CN108537466A - A kind of method and computing device of statistics application operation indicator - Google Patents
A kind of method and computing device of statistics application operation indicator Download PDFInfo
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Abstract
The invention discloses a kind of methods of statistics application operation indicator, are executed in computing device, this method includes：Acquire the first time sequence of the target operation indicator of intended application；It obtains by the first reference time array and the second reference time array of the target operation indicator of the collected intended application of third party；The fluctuation situation and overall trend that first time sequence is adjusted according to the first reference time array, obtain the second time series；The operation indicator value that each data point in the second time series is adjusted according to the second reference time array, obtains third time series；Using third time series as the actual time sequence of the target operation indicator of intended application.The present invention discloses corresponding computing device together.Technical scheme of the present invention can adjust the our collected operation indicator data of institute according to third-party application operation indicator data and obtain the actual time sequence that can be used in reacting the target operation indicator of intended application to eliminate the systematic error of we.
Description
Technical field
The present invention relates to the methods and calculating of mobile internet technical field more particularly to a kind of statistics application operation indicator
Equipment.
Background technology
With the development of development of Mobile Internet technology, the mobile terminal devices such as smart mobile phone, tablet computer become increasingly popular, various
Mobile application (APP) emerges one after another, and forms a very active application market, and the application type in same field is various and competing
Strive fierceness.In actual analysis work, for various purposes (such as using ranking, advertisement dispensing etc.), it is to be understood that
Traffic-operating period of certain applications, such as the active amount of application, overlay capacity etc..Internal truthful data is obtained from the operator of application
Difficulty is self-evident, and its credibility can be under suspicion.Therefore, it is common practice to, it is public by third party's data
It takes charge of to obtain the operation data of application.
Third party's data company provides SDK (Software Development Kit, software development work to application developer
Tool packet), the control during developer is applied to based on the SDK bury a little, you can obtains service condition of the user to the application.
This method can realize the automation collection of data, and convenient for the analysis and measurement of data.But each third party department of statistic
There is respective systematic error in system so that its operation indicator come out is inaccurate, and can not correctly describe the increasing of application
Long and fluctuation situation, thus, this statistical data is difficult to portray the true operation situation of application.
Invention content
For this purpose, the present invention provides a kind of method and computing device of statistics application operation indicator, to solve or at least alleviate
The problem of existing above.
According to an aspect of the present invention, a kind of method of statistics application operation indicator is provided, is executed in computing device,
This method includes：Acquire the first time sequence of the target operation indicator of intended application；It obtains by the collected target of third party
The first reference time array and the second reference time array of the target operation indicator of application, wherein each time series packet
Include multiple data points, each data point corresponds to the operation indicator value in unit timing statistics, first time sequence and
The quantity of data point included by first reference time array is identical, when the first unit timing statistics and the first reference units count
Between it is equal, the second reference units timing statistics are more than the first reference units timing statistics and for the first reference units timing statistics
Integral multiple, when the first unit timing statistics, the first reference units timing statistics, the second reference units timing statistics are respectively first
Between sequence, the first reference time array, the second reference time array unit timing statistics；According to the first reference time array come
The fluctuation situation and overall trend for adjusting first time sequence, obtain the second time series；According to the second reference time array come
The operation indicator value for adjusting each data point in the second time series, obtains third time series；Using third time series as mesh
Mark the actual time sequence of the target operation indicator of application.
Optionally, in the method for statistics application operation indicator according to the present invention, according to the first reference time array
Further include step before the step of fluctuation situation and overall trend to adjust first time sequence：Respectively to first time sequence
Row and the first reference time array are smoothed.
Optionally, in the method for statistics application operation indicator according to the present invention, according to the first reference time array come
The fluctuation situation and overall trend of first time sequence are adjusted, the step of obtaining the second time series includes：First object is set
Function and the first intermediate vector, the length of the first intermediate vector are less than the quantity of the data point included by first time sequence；Root
Intermediate sequence is determined according to the first intermediate vector and first time sequence, the quantity of included data point and the in intermediate sequence
One time series is identical；First object function is determined according to first time sequence, the first reference time array and intermediate sequence
Value, the first intermediate vector is adjusted according to the value of first object function；According to first time sequence and first object function
Intermediate sequence corresponding to optimal value determines the second time series.
Optionally, in the method for statistics application operation indicator according to the present invention, according to the first intermediate vector and first
Time series the step of determining intermediate sequence includes：Polynomial function f (x)=c is set0+c1*x+c2*x^2+c3*x^3+…+
cm-1* x^ (m-1), wherein c0~cm-1For coefficient, m is the length of the first intermediate vector, and the first intermediate vector is denoted as Y=[y1,
y2,…,ym]；Without m integer is randomly selected with putting back in the range of from 1 to n, n is data included in first time sequence
The quantity of point obtains sampling vector X=[x by m integer of taking-up according to being ranked sequentially from small to large1,x2,…,xm]；It will
(xi,yi) as sample point the polynomial function is substituted into respectively, to determine coefficient c0~cm-1Value so that it is determined that multinomial letter
Number, wherein 1≤i≤m；The functional value f in first time sequence corresponding to each data point is determined according to polynomial function
(xj), wherein xjFor position number of the data point in first time sequence, 1≤xj≤ n and xjWith x1~xmValue not phase
Together；The value of f (1)~f (n) is constituted into intermediate sequence.
Optionally, in the method for statistics application operation indicator according to the present invention, first object function is：
Or
Wherein, min indicates that optimization aim is to make first object function obj1Minimum, k are counting variable, and n is at the first time
The quantity of included data point in sequence, r indicates first time sequence and intermediate sequence and sequence, r (k), r (k+1) points
Not Biao Shi and sequence r in k-th, the value of+1 element of kth, s indicates the first reference time array, s (k), s (k+1) table respectively
Show in the first reference time array s k-th, the value of+1 element of kth；Max indicates that optimization aim is to make first object function
obj1Maximum, λ0、λ1For preset coefficient, a00Indicate that element value is 0 in the first volatility series br and the second volatility series bs
The quantity of position, a01Indicate that element value is 0 in the first volatility series br, the position that element value is 1 in the second volatility series bs
Quantity, a10Indicate that element value is 1 in the first volatility series br, the quantity for the position that element value is 0 in the second volatility series bs,
a11Indicate that element value in the first volatility series br and the second volatility series bs is the quantity of 1 position, the first volatility series br,
Second volatility series bs is determined according to following formula：
Wherein, br (k) indicates that the value of k-th of element in the first volatility series br, bs (k) indicate in the second volatility series bs
The value of k-th of element, sign () are sign function.
Optionally, in the method for statistics application operation indicator according to the present invention, according to first time sequence, first
Further include step before the value of reference time array and intermediate sequence to determine first object function：To first time sequence,
One reference time array and intermediate sequence carry out the sampling of same position element.
