CN108320109A - A kind of key index determines method and apparatus - Google Patents
A kind of key index determines method and apparatus Download PDFInfo
- Publication number
- CN108320109A CN108320109A CN201810167527.1A CN201810167527A CN108320109A CN 108320109 A CN108320109 A CN 108320109A CN 201810167527 A CN201810167527 A CN 201810167527A CN 108320109 A CN108320109 A CN 108320109A
- Authority
- CN
- China
- Prior art keywords
- index
- economic fluctuation
- economic
- influence
- influence index
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
This application provides a kind of key indexes to determine method and apparatus, including：History economics based on acquisition influence data, determine the economic fluctuation influence index that characterization has an impact economic fluctuation；Using each economic fluctuation influence index as independent variable economic fluctuation influence index screening model is built using the economic fluctuation index for characterizing economic fluctuation situation as dependent variable；The economic fluctuation influence index screening model is trained, the first economic fluctuation influence index collection is filtered out from each economic fluctuation influence index；The first economic fluctuation influence index collection is carried out further to preset Screening Treatment, obtains the key index for influencing the economic fluctuation index.
Description
Technical field
This application involves data analysis technique fields, and method and apparatus are determined in particular to a kind of key index.
Background technology
Currently, when to causing the influence factor of macroeconomic undulation to be analyzed, often according to Principles of Economics pair
Cause the influence factor of economic fluctuation to carry out qualitative analysis, determine the factor being had an impact to economic fluctuation, alternatively, utilizing macroscopic view
What economic growth and above-mentioned qualitative analysis went out causes the influence factor of macroeconomic undulation as independent variable, builds traditional economy
Model is learned, according to the respective variation coefficient in Conventional economics model, to analyze influence situation of each independent variable to economic fluctuation,
And influence degree.But when to causing economic fluctuation influence factor to carry out qualitative analysis, not from all levels, angle
(e.g., consumption, finance etc.) carries out the excavation of depth to influencing economic feature, and the influence factor obtained so as to cause analysis compares
Few, the type of influence factor is relatively simple, so that when being influenced on economic fluctuation by Conventional economics model analysis independent variable,
Cannot there is what is stressed to analyze emphasis influence factor, effectively macroeconomy cannot be regulated and controled, also be conducive to economic stability and send out
Exhibition.
Invention content
In view of this, a kind of key index of being designed to provide of the application determines method and apparatus, it is existing for solving
The single problem of index in technology when predicting economic fluctuation.
In a first aspect, the embodiment of the present application, which provides a kind of key index, determines that method, this method include：
History economics based on acquisition influence data, determine that characterization refers to the economic fluctuation influence that economic fluctuation has an impact
Mark；
Using each economic fluctuation influence index as independent variable, will characterize the economic fluctuation index of economic fluctuation situation as because
Variable builds economic fluctuation influence index screening model；
The economic fluctuation influence index screening model is trained, is screened from each economic fluctuation influence index
Go out the first economic fluctuation influence index collection；
The first economic fluctuation influence index collection is carried out further to preset Screening Treatment, obtains influencing the economic wave
The key index of dynamic index.
Optionally, the economic fluctuation influence index screening model is trained, is specifically included：
It is influenced in data from the history economics of acquisition, determines the index value of each economic fluctuation influence index；
Obtain the economic fluctuation index corresponding with the index value of each economic fluctuation influence index place period
Index value；
Using the index value of determining economic fluctuation influence index as the value of independent variable, the economic fluctuation of the same period is referred to
Value of the target index value as dependent variable is trained the economic fluctuation influence index screening model.
Optionally, the first economic fluctuation influence index collection is filtered out from each economic fluctuation influence index, it is specific to wrap
It includes：
Based on training result, each economic fluctuation influence index in the economic fluctuation influence index screening model after training is determined
Corresponding contribution margin；
The corresponding economic fluctuation influence index of contribution margin that will be greater than default contribution margin threshold value is determined as first economy
Influence of fluctuations index set.
Optionally, further include：
Each economic fluctuation influence index degree of correlation with the economic fluctuation index respectively is calculated, is more than by the degree of correlation
The economic fluctuation influence index of default relevance threshold is determined as the second economic fluctuation influence index collection.
