart machine 700, referring to Fig. 7.For example, smart machine 700 can be mobile phone, and computer, number Word broadcast terminal, messaging devices, game console, tablet device, Medical Devices, body-building equipment, personal digital assistant, intelligence Energy equipment etc..Alternatively, smart machine 700 can also be intelligent router, Intelligent air purifier, intelligent water purifier, intelligence Image first-class.

Reference picture 7, smart machine 700 can include following one or more assemblies：Processing component 702, memory 704, Electric power assembly 706, multimedia groupware 708, audio-frequency assembly 710, the interface 712 of input/output (I/O), sensor cluster 714, And communication component 716.

Processing component 702 generally controls the integrated operation of smart machine 700, such as leads to display, call, data The operation that letter, camera operation and record operation are associated.Processing component 702 can include one or more processors 720 to hold Row instruction, to complete all or part of step of above-mentioned method.In addition, processing component 702 can include one or more moulds Block, the interaction being easy between processing component 702 and other assemblies.For example, processing component 702 can include multi-media module, with Facilitate the interaction between multimedia groupware 708 and processing component 702.

Memory 704 is configured as storing various types of data to support the operation in equipment 700.These data are shown Example includes the instruction of any application program or method for being operated on smart machine 700, contact data, telephone directory number According to, message, picture, video etc..Memory 704 can by any kind of volatibility or non-volatile memory device or they Combination realize, as static RAM (SRAM), Electrically Erasable Read Only Memory (EEPROM) are erasable Programmable read only memory (EPROM), programmable read only memory (PROM), read-only storage (ROM), magnetic memory, quick flashing Memory, disk or CD.

Electric power assembly 706 provides electric power for the various assemblies of smart machine 700.Electric power assembly 706 can include power supply pipe Reason system, one or more power supplys, and other components associated with generating, managing and distributing electric power for smart machine 700.

Multimedia groupware 708 is included in the screen of one output interface of offer between the smart machine 700 and user. In certain embodiments, screen can include liquid crystal display (LCD) and touch panel (TP).If screen includes touch surface Plate, screen may be implemented as touch-screen, to receive the input signal from user.Touch panel includes one or more touch Sensor is with the gesture on sensing touch, slip and touch panel.The touch sensor can not only sensing touch or slip The border of action, but also detect the duration and pressure related to the touch or slide.In certain embodiments, Multimedia groupware 708 includes a front camera and/or rear camera.When equipment 700 is in operator scheme, mould is such as shot When formula or video mode, front camera and/or rear camera can receive outside multi-medium data.Each preposition shooting Head and rear camera can be a fixed optical lens system or have focusing and optical zoom capabilities.

Audio-frequency assembly 710 is configured as output and/or input audio signal.For example, audio-frequency assembly 710 includes a Mike Wind (MIC), when smart machine 700 is in operator scheme, during such as call model, logging mode and speech recognition mode, microphone It is configured as receiving external audio signal.The audio signal received can be further stored in memory 704 or via logical Letter component 716 is sent.In certain embodiments, audio-frequency assembly 710 also includes a loudspeaker, for exports audio signal.

I/O interfaces 712 provide interface between processing component 702 and peripheral interface module, and above-mentioned peripheral interface module can To be keyboard, click wheel, button etc..These buttons may include but be not limited to：Home button, volume button, start button and lock Determine button.

Sensor cluster 714 includes one or more sensors, for providing the state of various aspects for smart machine 700 Assess.For example, sensor cluster 714 can detect opening/closed mode of equipment 700, the relative positioning of component, such as institute The display and keypad that component is smart machine 700 are stated, sensor cluster 714 can also detect smart machine 700 or intelligence The position of 700 1 components of equipment changes, the existence or non-existence that user contacts with smart machine 700, the orientation of smart machine 700 Or acceleration/deceleration and the temperature change of smart machine 700.Sensor cluster 714 can include proximity transducer, be configured to The presence of object nearby is detected in no any physical contact.Sensor cluster 714 can also include optical sensor, such as CMOS or ccd image sensor, for being used in imaging applications.In certain embodiments, the sensor cluster 714 can be with Including acceleration transducer, gyro sensor, Magnetic Sensor, pressure sensor or temperature sensor.