Optionally, in the method for statistics application operation indicator according to the present invention, according to first time sequence and first
Intermediate sequence corresponding to the optimal value of object function includes the step of determining the second time series：By first time sequence and
Intermediate sequence corresponding to the optimal value of first object function and as the second time series.
Optionally, in the method for statistics application operation indicator according to the present invention, according to the second reference time array come
The operation indicator value for adjusting each data point in the second time series, the step of obtaining third time series include：By the second time
Sequence is divided into multiple subsequences, and the length of each subsequence is equal to the second reference units timing statistics and the first reference units
The ratio of timing statistics, each subsequence correspond to a data point in the second reference time array；Among setting second
Vector, third intermediate vector, the second object function and third object function, second intermediate vector, third intermediate vector
Length is the ratio of the second reference units timing statistics and the first reference units timing statistics；According to multiple subsequences,
Two intermediate vectors, third intermediate vector, the second reference time array determine the value of the second object function and third object function,
The second intermediate vector, third intermediate vector are adjusted according to the value of the second object function and third object function；When according to second
Between sequence and the second object function, third object function optimal value corresponding to third intermediate vector determine third time sequence
Row.
Optionally, in the method for statistics application operation indicator according to the present invention, the second object function is：
Third object function is：
Wherein, min indicates that optimization aim is to make the second object function obj2, third object function obj3Minimum, i, j are meter
Number variable, q are the quantity for participating in calculating the subsequence of the second object function, third object function, and p counts for the second reference units
The ratio of time and the first reference units timing statistics, point (i) indicate the second reference time array corresponding to subsequence i
In data point value, tempv2、tempv3、ts2The second intermediate vector, third intermediate vector, the second time sequence are indicated respectively
Row, tempv2(j)、tempv3(j)、ts2(j) the second intermediate vector tempv is indicated respectively2, third intermediate vector tempv3, second
Time series ts2In j-th of element value, α, β be preset constant, var (tempv2) indicate the second intermediate vector tempv2In
The variance of each element value.
Optionally, in the method for statistics application operation indicator according to the present invention, among multiple subsequences, second
The step of value to determine the second object function and third object function of vector, third intermediate vector, the second reference time array
Including：Between element value in all subsequences of second time series is standardized as 0~1, subsequence two-by-two is determined respectively
Between similitude；Similar sub-sequence set, the similar sub-sequence collection are determined according to the similitude between subsequence two-by-two
Three subsequences are included at least in conjunction；According to multiple subsequences in the similar sub-sequence set, the second intermediate vector, third
Intermediate vector, the second reference time array determine the value of the second object function and third object function.
Optionally, in the method for statistics application operation indicator according to the present invention, the similitude between subsequence two-by-two
It is determined using Wilcoxen signed rank test method.
Optionally, in the method for statistics application operation indicator according to the present invention, according to the second time series and second
Object function, third object function optimal value corresponding to third intermediate vector wrapped the step of third time series to determine
It includes：Respectively by each subsequence of the second time series and the second object function, third object function optimal value corresponding to
Third intermediate vector corresponding position element value be multiplied, obtain third time series.
Optionally, in the method for statistics application operation indicator according to the present invention, the first reference units timing statistics are
One day, the second reference units timing statistics were one week.
According to another aspect of the present invention, a kind of computing device is provided, including：At least one processor；Be stored with
The memory of program instruction, wherein program instruction is configured as being suitable for being executed by above-mentioned at least one processor, program instruction packet
Include the instruction of the method for executing statistics application operation indicator as described above.
According to a further aspect of the invention, a kind of readable storage medium storing program for executing for the instruction that has program stored therein is provided, when above-mentioned journey
When sequence instruction is read and is executed by computing device so that the computing device executes the side of statistics application operation indicator as described above
Method.
According to the technique and scheme of the present invention, first time sequence is time series to be adjusted, by our data company
Acquisition；First reference time array and the second reference time array are acquired by another third party's data company.According to the first ginseng
Time series and the second reference time array are examined to be adjusted to first time sequence, the target operation for obtaining intended application refers to
Target actual time sequence.Technical scheme of the present invention can be adjusted according to the collected application operation indicator data of third party institute
The our collected operation indicator data of institute obtain can be used in reacting intended application to eliminate the systematic error of we
The actual time sequence of target operation indicator.
Above description is only the general introduction of technical solution of the present invention, in order to better understand the technical means of the present invention,
And can be implemented in accordance with the contents of the specification, and in order to allow above and other objects of the present invention, feature and advantage can
It is clearer and more comprehensible, below the special specific implementation mode for lifting the present invention.
Description of the drawings
To the accomplishment of the foregoing and related purposes, certain illustrative sides are described herein in conjunction with following description and drawings
Face, these aspects indicate the various modes that can put into practice principles disclosed herein, and all aspects and its equivalent aspect
It is intended to fall in the range of theme claimed.Read following detailed description in conjunction with the accompanying drawings, the disclosure it is above-mentioned
And other purposes, feature and advantage will be apparent.Throughout the disclosure, identical reference numeral generally refers to identical
Component or element.
Fig. 1 shows the schematic diagram of the system 100 of statistics application operation indicator according to an embodiment of the invention；
Fig. 2 shows the schematic diagrames of computing device 200 according to an embodiment of the invention；
Fig. 3 shows the flow chart of the method 300 of statistics application operation indicator according to an embodiment of the invention；
Fig. 4 shows the schematic diagram of first time sequence according to an embodiment of the invention；
Fig. 5 shows first time sequence according to an embodiment of the invention and is adjusted to first time sequence
The schematic diagram of whole obtained second time series；
Fig. 6 shows according to an embodiment of the invention according to the second time series ts2With among optimal third to
Measure tempv3Best determines third time series ts3Schematic diagram.
Specific implementation mode
The exemplary embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing the disclosure in attached drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure
Completely it is communicated to those skilled in the art.
Fig. 1 shows the schematic diagram of the system 100 of statistics application operation indicator according to an embodiment of the invention.Such as figure
Shown in 1, system 100 includes computing device 200, data storage device 120 and mobile terminal 130.
Computing device 200 be have communication, calculating, store function equipment, can be implemented as server, such as monitor
Server, application server, Web server etc., but not limited to this.It should be pointed out that computing device 200 can be implemented as a clothes
It is engaged in device, the cluster being made of multiple servers or distributed system can also be embodied as；When it is multiple servers, this is more
Platform server can be deployed in same geographical location, can also dispersed placement in multiple geographical locations, the present invention is to computing device
The quantity of server included by 200 and the deployed position of each server are not limited.