Optionally, described that the first economic fluctuation influence index collection is carried out further to preset Screening Treatment, obtain shadow
The key index for ringing the economic fluctuation index, specifically includes：
The first economic fluctuation influence index collection and second economic fluctuation are influenced using Principal Component Analysis Algorithm
Index set is handled, and the key index for influencing the economic fluctuation index is obtained.
Second aspect, the embodiment of the present application provide a kind of key index determining device, which includes：
Determining module influences data for the history economics based on acquisition, determines what characterization had an impact economic fluctuation
Economic fluctuation influence index；
Module is built, for using each economic fluctuation influence index as independent variable, the economy of economic fluctuation situation will to be characterized
Index is fluctuated as dependent variable, builds economic fluctuation influence index screening model；
First processing module, for being trained to the economic fluctuation influence index screening model, from each economy
The first economic fluctuation influence index collection is filtered out in influence of fluctuations index；
Second processing module further presets Screening Treatment for being carried out to the first economic fluctuation influence index collection,
Obtain influencing the key index of the economic fluctuation index.
Optionally, the first processing module is used for：
It is influenced in data from the history economics of acquisition, determines the index value of each economic fluctuation influence index；
Obtain the economic fluctuation index corresponding with the index value of each economic fluctuation influence index place period
Index value；
Using the index value of determining economic fluctuation influence index as the value of independent variable, the economic fluctuation of the same period is referred to
Value of the target index value as dependent variable is trained the economic fluctuation influence index screening model.
Optionally, the first processing module is used for：
Based on training result, each economic fluctuation influence index in the economic fluctuation influence index screening model after training is determined
Corresponding contribution margin；
The corresponding economic fluctuation influence index of contribution margin that will be greater than default contribution margin threshold value is determined as first economy
Influence of fluctuations index set.
Optionally, further include：Computing module, the computing module are used for：
Each economic fluctuation influence index degree of correlation with the economic fluctuation index respectively is calculated, is more than by the degree of correlation
The economic fluctuation influence index of default relevance threshold is determined as the second economic fluctuation influence index collection.
Optionally, the Second processing module is specifically used for：
The first economic fluctuation influence index collection and second economic fluctuation are influenced using Principal Component Analysis Algorithm
Index set is handled, and the key index for influencing the economic fluctuation index is obtained.
Key index provided by the embodiments of the present application determines method and apparatus, influences to determine in data from history economics economical
Influence of fluctuations index, by building and training economic fluctuation influence index screening model, to refer to from above-mentioned economic fluctuation influence
Mark determines the first economic fluctuation influence index collection being affected to economic fluctuation, further to the first economic fluctuation influence index
Collection carries out Screening Treatment, obtains the key index for influencing economic fluctuation index.In this way, economical to influencing with angle in all its bearings
The index of fluctuation carries out profound excavation, increases the index being had an impact to economic fluctuation, reduces the prior art and pass through
The deficiency that relatively single index predicts economic fluctuation improves the accuracy predicted economic fluctuation.
To enable the above objects, features, and advantages of the application to be clearer and more comprehensible, preferred embodiment cited below particularly, and coordinate
Appended attached drawing, is described in detail below.
Description of the drawings
It, below will be to needed in the embodiment attached in order to illustrate more clearly of the technical solution of the embodiment of the present application
Figure is briefly described, it should be understood that the following drawings illustrates only some embodiments of the application, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is the flow diagram that a kind of key index provided by the embodiments of the present application determines method；
Fig. 2 is the schematic diagram that a kind of history economics provided by the embodiments of the present application influence data；
Fig. 3 is a kind of structural schematic diagram of key index determining device provided by the embodiments of the present application；
Fig. 4 is a kind of structural schematic diagram of computer equipment 400 provided by the embodiments of the present application.