Communication component 716 is configured to facilitate the communication of wired or wireless way between smart machine 700 and other equipment. Smart machine 700 can access the wireless network based on communication standard, such as WiFi, 2G or 3G, or combinations thereof.Show at one In example property embodiment, communication component 716 receives broadcast singal or broadcast from external broadcasting management system via broadcast channel Relevant information.In one exemplary embodiment, the communication component 716 also includes near-field communication (NFC) module, short to promote Cheng Tongxin.For example, radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band can be based in NFC module (UWB) technology, bluetooth (BT) technology and other technologies are realized.

In the exemplary embodiment, smart machine 700 can be by one or more application specific integrated circuits (ASIC), number Word signal processor (DSP), digital signal processing appts (DSPD), PLD (PLD), field programmable gate array (FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for performing the above method.

In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instructing, example are additionally provided Such as include the memory 704 of instruction, above-mentioned instruction can be performed to complete the above method by the processor 720 of smart machine 700.Example Such as, the non-transitorycomputer readable storage medium can be ROM, it is random access memory (RAM), CD-ROM, tape, soft Disk and optical data storage devices etc..

The startup time of smart machine operation next time for the prediction that the disclosure is returned by receiving control terminal and stopping Time；According to smart machine startup optimization described in the startup time control of operation next time, and according to operation next time Dwell time controls the smart machine out of service.Realize and practised according to use of the user to the operating time of smart machine It is used, smart machine startup optimization and/or out of service is automatically controlled, the cumbersome manipulation that user sets smart machine is reduced, carries High usage experience of the smart machine to user.

The device of the control smart machine start and stop provided corresponding to above-mentioned example embodiment, disclosure another exemplary are real Apply example and provide a kind of control terminal 800, referring to Fig. 8.For example, control terminal 800 can be mobile phone, and computer, digital broadcasting Control terminal, messaging devices, game console, tablet device, Medical Devices, body-building equipment, personal digital assistant etc..

Reference picture 8, control terminal 800 can include following one or more assemblies：Processing component 802, memory 804, electricity Power component 806, multimedia groupware 808, audio-frequency assembly 810, the interface 812 of input/output (I/O), sensor cluster 815, with And communication component 816.

Processing component 802 generally controls the integrated operation of control terminal 800, is such as communicated with display, call, data, The operation that camera operation and record operation are associated.Processing component 802 can refer to including one or more processors 820 to perform Order, to complete all or part of step of above-mentioned method.In addition, processing component 802 can include one or more modules, just Interaction between processing component 802 and other assemblies.For example, processing component 802 can include multi-media module, it is more to facilitate Interaction between media component 808 and processing component 802.

Memory 804 is configured as storing various types of data to support the operation in equipment 800.These data are shown Example includes being used for the instruction of any application program or method operated in control terminal 800, contact data, telephone book data, Message, picture, video etc..Memory 804 can by any kind of volatibility or non-volatile memory device or they Combination is realized, such as static RAM (SRAM), Electrically Erasable Read Only Memory (EEPROM), it is erasable can Program read-only memory (EPROM), programmable read only memory (PROM), read-only storage (ROM), magnetic memory, flash memory Reservoir, disk or CD.

Electric power assembly 806 provides electric power for the various assemblies of control terminal 800.Electric power assembly 806 can include power management System, one or more power supplys, and other components associated with generating, managing and distributing electric power for control terminal 800.

Multimedia groupware 808 is included in the screen of one output interface of offer between control terminal 800 and user.At some In embodiment, screen can include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel, screen Touch-screen is may be implemented as, to receive the input signal from user.Touch panel includes one or more touch sensors With the gesture on sensing touch, slip and touch panel.Touch sensor can the not only border of sensing touch or sliding action, But also the duration and pressure that detection is related to touch or slide.In certain embodiments, multimedia groupware 808 wraps Include a front camera and/or rear camera.When equipment 800 is in operator scheme, during such as screening-mode or video mode, Front camera and/or rear camera can receive the multi-medium data of outside.Each front camera and rear camera It can be a fixed optical lens system or there is focusing and optical zoom capabilities.