Data storage device 120 can be relevant database such as MySQL, ACCESS, can also be non-relational
Database is such as NoSQL；It can be the local data base resided in computing device 200, can also be used as distributed data
Library is set to multiple geographical locations such as HBase, in short, data storage device 120 is for storing data, logarithm of the present invention
It is not limited according to the specific deployment of storage device 120, configuring condition.Computing device 200 can connect with data storage device 120
It connects, and obtains the data stored in data storage device 120.For example, computing device 200 can directly read data storage dress
Set the data (when data storage device 120 is the local data base of computing device 200) in 120, can also by wired or
Internet is wirelessly accessed, and the data in data storage device 120 are obtained by data-interface.
Mobile terminal 130 is but unlimited such as can be mobile phone, tablet computer, multimedia equipment, intelligent wearable device
In this.
In the present invention, computing device 200 is third party's data service company C1 (hereinafter referred to as " we ") institute
The monitoring server of deployment.We can provide the SDK for obtaining user to the usage behavior of application for application developer.It moves
One or more application (APP) is installed in dynamic terminal 130, the SDK that we are provided may be integrated in certain applications.For
It is integrated with the application of SDK, when user uses this in application, the SDK can be by user to the behavior number of application on mobile terminal 130
According to computing device 200 is reported to, computing device 200 obtains the data, writes data into data storage device 120 immediately and deposited
Storage.Further, computing device 200 can be directed to the behavior of a certain application based on the user that data storage device 120 is stored
Data summarize the operation indicator data for obtaining the application, such as day/week/month is actively measured, day/week/month overlay capacity etc., and will
The operation indicator data deposit data storage device 120 gone out is in case he uses.Computing device 200 can also be to other third party's data
Service company C2, C3 ..., the request operation indicator data such as the server of Cn (hereinafter referred to as " third party "), and return it into
Operation indicator data be stored in data storage device 120.
It should be pointed out that we and third party collected operation indicator data there is certain systematic error, respectively
The operation indicator data that corporate statistics come out are inaccurate, and can not correctly describe growth and the fluctuation situation of application, thus, it is each
The statistical data of company is difficult to portray the true operation situation of application.For the problem, in the present invention, computing device
200 can execute the method 300 of statistics application operation indicator, be adjusted according to the collected application operation indicator data of third party institute
The collected operation indicator data of whole we institute obtain can be used in reacting intended application to eliminate the systematic error of we
Target operation indicator actual time sequence.For example, according to the collected operation indicator data of third company C2 come to this
The collected operation indicator data in side are adjusted, obtain one more can reactive applications true traffic-operating period operation indicator number
According to.
Although should be pointed out that in the above description, computing device 200 can be used for obtaining user behavior data, to user
Behavioral data is carried out summarizing the operation indicator data being applied, be adjusted according to the operation indicator data of other third company
The operation indicator data of we are to obtain true operation indicator data, it will be understood by those skilled in the art, however, that above-mentioned three
A procedure can realize by the same computing device (such as above-mentioned computing device 200), can also be by different calculating
Equipment realizes that the present invention disposes the particular hardware for being related to above three procedure and is not limited.
Fig. 2 shows the configuration schematic diagrams of computing device 200 according to an embodiment of the invention.In basic configuration
In 202, computing device 200 typically comprises system storage 206 and one or more processor 204.Memory bus 208
It can be used for the communication between processor 204 and system storage 206.
Depending on desired configuration, processor 204 can be any kind of processing, including but not limited to：Microprocessor
(μ P), microcontroller (μ C), digital information processor (DSP) or any combination of them.Processor 204 may include such as
The cache of one or more rank of on-chip cache 210 and second level cache 212 etc, processor core
214 and register 216.Exemplary processor core 214 may include arithmetic and logical unit (ALU), floating-point unit (FPU),
Digital signal processing core (DSP core) or any combination of them.Exemplary Memory Controller 218 can be with processor
204 are used together, or in some implementations, and Memory Controller 218 can be an interior section of processor 204.
Depending on desired configuration, system storage 206 can be any type of memory, including but not limited to：Easily
The property lost memory (RAM), nonvolatile memory (ROM, flash memory etc.) or any combination of them.System stores
Device 106 may include operating system 220, one or more apply 222 and program data 224.It is actually more using 222
Bar program instruction, is used to indicate processor 204 and executes corresponding operation.In some embodiments, it can be arranged using 222
For on an operating system so that processor 204 is operated using program data 224.
Computing device 200 can also include contributing to from various interface equipments (for example, output equipment 242, Peripheral Interface
244 and communication equipment 246) to basic configuration 202 via the communication of bus/interface controller 230 interface bus 240.Example
Output equipment 242 include graphics processing unit 248 and audio treatment unit 250.They can be configured as contribute to via
One or more port A/V 252 is communicated with the various external equipments of such as display or loud speaker etc.Outside example
If interface 244 may include serial interface controller 254 and parallel interface controller 256, they, which can be configured as, contributes to
Via one or more port I/O 258 and such as input equipment (for example, keyboard, mouse, pen, voice-input device, touch
Input equipment) or the external equipment of other peripheral hardwares (such as printer, scanner etc.) etc communicated.Exemplary communication is set
Standby 246 may include network controller 260, can be arranged to convenient for via one or more communication port 264 and one
The communication that other a or multiple computing devices 262 pass through network communication link.
Network communication link can be an example of communication media.Communication media can be usually presented as in such as carrier wave
Or the computer-readable instruction in the modulated data signal of other transmission mechanisms etc, data structure, program module, and can
To include any information delivery media." modulated data signal " can such signal, one in its data set or more
It is a or it change can the mode of coding information in the signal carry out.As unrestricted example, communication media can be with
Include the wire medium of such as cable network or private line network etc, and such as sound, radio frequency (RF), microwave, infrared
(IR) the various wireless mediums or including other wireless mediums.Term computer-readable medium used herein may include depositing
Both storage media and communication media.
In computing device 200 according to the present invention, the application 228 for including statistics application operation indicator using 222, statistics
Include a plurality of program instruction using the application 228 of operation indicator, and program data 224 may include by data storage device 120
In the we that get collected application the collected operation indicator data of operation indicator data and third party institute.It answers
It can indicate that processor 204 executes the method 300 of statistics application operation indicator with 228, according to the collected operation of third party institute
Achievement data adjusts the our collected operation indicator data of institute, with the true traffic-operating period being applied.
Fig. 3 shows the flow chart of the method 300 of statistics application operation indicator according to an embodiment of the invention.Method
300 are suitable for executing in computing device (such as aforementioned computing device 200).As shown in figure 3, method 300 starts from step S310.