Specific implementation mode
To keep the purpose, technical scheme and advantage of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
Middle attached drawing, technical solutions in the embodiments of the present application are clearly and completely described, it is clear that described embodiment is only
It is some embodiments of the present application, instead of all the embodiments.The application being usually described and illustrated herein in the accompanying drawings is real
Applying the component of example can be arranged and designed with a variety of different configurations.Therefore, below to the application's for providing in the accompanying drawings
The detailed description of embodiment is not intended to limit claimed scope of the present application, but is merely representative of the selected reality of the application
Apply example.Based on embodiments herein, institute that those skilled in the art are obtained without making creative work
There is other embodiment, shall fall in the protection scope of this application.
The embodiment of the present application provides a kind of key index and determines method, as shown in Figure 1, this approach includes the following steps：
S101, the history economics based on acquisition influence data, determine the economic fluctuation that characterization has an impact economic fluctuation
Influence index；
Here, it is usually to be obtained from default platform that history economics, which influence data, for example, Educational website, job hunting website, political affairs
Mansion site for service etc., the history economics of acquisition influence data and can refer to Fig. 2；The economic fluctuation that economic fluctuation has an impact is influenced
Index is generally the economic fluctuation influence index that is had an impact to GDP (GDP), and economic fluctuation influence index can be with
It is patent index, certificate index, major field index, regional index, financing index etc., e.g., patent index can be enterprise Shen
The quantity of patent please, certificate index can be English Band certificate, the ENGLISH BAND SIX CERTIFICATE that student obtains, and regional index can be with
For area of mainly obtaining employment etc., a pair of each index that differs herein is illustrated.
It, can be from the level of consumption, investment level, inlet and outlet level, industry warp after getting history economics and influencing data
Ji is horizontal, finance is horizontal angularly excavates the factor for influencing macroeconomic undulation, and then finds to influence the feature of economic fluctuation；Together
When, for each area, economic impact degree of the fluctuation situation to this area of this area's industrial economy can be excavated, to there is side
The development priority industry of emphasis, drives the economic growth of this area.It is carried out by the index to influencing economic fluctuation of multi-angle
Excavate, also have important meaning for financial investments such as stock, futures, bonds, in this way, to macroeconomy have preferably prediction and
Regulation and control ensure stable macroeconomy, health, lasting development.
S102 will characterize the economic fluctuation index of economic fluctuation situation using each economic fluctuation influence index as independent variable
As dependent variable, economic fluctuation influence index screening model is built；
Here, the economic fluctuation index of characterization economic fluctuation situation can be the index that characterization GDP fluctuates situation；Economic wave
Dynamic influence index screening model can be built according to the algorithm of random forest, and the application not limits this.
S103 is trained the economic fluctuation influence index screening model, from each economic fluctuation influence index
In filter out the first economic fluctuation influence index collection；
To the process that economic fluctuation influence index screening model is trained, following steps are specifically included：
It is influenced in data from the history economics of acquisition, determines the index value of each economic fluctuation influence index；
Obtain the economic fluctuation index corresponding with the index value of each economic fluctuation influence index place period
Index value；
Using the index value of determining economic fluctuation influence index as the value of independent variable, the economic fluctuation of the same period is referred to
Value of the target index value as dependent variable is trained the economic fluctuation influence index screening model.
Here it is possible to which obtaining the history economics of each historical time section in multiple historical time sections influences data and corresponding
The index value of economic fluctuation index, historical time section can be continuous number of days, month, season etc., for example, the history warp obtained
Ji influences the data that data are January, then the index value of the corresponding economic fluctuation index obtained is also January.
In specific implementation, economic fluctuation influence index screening model is what the algorithm based on random forest was built, in structure
During building, multiple economic fluctuation index screening submodels can be built, each economic fluctuation index screening submodel can claim
For a random tree.It, can be from determining multiple economic fluctuation influence indexs for each random tree when building random tree
In, it selects preset number economic fluctuation influence index as the independent variable of the random tree, corresponding economic fluctuation index is made
For the dependent variable of the random tree.When being trained to each random tree, for each random tree, the independent variable of the random tree is determined
The index value of the index value of corresponding economic fluctuation influence index and the economic fluctuation index of the corresponding same period, it is random to this
Tree is trained.Wherein, the independent variable in different random trees can part it is identical, can also all it is identical, can also be complete
Difference can be determined on a case-by-case basis, and the number of the economic fluctuation influence index of each random tree selection should regard actual conditions and determine.