Audio-frequency assembly 810 is configured as output and/or input audio signal.For example, audio-frequency assembly 810 includes a Mike Wind (MIC), when control terminal 800 is in operator scheme, during such as call model, logging mode and speech recognition mode, microphone quilt It is configured to receive external audio signal.The audio signal received can be further stored in memory 804 or via communication Component 816 is sent.In certain embodiments, audio-frequency assembly 810 also includes a loudspeaker, for exports audio signal.

I/O interfaces 812 provide interface between processing component 802 and peripheral interface module, and above-mentioned peripheral interface module can To be keyboard, click wheel, button etc..These buttons may include but be not limited to：Home button, volume button, start button and lock Determine button.

Sensor cluster 815 includes one or more sensors, and the state for providing various aspects for control terminal 800 is commented Estimate.For example, sensor cluster 815 can detect opening/closed mode of equipment 800, the relative positioning of component, such as component For the display and keypad of control terminal 800, sensor cluster 815 can also detect 800 1 groups of control terminal 800 or control terminal The position of part changes, the existence or non-existence that user contacts with control terminal 800, the orientation of control terminal 800 or acceleration/deceleration and control The temperature change at end 800.Sensor cluster 815 can include proximity transducer, be configured to connect in no any physics The presence of object nearby is detected when touching.Sensor cluster 815 can also include optical sensor, such as CMOS or ccd image sensor, For being used in imaging applications.In certain embodiments, the sensor cluster 815 can also include acceleration transducer, top Spiral shell instrument sensor, Magnetic Sensor, pressure sensor or temperature sensor.

Communication component 816 is configured to facilitate the communication of wired or wireless way between control terminal 800 and other equipment.Control End 800 processed can access the wireless network based on communication standard, such as WiFi, 2G or 3G, or combinations thereof.It is exemplary at one In embodiment, communication component 816 receives broadcast singal or broadcast correlation from external broadcasting management system via broadcast channel Information.In one exemplary embodiment, communication component 816 also includes near-field communication (NFC) module, to promote junction service. For example, radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band (UWB) skill can be based in NFC module Art, bluetooth (BT) technology and other technologies are realized.

In the exemplary embodiment, control terminal 800 can be by one or more application specific integrated circuits (ASIC), numeral Signal processor (DSP), digital signal processing appts (DSPD), PLD (PLD), field programmable gate array (FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for performing the above method.

In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instructing, example are additionally provided Such as include the memory 804 of instruction, above-mentioned instruction can be performed to complete the above method by the processor 820 of terminal 800.For example, Non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, tape, floppy disk and light Data storage device etc..

Disclosure history start-stop time according to corresponding to smart machine gathers, when predicting the startup of smart machine operation next time Between and dwell time, and by next time operation the startup time and dwell time return to smart machine.Realize according to user couple The use habit of the operating time of smart machine, smart machine startup optimization and/or out of service is automatically controlled, reduces user The cumbersome manipulation of smart machine is set, improves usage experience of the smart machine to user.

The method of the control smart machine start and stop provided corresponding to above-mentioned example embodiment, disclosure another exemplary are real Apply example and provide a kind of control terminal 900, Fig. 9 is that one kind according to an exemplary embodiment is used to control smart machine start and stop Control terminal 900 block diagram.For example, control terminal 900 may be provided in a server.Reference picture 9, control terminal 900 include place Component 922 is managed, it further comprises one or more processors, and as the memory resource representated by memory 932, is used for Storage can be by the instruction of the execution of processing component 922, such as application program.The application program stored in memory 932 can wrap Include it is one or more each correspond to the module of one group of instruction.Refer in addition, processing component 922 is configured as execution Order, to perform the method for above-mentioned control smart machine start and stop.

Control terminal 900 can also include a power supply module 926 be configured as perform control terminal 900 power management, one Individual wired or wireless network interface 950 is configured as control terminal 900 being connected to network, and input and output (I/O) interface 958.Control terminal 900 can be operated based on the operating system for being stored in memory 932, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM or similar.

Disclosure history start-stop time according to corresponding to smart machine gathers, when predicting the startup of smart machine operation next time Between and dwell time, and by next time operation the startup time and dwell time return to smart machine.Realize according to user couple The use habit of the operating time of smart machine, smart machine startup optimization and/or out of service is automatically controlled, reduces user The cumbersome manipulation of smart machine is set, improves usage experience of the smart machine to user.