In step S310, the first time sequence ts of the target operation indicator of intended application is acquired1；It obtains by third party
First reference time array ref of the target operation indicator of collected intended application1With the second reference time array ref2.It answers
When pointing out, intended application indicates application to be analyzed, can be arbitrary application, rather than refer in particular to some application；Likewise,
The operation indicator that target operation indicator is used to indicate a desire to obtain can be the arbitrary indexs such as active amount, overlay capacity, and not
Refer in particular to some operation indicator.Such as, if it is desired to the active amount using A is obtained, then it is intended application to apply A, and active amount is
For target operation indicator.First time sequence ts1It is acquired for we, the first reference time array ref1With the second reference time sequence
Arrange ref2It is acquired for third party.
First time sequence, the first reference time array, three times of the second reference time array involved in step S310
Sequence.Time series is the sequence for arranging operation indicator value according to chronological order and being formed, each time series packet
Multiple data points are included, each data point corresponds to the operation indicator value in a unit timing statistics.
In the present invention, first time sequence is identical with the quantity of the data point included by the first reference time array,
That is, first time sequence is identical with the length of the first reference time array.The unit timing statistics of time series can be by ability
Field technique personnel are voluntarily arranged, for example, unit timing statistics can be set to day, week, moon etc., but not limited to this.When one
When the unit timing statistics of time series are day, correspondingly, each data point of the time series indicates the operation of some day
Index value, for example, actively measuring day, day overlay capacity etc..In order to describe conveniently, when the present invention is by first time sequence, the first reference
Between sequence, three time serieses of the second reference time array unit timing statistics be denoted as the first unit timing statistics, respectively
One reference units timing statistics, the second reference units timing statistics.In the present invention, the first unit timing statistics and the first reference
Unit timing statistics are equal, and the second reference units timing statistics are more than the first reference units timing statistics and are the first reference units
The integral multiple of timing statistics.For example, the first unit timing statistics and the first reference units timing statistics are one day, the second reference
Unit timing statistics are one week.
The following table shows a first time sequence ts1Example (intended application is good app, and target operation indicator is
Active amount)：
As seen from the above table, the unit timing statistics of the first time sequence are one day.Every a line in upper table indicates first
A data point in time series, which includes 8 data points altogether, that is, the length of first time sequence is 8.Upper table
Shown in first time sequence can also indicate that in Fig. 4, the horizontal axis of reference axis is time, the longitudinal axis with curve as shown in Figure 4
For operation indicator value, point A~H on curve is each data point in first time sequence.
Then, in step s 320, according to the first reference time array ref1To adjust first time sequence ts1Fluctuation
Situation and overall trend obtain the second time series ts2。
Further include that (step S312 does not show step S312 in figure 3 before executing step S320 according to a kind of embodiment
Go out).In step S312, respectively to first time sequence ts1With the first reference time array ref1It is smoothed, to
Eliminate apparent abnormal noise spot.It should be pointed out that those skilled in the art can design arbitrary smoothing algorithm when coming to first
Between sequence and the first reference time array be smoothed, for example, using simple rolling average, weighted moving average, index
Smooth to wait smoothing algorithms etc., the present invention is not limited smoothing algorithm.
According to a kind of embodiment, step S320 is implemented further according to following steps S322~S328：
In step S322, first object function and the first intermediate vector tempv are set1.Step S320 is equivalent to one
Optimization process, first object function are the optimization aim of the optimization process, the first intermediate vector tempv1For the optimization process
Original state.
First object function target as an optimization is intended to the fluctuation situation for two time serieses r, s for making participation optimize
Tend to be similar with overall trend.First object function can be voluntarily arranged by those skilled in the art, and the present invention does not limit this
System.According to a kind of embodiment, first object function could be provided as following form：
Wherein, min indicates that optimization aim is to make first object function obj1Minimum, k are counting variable, and n is to participate in optimizing
Two time serieses in included data point quantity, r, s indicate two time serieses for participating in optimizing, r (k), r respectively
(k+1) k-th, the value of kth+1 element are indicated in time series r respectively, and s (k), s (k+1) are indicated in time series s respectively
K-th, the value of+1 element of kth.
According to another embodiment, first object function could be provided as following form：
Wherein, max indicates that optimization aim is to make first object function obj1Maximum, λ0、λ1For preset coefficient, λ0、λ1's
Value can be voluntarily arranged by those skilled in the art, and the present invention is not limited its value.a00、a01、a10、a11Value according to
Following methods determine：
First, time series r, s corresponding volatility series br, the bs for participating in optimization are determined respectively according to following formula：
Wherein, br (k) indicates that the value of k-th of element in volatility series br, bs (k) indicate in volatility series bs k-th yuan
The value of element, sign () are sign function.
Then, a is determined according to volatility series br, bs00、a01、a10、a11Value.Wherein, a00Indicate two volatility series
Element value is the quantity of 0 position, a in br, bs01Indicate that element value is 0 in volatility series br, element value in volatility series bs
For the quantity of 1 position, a10Indicate that element value is 1 in volatility series br, the number for the position that element value is 0 in volatility series bs
Amount, a11Element value is the quantity of 1 position in expression volatility series br and volatility series bs.For example, volatility series br=[0,
1,0,0,1,1,0], [1,1,1,0,1,0,1] bs=, two volatility series include 7 elements, correspond to position 1~7.Only
The element value of br, bs are 0 at position 4, i.e. br [4]=bs [4]=0, therefore a00=1；The element value of br is at position 1,3,7
0, bs element value is 1, i.e. br [1]=br [3]=br [7]=0, bs [1]=bs [3]=bs [7]=1, therefore, a01=3；br
[6]=1, bs [6]=0, therefore, a10=1；Br [2]=bs [2]=1, br [5]=bs [5]=1, therefore, a11=2.
First intermediate vector tempv1It is equivalent to the original state of the optimization process of step S320.First intermediate vector
tempv1Length be preferably less than the quantity of the data point included by first time sequence.For example, having in first time sequence
100 data points (i.e. the length of first time sequence is 100), then the length of the first intermediate vector may be configured as less than 100
Arbitrary integer.It should be pointed out that the value of each element can be by art technology in the length of the first intermediate vector and the vector
Personnel are voluntarily arranged, and the specific value of both present invention is not limited.
Then, in step S324, according to the first intermediate vector tempv1With first time sequence ts1To determine intermediate sequence
The quantity and first time sequence ts of included data point in row temps, intermediate sequence temps1It is identical.