After completing to the training of economic fluctuation influence index screening model, filtered out from each economic fluctuation influence index
First economic fluctuation influence index collection, specifically includes：
Based on training result, each economic fluctuation influence index in the economic fluctuation influence index screening model after training is determined
Corresponding contribution margin；
The corresponding economic fluctuation influence index of contribution margin that will be greater than default contribution margin threshold value is determined as first economy
Influence of fluctuations index set.
Here, contribution margin threshold value can be that user is arranged based on practical application.
In specific implementation, the example for continuing above-mentioned trained random tree can obtain current random tree in training random tree
In economic fluctuation influence index influential on economic fluctuation, by being trained to a large amount of random tree, it is multiple right to obtain
The influential economic fluctuation influence index of economic fluctuation.Obtaining multiple economic fluctuation influence indexs influential on economic fluctuation
Afterwards, the contribution margin for each economic fluctuation influence index that can be determined by way of ballot.For example, having trained 5 at random
Tree, obtained economic fluctuation influence index are respectively：A, b, c, a, c, then, economic fluctuation influence index a have 2 tickets, b have 1 ticket,
C has 2 tickets, and the poll of above-mentioned economic fluctuation influence index can be as the contribution margin of the economic fluctuation influence index.But should
Understand, above-mentioned example is only schematical, can obtain a large amount of economic fluctuation influence index in practical applications, should be with reality
Subject to situation.
S104 carries out the first economic fluctuation influence index collection further to preset Screening Treatment, obtain described in influence
The key index of economic fluctuation index.
Before executing step S104, this method is further comprising the steps of：
Each economic fluctuation influence index degree of correlation with the economic fluctuation index respectively is calculated, is more than by the degree of correlation
The economic fluctuation influence index of default relevance threshold is determined as the second economic fluctuation influence index collection.
In specific implementation, it is related to economic fluctuation index to be calculated by the following formula any economic fluctuation influence index
Spend r：
Wherein, r is the degree of correlation of any economic fluctuation influence index and economic fluctuation index, and x is any economic fluctuation
Influence index, y are economic fluctuation index, and N is the number of the corresponding index value of any economic fluctuation influence index, generally just
Integer.
For example, any economic fluctuation influence index x is a, the number N of the corresponding index values of a is 3, above-mentioned 3 indexs
Value can be the value of 3 historical time sections respectively, and a is corresponding with economic fluctuation index y in the index value of each historical time section
Index value, that is, 3 values of a are corresponding with the value of 3 economic fluctuation index ies, by each index value of a and corresponding economic fluctuation
The value of index y inputs above-mentioned relatedness computation formula, and then obtains economic fluctuation influence index a and corresponding economic fluctuation index
The degree of correlation.
Each economic fluctuation influence index and the calculating process of the degree of correlation of economic fluctuation index are identical as above-mentioned example, this
Place no longer explains one by one.
Can will be more than preset phase after obtaining the degree of correlation of each economic fluctuation influence index with economic fluctuation index
The economic fluctuation influence index of pass degree threshold value is determined as the second economic fluctuation influence index collection, can also according to the degree of correlation by height to
Low sequence is ranked up each degree of correlation, and preceding quantity threshold economic fluctuation influence is selected to refer to from the degree of correlation after sequence
Mark is determined as the second economic fluctuation influence index collection.
After obtaining the second economic fluctuation influence index collection, the first economic fluctuation influence index collection is carried out further
Default Screening Treatment, obtains the key index for influencing the economic fluctuation index, specifically includes following steps：
The first economic fluctuation influence index collection and second economic fluctuation are influenced using Principal Component Analysis Algorithm
Index set is handled, and the key index for influencing the economic fluctuation index is obtained.