Those skilled in the art will readily occur to the disclosure its after considering specification and putting into practice invention disclosed herein Its embodiment.The application is intended to any modification, purposes or the adaptations of the disclosure, these modifications, purposes or Person's adaptations follow the general principle of the disclosure and including the undocumented common knowledges in the art of the disclosure Or conventional techniques.Description and embodiments are considered only as exemplary, and the true scope of the disclosure and spirit are by following Claim is pointed out.

It should be appreciated that the invention is not limited in the precision architecture for being described above and being shown in the drawings, and And various modifications and changes can be being carried out without departing from the scope.The scope of the present invention is only limited by appended claim.

Claims (16)

1. a kind of method for controlling smart machine start and stop, methods described are applied to smart machine, it is characterised in that methods described bag Include：

Receive startup time and/or the dwell time of smart machine operation next time for the prediction that control terminal returns；It is described pre- The time that starts for smart machine operation next time surveyed utilizes prediction by the control terminal according to time decay weighting algorithm The startup time prediction of n times of time point foregoing description smart machine obtains；Weighting algorithm is decayed using in advance according to the time N times of the time point foregoing description smart machine of survey starts the startup time of smart machine operation next time described in time prediction Formula is：

<mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；Start (t-1) is the startup time of 1 time nearest operation of the time point foregoing description smart machine of prediction, Start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t-3) For the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) be prediction when Between put foregoing description smart machine it is nearest n-th operation the startup time；

And/or

The dwell time of smart machine operation next time of the prediction is by the control terminal according to time decay weighting algorithm Predict to obtain using the dwell time of n times of the time point foregoing description smart machine of prediction；Decayed according to the time and weighted Algorithm predicts operation smart machine next time using the dwell time of n times of the time point foregoing description smart machine of prediction The formula of dwell time is：

<mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a<1；end (t-1) be the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, end (t-2) be prediction when Between put the dwell time of the 2nd time nearest operation of foregoing description smart machine, end (t-3) is the time point foregoing description of prediction The dwell time of the 3rd time nearest operation of smart machine, end (t-n) are that the time point foregoing description smart machine of prediction is nearest N-th operation dwell time；

Run according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time Dwell time control the smart machine out of service.

2. according to the method for claim 1, it is characterised in that methods described includes：After each run, this is run The startup time send to the control terminal；And/or every time the smart machine it is out of service after, by this operation stopping when Between send to the control terminal.

3. according to the method for claim 1, it is characterised in that the startup time control institute according to operation next time Smart machine startup optimization is stated, including：

When the startup time of operation next time is reached in the time, status query request message is sent to the control terminal；

If receiving the online response message that the control terminal returns, the smart machine startup optimization is controlled.

4. according to the method for claim 1, it is characterised in that the startup time control institute according to operation next time Smart machine startup optimization is stated, including：

Before the startup time of the time arrival operation next time during preset time, the smart machine startup optimization is controlled.

5. a kind of method for controlling smart machine start and stop, methods described are applied to control terminal, it is characterised in that methods described bag Include：

The startup time prediction institute of n times according to time decay weighting algorithm using the time point foregoing description smart machine of prediction State the startup time of smart machine operation next time；The time point foregoing description according to time decay weighting algorithm using prediction The startup of n times of smart machine formula of startup time of smart machine operation next time described in time prediction is：

<mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；Start (t-1) is the startup time of 1 time nearest operation of the time point foregoing description smart machine of prediction, Start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t-3) For the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) be prediction when Between put foregoing description smart machine it is nearest n-th operation the startup time；

And/or

Institute is predicted using the dwell time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm State the dwell time of smart machine operation next time；The time point foregoing description according to time decay weighting algorithm using prediction The dwell time of n times of smart machine predicts that the formula of the dwell time of operation smart machine next time is：

<mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a<1；end (t-1) be the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, end (t-2) be prediction when Between put the dwell time of the 2nd time nearest operation of foregoing description smart machine, end (t-3) is the time point foregoing description of prediction The dwell time of the 3rd time nearest operation of smart machine, end (t-n) are that the time point foregoing description smart machine of prediction is nearest N-th operation dwell time；

The startup time of operation next time and dwell time are sent to the smart machine.