Intermediate sequence temps can be determined further according to following steps：First, setting polynomial function f (x)=c0+c1*x
+c2*x^2+c3*x^3+…+cm-1* x^ (m-1), wherein c0~cm-1For coefficient, m is the length of the first intermediate vector, by first
Intermediate vector is denoted as Y=[y1,y2,…,ym].Then, in the range of 1~n without randomly selecting m integer with putting back to, n the
The quantity of included data point in one time series is taken out by m integer of taking-up according to being ranked sequentially from small to large
Sample vector X=[x1,x2,…,xm].Then, by (xi,yi) as sample point above-mentioned polynomial function is substituted into respectively, be to determine
Number c0~cm-1Value so that it is determined that the polynomial function, wherein 1≤i≤m.Then, first is determined according to polynomial function
Functional value f (x in time series corresponding to each data pointj), wherein xjFor position-order of the data point in first time sequence
Number, 1≤xj≤ n and xjWith x1~xmValue be all different.Finally, the value of f (1)~f (n) is constituted into intermediate sequence temps.
For example, first time sequence ts1Length be 100, the first intermediate vector tempv1Length be 10, i.e. n=100,
First intermediate vector is correspondingly denoted as Y=[y by m=101,y2,…,y10], polynomial function is f (x)=c0+c1*x+c2*x
^2+c3*x^3+…+cm-1*x^9.Without 10 integers are randomly selected with putting back in the range of 1~100, for example, extraction result is
[4,9,55,22,8,91,7,36,73,56] obtain sampling vector X by the number of taking-up according to being ranked sequentially from small to large
=[x1,x2,…,x10]=[4,7,8,9,22,36,55,56,73,91].By (x1,y1)~(x10,y10) distinguish as sample point
It brings above-mentioned polynomial function f (x) into, obtains 10 equations, coefficient c can be determined according to this 10 equations0~c9Value to really
Determine the expression formula of polynomial function f (x).Then, each data point in first time sequence is determined according to polynomial function f (x)
Corresponding functional value f (xj), wherein xjFor position number of the data point in first time sequence, 1≤xj≤ 100 and xjWith
x1~x10Value be all different, in this way, each data point in first time sequence both corresponds to a functional value, functional value
F (1)~f (n) may make up intermediate sequence temps.
Then, in step S326, according to first time sequence ts1, the first reference time array ref1And intermediate sequence
Temps determines the value of first object function, adjusts the first intermediate vector tempv according to the value of first object function1。
It is public when according to value to calculate first object function of aforementioned formula (1) or (2)~(4) according to a kind of embodiment
Two time serieses r, s that optimization is participated in formula are respectively first time sequence ts1With intermediate sequence temps's and sequence,
One reference time array ref1, that is, r=ts1+ temps, s=ref1.In this way, according to sequence r and the first reference time array
ref1It can determine the value of first object function.It, can be according to first object letter after the value that first object function is determined
Several values adjusts the first intermediate vector tempv1, the process phase of the first intermediate vector is adjusted according to the value of first object function
When in one-step optimization process.After optimizing by multistep, it can be deduced that the optimal value of first object function and the optimal value institute
Corresponding first intermediate vector tempv1Best and intermediate sequence tempsbest.Specific optimization process may be used such as
Nelder-Mead methods (simplex method of going down the hill) etc., the present invention is not limited specific algorithm used by optimization process.
According to a kind of embodiment, in order to accelerate optimization process, before executing step S326, first to first time sequence
ts1, the first reference time array ref1The sampling that same position element is carried out with intermediate sequence temps calculates the first mesh to reduce
The calculation amount when value of scalar functions.For example, script first time sequence ts1, the first reference time array ref1And intermediate sequence
The length of temps is 100, and three sequences are carried out with the sampling of singular position element, that is, by the 1st in three sequences, the 3rd
It is a ..., the 99th element take out, form the sample sequence that three length halve (i.e. length is 50).With the sequence after sampling come
Calculate the value of first object function.
Then, in step S328, according to first time sequence ts1In corresponding to optimal value with first object function
Between sequence tempsbest determine the second time series ts2.According to a kind of embodiment, by first time sequence and first object
Intermediate sequence corresponding to the optimal value of function and as the second time series, i.e. ts2=ts1+tempsbest。
It should be pointed out that first time sequence ts1With the first reference time array ref1It may be implemented mutually to correct, correction side
Method is identical, only with first time sequence ts in step S3201For to illustrate to correct it fluctuate situation and overall trend
Detailed process.It will be understood by those skilled in the art that the Method And Principle shown in using above mentioned steps S3 20, it can also be according to
One time series ts1To adjust the first reference time array ref1Fluctuation situation and overall trend.Fig. 5 is shown according to this hair
The first time sequence ts of bright one embodiment1And obtained second time series is adjusted to first time sequence
ts2Schematic diagram.Scheme the data and curves that (a) is original, curve 510 indicates first time sequence ts1, first ginseng of the expression of curve 520
Examine time series ref1, by figure (a) as it can be seen that curve 510 significantly decreases trend, but fluctuation is smaller；Curve 520 fluctuates
It is larger, but trend is not risen or fallen significantly.Figure (b) indicates to have corrected fluctuation situation by step S320 and entirety becomes
Curve after gesture, curve 510 ' indicate first time sequence ts1Correction sequence, i.e. the second time series ts2；520 ' table of curve
Show the first reference time array ref1Correction sequence, mutually corrected in fact, curve 510 ', 520 ' is curve 510,520
As a result.By figure (b) as it can be seen that due to curve 520 introducing, curve 510 ' obviously increases compared to 510 fluctuation of curve；In addition,
Due to the introducing of curve 510, curve 520 ' has apparent downward trend compared to curve 520.That is, it is based on step S320,
First time sequence ts can be adjusted1Fluctuation situation and overall trend, obtain the second time series ts2。
It should be pointed out that step S320 is only to first time sequence ts1Fluctuation situation and overall trend be adjusted, and do not have
There is the concrete numerical value for adjusting each data point.Therefore the second time series ts2Fluctuation situation and overall trend already close to true
Value, however it is still necessary to the second time series ts2In the specific operation indicator value of each data point be adjusted.Operation indicator value
Adjustment as steps described below S330 carry out.
In step S330, according to the second reference time array ref2To adjust the second time series ts2In each data point
Operation indicator value obtains third time series ts3.Since the unit timing statistics of the second reference time array are larger, data
Point is less, serious forgiveness higher, therefore, the second reference time array ref2In operation indicator value compared to first time sequence
ts1, the second time series ts2, the first reference time array ref1For it is more accurate and reliable.Therefore according to second in step S330
Reference time array ref2To adjust the second time series ts2In each data point operation indicator value.
According to a kind of embodiment, step S330 is implemented further according to following steps S332~S338：
In step S332, by the second time series ts2Multiple subsequences are divided into, the length of each subsequence is equal to
The ratio of second reference units timing statistics and the first reference units timing statistics, when each subsequence corresponds to the second reference
Between a data point in sequence.If for example, the first reference time array be actively measure sequence day, the second reference time array is
Week actively measures sequence, then the first reference units timing statistics are one day, the second reference units timing statistics are one week, correspondingly,
The length of each subsequence of the second time series is 1 week/1 day=7.For example, April 29 23 days~2018 April in 2018
Day actively measure day and constitutes a subsequence, actively measured this in week corresponding to the 17th week 2018 in the second reference time array
One data point.