In specific implementation, the first economic fluctuation influence index collection and the second economic fluctuation influence index collection due to obtaining
In there may be common economic fluctuation influence index, in order to avoid economic fluctuation influence index repeats, therefore, take the first economy
The union of influence of fluctuations index set and the second economic fluctuation influence index collection further utilizes Principal Component Analysis Algorithm
(Principal Component Analysis, PCA algorithm) to taking the economic fluctuation influence index after union to handle, most
Obtain influencing the key index of economic fluctuation index eventually, the prior art is to having utilized the process of Principal Component Analysis Algorithm screening index
There is detailed introduction, is no longer excessively illustrated herein.
After obtaining key index, can using obtained key index as independent variable, using economic fluctuation index as because
Variable, structure economic fluctuation influence model and training, influence the index value that data determine key index based on history economics, will be upper
The economic fluctuation influence model of training, the index for the economic fluctuation index predicted are completed in the index value input for stating key index
Value, predicts macroeconomy, so that related personnel regulates and controls macroeconomy based on prediction result.
In addition, after obtaining key index, key that can be by decision Tree algorithms or logistic regression algorithm to obtaining
Index carries out qualitative analysis, can also carry out quantitative analysis to obtained key index by SVR homing methods, with to obtaining
Prediction effect of the key index in prediction is assessed, in this way, can be carried out to obtained key index in order to related personnel
It corrects, improves the accuracy for carrying out economic fluctuation influence by key index.
Key index provided by the embodiments of the present application determines method, influences to determine economic fluctuation shadow in data from history economics
Snap mark, by building and training economic fluctuation influence index screening model, to be determined from above-mentioned economic fluctuation influence index
To the first economic fluctuation influence index collection that economic fluctuation is affected, further the first economic fluctuation influence index collection is carried out
Screening Treatment obtains the key index for influencing the economic fluctuation index.In this way, in all its bearings with angle to influencing economic wave
Dynamic index carries out profound excavation, increases the index being had an impact to economic fluctuation, reduces the prior art and pass through phase
To the deficiency that single index predicts economic fluctuation, the accuracy predicted economic fluctuation is improved.
The embodiment of the present application provides a kind of key index determining device, as shown in figure 3, the device includes：
Determining module 31 influences data for the history economics based on acquisition, determines that characterization has an impact economic fluctuation
Economic fluctuation influence index；
Module 32 is built, for using each economic fluctuation influence index as independent variable, the warp of economic fluctuation situation will to be characterized
Ji fluctuation index builds economic fluctuation influence index screening model as dependent variable；
First processing module 33, for being trained to the economic fluctuation influence index screening model, from each warp
The first economic fluctuation influence index collection is filtered out in Ji influence of fluctuations index；
Second processing module 34, for the first economic fluctuation influence index collection further preset at screening
Reason, obtains the key index for influencing the economic fluctuation index.
Optionally, the first processing module 33 is used for：
It is influenced in data from the history economics of acquisition, determines the index value of each economic fluctuation influence index；
Obtain the economic fluctuation index corresponding with the index value of each economic fluctuation influence index place period
Index value；
Using the index value of determining economic fluctuation influence index as the value of independent variable, the economic fluctuation of the same period is referred to
Value of the target index value as dependent variable is trained the economic fluctuation influence index screening model.
Optionally, the first processing module 33 is used for：
Based on training result, each economic fluctuation influence index in the economic fluctuation influence index screening model after training is determined
Corresponding contribution margin；
The corresponding economic fluctuation influence index of contribution margin that will be greater than default contribution margin threshold value is determined as first economy
Influence of fluctuations index set.
Optionally, which further includes：Computing module 35, the computing module 45 are used for
Each economic fluctuation influence index degree of correlation with the economic fluctuation index respectively is calculated, is more than by the degree of correlation
The economic fluctuation influence index of default relevance threshold is determined as the second economic fluctuation influence index collection.
Optionally, the Second processing module 34 is specifically used for：
The first economic fluctuation influence index collection and second economic fluctuation are influenced using Principal Component Analysis Algorithm
Index set is handled, and the key index for influencing the economic fluctuation index is obtained.
Method is determined corresponding to the key index in Fig. 4, the embodiment of the present application also provides a kind of computer equipment 400,
As shown in figure 4, the equipment includes memory 401, processor 402 and is stored on the memory 401 and can be in the processor 402
The computer program of upper operation, wherein above-mentioned processor 402 realizes that above-mentioned key index determines when executing above computer program
Method.