6. according to the method for claim 5, it is characterised in that methods described includes：The smart machine is received to transport every time The startup time of this operation sent after row and/or dwell time.

7. according to the method for claim 6, it is characterised in that methods described also includes：

The startup time of this operation and/or dwell time are gathered in the history start-stop time corresponding to the smart machine In preserved.

8. a kind of device for controlling smart machine start and stop, described device are applied to smart machine, it is characterised in that described device bag Include：

First receiving module, for receive control terminal return prediction the smart machine next time operation the startup time and/ Or dwell time；The startup time of smart machine operation next time of the prediction is added by the control terminal according to time decay Power algorithm is obtained using the startup time prediction of n times of the time point foregoing description smart machine of prediction；Declined according to the time Subtract weighting algorithm using smart machine next time described in the startup time prediction of n times of the time point foregoing description smart machine of prediction The formula of the startup time of operation is：

<mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；Start (t-1) is the startup time of 1 time nearest operation of the time point foregoing description smart machine of prediction, Start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t-3) For the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) be prediction when Between put foregoing description smart machine it is nearest n-th operation the startup time；

And/or

The dwell time of smart machine operation next time of the prediction is by the control terminal according to time decay weighting algorithm Predict to obtain using the dwell time of n times of the time point foregoing description smart machine of prediction；Decayed according to the time and weighted Algorithm predicts operation smart machine next time using the dwell time of n times of the time point foregoing description smart machine of prediction The formula of dwell time is：

<mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a<1；end (t-1) be the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, end (t-2) be prediction when Between put the dwell time of the 2nd time nearest operation of foregoing description smart machine, end (t-3) is the time point foregoing description of prediction The dwell time of the 3rd time nearest operation of smart machine, end (t-n) are that the time point foregoing description smart machine of prediction is nearest N-th operation dwell time；

Operation control module, for smart machine startup optimization described in the startup time control according to operation next time；And/or For controlling the smart machine out of service according to the dwell time of operation next time.

9. device according to claim 8, it is characterised in that described device also includes：

First sending module, for after each run, the startup time of this operation to be sent to the control terminal；And/or After each smart machine is out of service, the dwell time of this operation is sent to the control terminal.

10. device according to claim 8, it is characterised in that the operation control module, including：

Transmitting element, for the time reach it is described next time operation the startup time when, to the control terminal send status inquiry Request message；

First control unit, for when receiving the online response message that the control terminal returns, controlling the smart machine Startup optimization.

11. device according to claim 8, it is characterised in that the operation control module, including：

Second control unit, before the startup time for reaching operation next time in the time during preset time, described in control Smart machine startup optimization.

12. a kind of device for controlling smart machine start and stop, described device are applied to control terminal, it is characterised in that described device bag Include：

Computing module, for being utilized n time of time point foregoing description smart machine of prediction according to time weighting algorithm of decaying Start the startup time of smart machine operation next time described in time prediction；Prediction is utilized according to time decay weighting algorithm The formula for starting the startup time of smart machine operation next time described in time prediction of n times of time point foregoing description smart machine For：

<mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>n</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；Start (t-1) is the startup time of 1 time nearest operation of the time point foregoing description smart machine of prediction, Start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t-3) For the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) be prediction when Between put foregoing description smart machine it is nearest n-th operation the startup time；

And/or

Institute is predicted using the dwell time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm State the dwell time of smart machine operation next time；The time point foregoing description according to time decay weighting algorithm using prediction The dwell time of n times of smart machine predicts that the formula of the dwell time of operation smart machine next time is：

<mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a<1；end (t-1) be the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, end (t-2) be prediction when Between put the dwell time of the 2nd time nearest operation of foregoing description smart machine, end (t-3) is the time point foregoing description of prediction The dwell time of the 3rd time nearest operation of smart machine, end (t-n) are that the time point foregoing description smart machine of prediction is nearest N-th operation dwell time；

Second sending module, for the startup time of operation next time and/or dwell time to be sent into the smart machine.