Then, in step S334, the second intermediate vector tempv is set2, third intermediate vector tempv3, the second target letter
Number and third object function, the second intermediate vector, the length of third intermediate vector are the second reference units timing statistics and first
The ratio of reference units timing statistics.That is, the second intermediate vector tempv2, third intermediate vector tempv3With the second time series
ts2Each subsequence length it is identical.For example, the first reference units timing statistics are one day, the second reference units count
Time is one week, then each subsequence, the second intermediate vector, the length of third intermediate vector are 7.
Step S330 is equivalent to an optimization process, the second intermediate vector tempv2, third intermediate vector tempv3It is equivalent to
The original state of the optimization process, the second object function obj2, third object function obj3For the optimization aim of the optimization process.
According to a kind of embodiment, the second object function obj2, third object function obj3It is as follows：
Wherein, wherein min indicates that optimization aim is to make the second object function obj2, third object function obj3Minimum, i, j
For counting variable, q is the quantity for participating in calculating the subsequence of the second object function, third object function, and p is the second reference units
The ratio of timing statistics and the first reference units timing statistics, point (i) indicate the second reference time corresponding to subsequence i
The value of data point in sequence, tempv2、tempv3、ts2The second intermediate vector, third intermediate vector, the second time are indicated respectively
Sequence, tempv2(j)、tempv3(j)、ts2(j) the second intermediate vector tempv is indicated respectively2, third intermediate vector tempv3,
Two time series ts2In j-th of element value, α, β be preset constant, var (tempv2) indicate the second intermediate vector tempv2
The variance of middle each element value.It should be pointed out that the value of α, β can be voluntarily arranged by those skilled in the art, the present invention does not do this
Limitation.
Then, in step S336, according to multiple subsequences, the second intermediate vector tempv2, third intermediate vector
tempv3, the second reference time array ref2The value of the second object function and third object function is determined, according to the second target letter
It counts and adjusts the second intermediate vector, third intermediate vector with the value of third object function.
It should be pointed out that the subsequence for participating in step S336 can be the second time series ts2All subsequences, can also
It is a part of subsequence therein.Due to unit statistics section it is shorter, in the second time series each subsequence trend be distributed with
And in subsequence each element value weight distribution it is uneven, the calculating of step S336 can be affected greatly.It is therefore preferable that
The second time series ts is selected on ground2In more similar subsequence carry out the calculating of step S336, that is, step S336 according to
Following steps execute：
First, between the element value in all subsequences of the second time series being standardized as 0~1, two are determined respectively
Similitude between two subsequences.Standardized method can be voluntarily arranged by those skilled in the art, and the present invention does not limit this
System.For example, standardization can be realized with the ratio of the sum of element value in a certain element value and subsequence, for subsequence [2,
6,3,7,4,8,6], standardization result is [2,6,3,7,4,8,6]/36=[1/18,1/6,1/12,7/36,1/9,2/9,1/
6].In addition, the computational methods of similitude can also be voluntarily arranged by those skilled in the art, the present invention is without limitation.Example
Such as, Wilcoxen (Wilcoxon) signed rank test method may be used to determine the similitude between two subsequences.Then, root
Similar sub-sequence set is determined according to the similitude between subsequence two-by-two, and three sub- sequences are included at least in similar sub-sequence set
Row.For example, the calculating by similitude, subsequence A is similar to subsequence B, and subsequence B is similar to subsequence C, then subsequence A,
B, C constitutes similar sub-sequence set.Finally, according to multiple subsequences in similar sub-sequence set, the second intermediate vector
tempv2, third intermediate vector tempv3, the second reference time array ref2To determine the second object function and third object function
Value, the second intermediate vector, third intermediate vector are adjusted according to the value of the second object function and third object function.Specifically
Ground can first fix the second intermediate vector tempv2It is constant, the value of the second object function is calculated according to formula (5), according to
The value of two object functions constantly adjusts third intermediate vector tempv3, optimal under current second intermediate vector until finding out
Third intermediate vector tempv3best；Then, fixed third intermediate vector is tempv3Best calculates according to formula (6)
The value of three object functions constantly adjusts the second intermediate vector tempv according to the value of third object function2, working as until finding out
The second optimal intermediate vector tempv under preceding third intermediate vector2best；Then, fixing the second intermediate vector again is
tempv2Best calculates the value of the second object function according to formula (5), and the is constantly adjusted according to the value of the second object function
Three intermediate vector tempv3..., and so on, after repeatedly optimizing, it can obtain the second object function, third object function
The second intermediate vector tempv corresponding to optimal value and the optimal value2Best, third intermediate vector tempv3best.Specifically
Nelder-Mead methods (simplex method of going down the hill) etc. may be used in optimization process, and the present invention is to used by optimization process
Specific algorithm is not limited.
Then, in step S338, according to the second time series ts2Most with the second object function, third object function
Third intermediate vector tempv corresponding to the figure of merit3Best determines third time series ts3.According to a kind of embodiment, respectively will
Second time series ts2Each subsequence and the second object function, third object function optimal value corresponding to third
Intermediate vector tempv3The element value of the corresponding position of best is multiplied, and obtains third time series ts3.For example, as shown in fig. 6,
Two time serieses are ts2=[1,5,8,2,3,1,6,5,9,7,4,2,2,5,1], the second time series ts2In every seven elements
Constitute a subsequence.Optimal third intermediate vector is tempv3Best=[0.2,0.9,1.5,2,0.5,0.4,1.2].It is first
First, by the second time series ts2First subsequence [1,5,8,2,3,1,6] and third intermediate vector tempv3Pair of best
It answers the element value of position to be multiplied, the element value of first subsequence is adjusted to [0.2,4.5,12,4,1.5,0.4,7.2], it should
Subsequence after adjustment is third time series ts3First subsequence；Then, by ts2Second subsequence [5,9,
7,4,2,2,5] with third intermediate vector tempv3The element value of the corresponding position of best is multiplied, and adjusts the member of second subsequence
Element value, and so on, until the second time series ts2In each element value by third intermediate vector tempv3Best institutes
Until adjustment, the subsequence after all adjustment, which merges, constitutes third time series ts3, ts3=[0.2,4.5,12,4,
1.5,0.4,7.2,1,8.1,10.5,8,1,6,0.2].In other words, third intermediate vector tempv3Best is equivalent to a volume
Product core, with 7 for step-length along the second time series ts2It is mobile, convolution is carried out to each subsequence in the second time series, most
Third time series ts is obtained eventually3。
Then, in step S340, by third time series ts3Target operation indicator as intended application it is true when
Between sequence.