Specifically, above-mentioned memory 401 and processor 402 can be general memory and processor, do not do have here
Body limits, and when the computer program of 402 run memory 401 of processor storage, is able to carry out above-mentioned key index determination side
Method, to solving the problems, such as that the index in the prior art when predicting economic fluctuation is single, the application is in all its bearings and angle
Index to influencing economic fluctuation carries out profound excavation, increases the index being had an impact to economic fluctuation, reduces existing
The deficiency for having technology to be predicted economic fluctuation by relatively single index improves the standard predicted economic fluctuation
Exactness.
Method is determined corresponding to the key index in Fig. 1, and the embodiment of the present application also provides a kind of computer-readable storages
Medium is stored with computer program on the computer readable storage medium, is executed when which is run by processor
State the step of key index determines method.
Specifically, which can be general storage medium, such as mobile disk, hard disk, on the storage medium
Computer program when being run, be able to carry out above-mentioned key index and determine method, solve predicting economic wave in the prior art
The single problem of index when dynamic, the application carry out profound digging with angle to the index for influencing economic fluctuation in all its bearings
Pick, increases the index being had an impact to economic fluctuation, reduces the prior art by relatively single index to economic fluctuation
The deficiency predicted improves the accuracy predicted economic fluctuation.
In embodiment provided herein, it should be understood that disclosed system and method, it can be by others side
Formula is realized.System embodiment described above is only schematical, for example, the division of the unit, only one kind are patrolled
Volume function divides, formula that in actual implementation, there may be another division manner, in another example, multiple units or component can combine or can
To be integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some communication interfaces, system or unit
It connects, can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme
's.
In addition, each functional unit in embodiment provided by the present application can be integrated in a processing unit, also may be used
It, can also be during two or more units be integrated in one unit to be that each unit physically exists alone.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer read/write memory medium.Based on this understanding, the technical solution of the application is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be expressed in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be
People's computer, server or network equipment etc.) execute each embodiment the method for the application all or part of step.
And storage medium above-mentioned includes：USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic disc or CD.
It should be noted that：Similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined, then it further need not be defined and explained in subsequent attached drawing in a attached drawing, in addition, term " the
One ", " second ", " third " etc. are only used for distinguishing description, are not understood to indicate or imply relative importance.
Finally it should be noted that：Embodiment described above, the only specific implementation mode of the application, to illustrate the application
Technical solution, rather than its limitations, the protection domain of the application is not limited thereto, although with reference to the foregoing embodiments to this Shen
It please be described in detail, it will be understood by those of ordinary skill in the art that：Any one skilled in the art
In the technical scope that the application discloses, it can still modify to the technical solution recorded in previous embodiment or can be light
It is readily conceivable that variation or equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not make
The essence of corresponding technical solution is detached from the spirit and scope of the embodiment of the present application technical solution.The protection in the application should all be covered
Within the scope of.Therefore, the protection domain of the application shall be subject to the protection scope of the claim.
Claims (10)
1. a kind of key index determines method, which is characterized in that this method includes：
History economics based on acquisition influence data, determine the economic fluctuation influence index that characterization has an impact economic fluctuation；
Using each economic fluctuation influence index as independent variable, the economic fluctuation index of economic fluctuation situation will be characterized as because becoming
Amount builds economic fluctuation influence index screening model；
The economic fluctuation influence index screening model is trained, is filtered out from each economic fluctuation influence index
One economic influence of fluctuations index set；
The first economic fluctuation influence index collection is carried out further to preset Screening Treatment, obtaining, which influences the economic fluctuation, refers to
Target key index.
2. the method as described in claim 1, which is characterized in that instructed to the economic fluctuation influence index screening model
Practice, specifically includes：
It is influenced in data from the history economics of acquisition, determines the index value of each economic fluctuation influence index；
Obtain the index of the economic fluctuation index corresponding with the index value of each economic fluctuation influence index place period
Value；
Using the index value of determining economic fluctuation influence index as the value of independent variable, by the economic fluctuation index of the same period
Value of the index value as dependent variable is trained the economic fluctuation influence index screening model.