13. device according to claim 12, it is characterised in that described device also includes：

Second receiving module, for receive this operation sent after the smart machine each run startup time and/or Dwell time.

14. device according to claim 13, it is characterised in that described device also includes：

Preserving module, for the startup time of this operation and/or dwell time to be gone through corresponding to the smart machine Preserved in the set of history start-stop time.

15. a kind of device for controlling smart machine start and stop, described device are applied to smart machine, it is characterised in that including：

Processor；

For storing the memory of processor-executable instruction；

Wherein, the processor is configured as：

Receive startup time and/or the dwell time of smart machine operation next time for the prediction that control terminal returns；

The startup time of smart machine operation next time of the prediction is by the control terminal according to time decay weighting algorithm Obtained using the startup time prediction of n times of the time point foregoing description smart machine of prediction；Decayed according to the time and weighted Algorithm utilizes smart machine operation next time described in the startup time prediction of n times of the time point foregoing description smart machine of prediction Start the time formula be：

<mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；Start (t-1) is the startup time of 1 time nearest operation of the time point foregoing description smart machine of prediction, Start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t-3) For the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) be prediction when Between put foregoing description smart machine it is nearest n-th operation the startup time；

And/or

The dwell time of smart machine operation next time of the prediction is by the control terminal according to time decay weighting algorithm Predict to obtain using the dwell time of n times of the time point foregoing description smart machine of prediction；Decayed according to the time and weighted Algorithm predicts operation smart machine next time using the dwell time of n times of the time point foregoing description smart machine of prediction The formula of dwell time is：

<mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a<1；end (t-1) be the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, end (t-2) be prediction when Between put the dwell time of the 2nd time nearest operation of foregoing description smart machine, end (t-3) is the time point foregoing description of prediction The dwell time of the 3rd time nearest operation of smart machine, end (t-n) are that the time point foregoing description smart machine of prediction is nearest N-th operation dwell time；

Run according to smart machine startup optimization described in the startup time control of operation next time, and/or according to the next time Dwell time control the smart machine out of service.

16. a kind of device for controlling smart machine start and stop, described device are applied to control terminal, it is characterised in that including：

Processor；

For storing the memory of processor-executable instruction；

Wherein, the processor is configured as：

The startup time prediction institute of n times according to time decay weighting algorithm using the time point foregoing description smart machine of prediction State the startup time of smart machine operation next time；The time point foregoing description according to time decay weighting algorithm using prediction The startup of n times of smart machine formula of startup time of smart machine operation next time described in time prediction is：

<mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>s</mi> <mi>t</mi> <mi>a</mi> <mi>r</mi> <mi>t</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, start (t) is the startup time of smart machine operation next time of prediction；A is decay factor, a value model Enclose for：0<a<1；Start (t-1) is the startup time of 1 time nearest operation of the time point foregoing description smart machine of prediction, Start (t-2) is the startup time of the 2nd time nearest operation of the time point foregoing description smart machine of prediction, start (t-3) For the startup time of the 3rd time nearest operation of the time point foregoing description smart machine of prediction, start (t-n) be prediction when Between put foregoing description smart machine it is nearest n-th operation the startup time；

And/or

Institute is predicted using the dwell time of n times of the time point foregoing description smart machine of prediction according to time decay weighting algorithm State the dwell time of smart machine operation next time；The time point foregoing description according to time decay weighting algorithm using prediction The dwell time of n times of smart machine predicts that the formula of the dwell time of operation smart machine next time is：

<mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>a</mi> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mi>e</mi> <mi>n</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>-</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>+</mo> <mi>a</mi> <mo>+</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msup> <mi>a</mi> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfrac> </mrow>

Wherein, end (t) is the dwell time of operation next time of prediction；A is decay factor, and a span is：0<a<1；end (t-1) be the dwell time of 1 time nearest operation of the time point foregoing description smart machine of prediction, end (t-2) be prediction when Between put the dwell time of the 2nd time nearest operation of foregoing description smart machine, end (t-3) is the time point foregoing description of prediction The dwell time of the 3rd time nearest operation of smart machine, end (t-n) are that the time point foregoing description smart machine of prediction is nearest N-th operation dwell time；

The startup time of operation next time and/or dwell time are sent to the smart machine.