A9：Method described in A8, wherein second object function is：
The third object function is：
Wherein, min indicates that optimization aim is to make the second object function obj2, third object function obj3Minimum, i, j are meter
Number variable, q are the quantity for participating in calculating the subsequence of the second object function, third object function, and p counts for the second reference units
The ratio of time and the first reference units timing statistics, point (i) indicate the second reference time array corresponding to subsequence i
In data point value, tempv2、tempv3、ts2The second intermediate vector, third intermediate vector, the second time sequence are indicated respectively
Row, tempv2(j)、tempv3(j)、ts2(j) the second intermediate vector tempv is indicated respectively2, third intermediate vector tempv3, second
Time series ts2In j-th of element value, α, β be preset constant, var (tempv2) indicate the second intermediate vector tempv2In
The variance of each element value.
A10：Method described in A8 or 9, wherein according to multiple subsequences, the second intermediate vector, third intermediate vector,
The step of value of two reference time arrays to determine the second object function and third object function includes：
Between element value in all subsequences of second time series is standardized as 0~1, sequence sub- two-by-two is determined respectively
Similitude between row；
Similar sub-sequence set is determined according to the similitude between subsequence two-by-two, in the similar sub-sequence set extremely
Include three subsequences less；
According to multiple subsequences in the similar sub-sequence set, the second intermediate vector, third intermediate vector, the second ginseng
Time series is examined to determine the value of the second object function and third object function.
A11：Method described in A10, wherein the similitude between subsequence uses Wilcoxen signed rank test two-by-two
Method determines.
A12：Method described in any one of A8-11, wherein according to the second time series and the second object function, third
Third intermediate vector corresponding to the optimal value of object function includes the step of third time series to determine：
Respectively by the optimal value institute of each subsequence of the second time series and the second object function, third object function
The element value of the corresponding position of corresponding third intermediate vector is multiplied, and obtains third time series.
A13：Method described in any one of A1-12, wherein the first reference units timing statistics are one day, described
Second reference units timing statistics are one week.
Various technologies described herein are realized together in combination with hardware or software or combination thereof.To the present invention
Method and apparatus or the process and apparatus of the present invention some aspects or part can take embedded tangible media, such as can
Program code (instructing) in mobile hard disk, USB flash disk, floppy disk, CD-ROM or other arbitrary machine readable storage mediums
Form, wherein when program is loaded into the machine of such as computer etc, and when being executed by the machine, the machine becomes to put into practice
The equipment of the present invention.
In the case where program code executes on programmable computers, computing device generally comprises processor, processor
Readable storage medium (including volatile and non-volatile memory and or memory element), at least one input unit, and extremely
A few output device.Wherein, memory is configured for storage program code；Processor is configured for according to the memory
Instruction in the said program code of middle storage, the method for executing the statistics application operation indicator of the present invention.
By way of example and not limitation, readable medium includes readable storage medium storing program for executing and communication media.Readable storage medium storing program for executing
Store the information such as computer-readable instruction, data structure, program module or other data.Communication media is generally such as to carry
The modulated message signals such as wave or other transmission mechanisms embody computer-readable instruction, data structure, program module or other
Data, and include any information transmitting medium.Above any combination is also included within the scope of readable medium.
In the instructions provided here, algorithm and display not with any certain computer, virtual system or other
Equipment is inherently related.Various general-purpose systems can also be used together with the example of the present invention.As described above, it constructs this kind of
Structure required by system is obvious.In addition, the present invention is not also directed to any certain programmed language.It should be understood that can
With using various programming languages realize invention described herein content, and the description that language-specific is done above be for
Disclose the preferred forms of the present invention.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the present invention
Example can be put into practice without these specific details.In some instances, well known method, knot is not been shown in detail
Structure and technology, so as not to obscure the understanding of this description.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of each inventive aspect,
Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：It is i.e. required to protect
Shield the present invention claims the feature more features than being expressly recited in each claim.More precisely, as following
As claims reflect, inventive aspect is all features less than single embodiment disclosed above.Therefore, it abides by
Thus the claims for following specific implementation mode are expressly incorporated in the specific implementation mode, wherein each claim itself
As a separate embodiment of the present invention.
Those skilled in the art should understand that the module of the equipment in example disclosed herein or unit or groups
Part can be arranged in equipment as depicted in this embodiment, or alternatively can be positioned at and the equipment in the example
In different one or more equipment.Module in aforementioned exemplary can be combined into a module or be segmented into addition multiple
Submodule.
Those skilled in the art, which are appreciated that, to carry out adaptively the module in the equipment in embodiment
Change and they are arranged in the one or more equipment different from the embodiment.It can be the module or list in embodiment
Member or component be combined into a module or unit or component, and can be divided into addition multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it may be used any
Combination is disclosed to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so to appoint
Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power
Profit requires, abstract and attached drawing) disclosed in each feature can be by providing the alternative features of identical, equivalent or similar purpose come generation
It replaces.
In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments
In included certain features rather than other feature, but the combination of the feature of different embodiments means in of the invention
Within the scope of and form different embodiments.For example, in the following claims, embodiment claimed is appointed
One of meaning mode can use in any combination.
In addition, be described as herein can be by the processor of computer system or by executing for some in the embodiment
The combination of method or method element that other devices of the function are implemented.Therefore, have for implementing the method or method
The processor of the necessary instruction of element forms the device for implementing this method or method element.In addition, device embodiment
Element described in this is the example of following device：The device is used to implement performed by the element by the purpose in order to implement the invention
Function.
As used in this, unless specifically stated, come using ordinal number " first ", " second ", " third " etc.
Description plain objects are merely representative of the different instances for being related to similar object, and are not intended to imply that the object being described in this way must
Must have the time it is upper, spatially, in terms of sequence or given sequence in any other manner.
Although the embodiment according to limited quantity describes the present invention, above description, the art are benefited from
It is interior it is clear for the skilled person that in the scope of the present invention thus described, it can be envisaged that other embodiments.Additionally, it should be noted that
The language that is used in this specification primarily to readable and introduction purpose and select, rather than in order to explain or limit
Determine subject of the present invention and selects.Therefore, without departing from the scope and spirit of the appended claims, for this
Many modifications and changes will be apparent from for the those of ordinary skill of technical field.For the scope of the present invention, to this
The done disclosure of invention is illustrative and be not restrictive, and it is intended that the scope of the present invention be defined by the claims appended hereto.
Claims (10)
1. a kind of method of statistics application operation indicator, executes in computing device, the method includes：
Acquire the first time sequence of the target operation indicator of intended application；
When obtaining by the first reference time array of the target operation indicator of the collected intended application of third party and the second reference
Between sequence, wherein each described time series includes multiple data points, when each data point corresponds to a unit statistics
Interior operation indicator value, the first time sequence is identical with the quantity of the data point included by the first reference time array,
First unit timing statistics and the first reference units timing statistics are equal, and the second reference units timing statistics are more than first with reference to single
Position timing statistics and for the first reference units timing statistics integral multiple, the first unit timing statistics, the first reference units statistics
Time, the second reference units timing statistics are respectively the first time sequence, the first reference time array, the second reference time
The unit timing statistics of sequence；
The fluctuation situation and overall trend that the first time sequence is adjusted according to first reference time array obtain
Two time serieses；
The operation indicator value that each data point in second time series is adjusted according to second reference time array, obtains
Third time series；
Using the third time series as the actual time sequence of the target operation indicator of intended application.
2. the method for claim 1, wherein adjusting the first time according to first reference time array
Further include step before the step of fluctuation situation and overall trend of sequence：
First time sequence and the first reference time array are smoothed respectively.
3. method as claimed in claim 1 or 2, wherein according to first reference time array come when adjusting described first
Between sequence fluctuation situation and overall trend, the step of obtaining the second time series includes：
First object function and the first intermediate vector are set, and the length of the first intermediate vector is less than included by first time sequence
The quantity of data point；
Intermediate sequence is determined according to first intermediate vector and first time sequence, included number in the intermediate sequence
The quantity at strong point is identical as the first time sequence；
The value of first object function is determined according to first time sequence, the first reference time array and intermediate sequence, according to
The value of one object function adjusts first intermediate vector；
Intermediate sequence corresponding to first time sequence and the optimal value of first object function determines the second time series.
4. method as claimed in claim 3, wherein determine centre according to first intermediate vector and first time sequence
The step of sequence includes：
Polynomial function f (x)=c is set0+c1*x+c2*x^2+c3*x^3+…+cm-1* x^ (m-1), wherein c0~cm-1To be
Number, m are the length of the first intermediate vector, and the first intermediate vector is denoted as Y=[y1,y2,…,ym]；
Without m integer is randomly selected with putting back in the range of from 1 to n, n is the number of data point included in first time sequence
Amount obtains sampling vector X=[x by m integer of taking-up according to being ranked sequentially from small to large1,x2,…,xm]；
By (xi,yi) as sample point the polynomial function is substituted into respectively, to determine coefficient c0~cm-1Value so that it is determined that institute
State polynomial function, wherein 1≤i≤m；
Functional value f (the x corresponding to each data point in the first time sequence are determined according to the polynomial functionj),
In, xjFor position number of the data point in first time sequence, 1≤xj≤ n and xjWith x1~xmValue be all different；
The value of f (1)~f (n) is constituted into intermediate sequence.
5. method as described in claim 3 or 4, wherein the first object function is：
Or
Wherein, min indicates that optimization aim is to make first object function obj1Minimum, k are counting variable, and n is in first time sequence
The quantity of included data point, that r indicates first time sequence and intermediate sequence and sequence, r (k), r (k+1) are indicated respectively
With k-th in sequence r, the value of+1 element of kth, s indicate the first reference time array, s (k), s (k+1) indicate first respectively
K-th in reference time array s, the value of+1 element of kth；
Max indicates that optimization aim is to make first object function obj1Maximum, λ0、λ1For preset coefficient, a00Indicate the first fluctuation sequence
Element value is the quantity of 0 position, a in row br and the second volatility series bs01Indicate that element value is in the first volatility series br
The quantity for the position that element value is 1 in 0, the second volatility series bs, a10Indicate that element value is 1, second in the first volatility series br
The quantity for the position that element value is 0 in volatility series bs, a11Indicate element in the first volatility series br and the second volatility series bs
Value is the quantity of 1 position, and the first volatility series br, the second volatility series bs are determined according to following formula：
Wherein, br (k) indicates that the value of k-th of element in the first volatility series br, bs (k) indicate kth in the second volatility series bs
The value of a element, sign () are sign function.
6. the method as described in any one of claim 3-5, wherein according to first time sequence, the first reference time sequence
Further include step before row and value of the intermediate sequence to determine first object function：
The sampling of same position element is carried out to first time sequence, the first reference time array and intermediate sequence.
7. the method as described in any one of claim 3-6, wherein most according to first time sequence and first object function
Intermediate sequence corresponding to the figure of merit includes the step of determining the second time series：
By the intermediate sequence corresponding to first time sequence and the optimal value of first object function and as the second time series.
8. the method as described in any one of claim 1-7, wherein adjusted according to second reference time array described
The operation indicator value of each data point in second time series, the step of obtaining third time series include：
Second time series is divided into multiple subsequences, the length of each subsequence is equal to the second reference units timing statistics
With the ratio of the first reference units timing statistics, each subsequence corresponds to a data in the second reference time array
Point；
Second intermediate vector, third intermediate vector, the second object function and third object function be set, among described second to
Amount, the ratio that the length of third intermediate vector is the second reference units timing statistics and the first reference units timing statistics；
The second target letter is determined according to multiple subsequences, the second intermediate vector, third intermediate vector, the second reference time array
The value of number and third object function adjusts the second intermediate vector, the according to the value of the second object function and third object function
Three intermediate vectors；
According to the second time series and the second object function, third object function optimal value corresponding to third intermediate vector come
Determine third time series.
9. a kind of computing device, including：
At least one processor；With
Have program stored therein the memory of instruction, wherein described program instruction is configured as being suitable for by least one processor
It executes, described program instruction includes the side for executing the statistics application operation indicator as described in any one of claim 1-8
The instruction of method.
10. a kind of readable storage medium storing program for executing for the instruction that has program stored therein, when described program instruction is read and is executed by computing device,
So that the method that the computing device executes the statistics application operation indicator as described in any one of claim 1-8.
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| EP0779609A2 (en) * | 1995-12-13 | 1997-06-18 | Nec Corporation | Speech adaptation system and speech recognizer |
| CN103729530A (en) * | 2012-10-15 | 2014-04-16 | 富士通株式会社 | Device and method for processing sequence |
| US20160334542A1 (en) * | 2015-05-13 | 2016-11-17 | Conocophillips Company | Time corrections for drilling data |
| CN107516114A (en) * | 2017-08-28 | 2017-12-26 | 湖南大学 | A kind of time Series Processing method and device |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0779609A2 (en) * | 1995-12-13 | 1997-06-18 | Nec Corporation | Speech adaptation system and speech recognizer |
| CN103729530A (en) * | 2012-10-15 | 2014-04-16 | 富士通株式会社 | Device and method for processing sequence |
| US20160334542A1 (en) * | 2015-05-13 | 2016-11-17 | Conocophillips Company | Time corrections for drilling data |
| CN107516114A (en) * | 2017-08-28 | 2017-12-26 | 湖南大学 | A kind of time Series Processing method and device |
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