3. the method as described in claim 1, which is characterized in that filter out the first warp from each economic fluctuation influence index
Ji influence of fluctuations index set, specifically includes：
Based on training result, determine that each economic fluctuation influence index corresponds in the economic fluctuation influence index screening model after training
Contribution margin；
The corresponding economic fluctuation influence index of contribution margin that will be greater than default contribution margin threshold value is determined as first economic fluctuation
Influence index collection.
4. method as described in any one of claims 1-3, which is characterized in that further include：
Each economic fluctuation influence index degree of correlation with the economic fluctuation index respectively is calculated, is more than default by the degree of correlation
The economic fluctuation influence index of relevance threshold is determined as the second economic fluctuation influence index collection.
5. method as claimed in claim 4, which is characterized in that it is described to the first economic fluctuation influence index collection into traveling
One step presets Screening Treatment, obtains the key index for influencing the economic fluctuation index, specifically includes：
Using Principal Component Analysis Algorithm to the first economic fluctuation influence index collection and the second economic fluctuation influence index
Collection is handled, and the key index for influencing the economic fluctuation index is obtained.
6. a kind of key index determining device, which is characterized in that the device includes：
Determining module influences data for the history economics based on acquisition, determines the economy that characterization has an impact economic fluctuation
Influence of fluctuations index；
Module is built, for using each economic fluctuation influence index as independent variable, the economic fluctuation of economic fluctuation situation will to be characterized
Index builds economic fluctuation influence index screening model as dependent variable；
First processing module, for being trained to the economic fluctuation influence index screening model, from each economic fluctuation
The first economic fluctuation influence index collection is filtered out in influence index；
Second processing module is further preset Screening Treatment for being carried out to the first economic fluctuation influence index collection, is obtained
Influence the key index of the economic fluctuation index.
7. device as claimed in claim 6, which is characterized in that the first processing module is used for：
It is influenced in data from the history economics of acquisition, determines the index value of each economic fluctuation influence index；
Obtain the index of the economic fluctuation index corresponding with the index value of each economic fluctuation influence index place period
Value；
Using the index value of determining economic fluctuation influence index as the value of independent variable, by the economic fluctuation index of the same period
Value of the index value as dependent variable is trained the economic fluctuation influence index screening model.
8. device as claimed in claim 6, which is characterized in that the first processing module is used for：
Based on training result, determine that each economic fluctuation influence index corresponds in the economic fluctuation influence index screening model after training
Contribution margin；
The corresponding economic fluctuation influence index of contribution margin that will be greater than default contribution margin threshold value is determined as first economic fluctuation
Influence index collection.
9. such as claim 6-8 any one of them devices, which is characterized in that further include：Computing module, the computing module are used
In：
Each economic fluctuation influence index degree of correlation with the economic fluctuation index respectively is calculated, is more than default by the degree of correlation
The economic fluctuation influence index of relevance threshold is determined as the second economic fluctuation influence index collection.
10. device as claimed in claim 9, which is characterized in that the Second processing module is specifically used for：
Using Principal Component Analysis Algorithm to the first economic fluctuation influence index collection and the second economic fluctuation influence index
Collection is handled, and the key index for influencing the economic fluctuation index is obtained.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810167527.1A CN108320109A (en) | 2018-02-28 | 2018-02-28 | A kind of key index determines method and apparatus |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810167527.1A CN108320109A (en) | 2018-02-28 | 2018-02-28 | A kind of key index determines method and apparatus |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108320109A true CN108320109A (en) | 2018-07-24 |
Family
ID=62899983
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810167527.1A Pending CN108320109A (en) | 2018-02-28 | 2018-02-28 | A kind of key index determines method and apparatus |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108320109A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523054A (en) * | 2018-09-29 | 2019-03-26 | 中山大学 | A kind of season Runoff Forecast selecting predictors method based on random walk |
| CN112329271A (en) * | 2020-12-04 | 2021-02-05 | 国网山东省电力公司电力科学研究院 | Thermal power generating unit peak regulation key index identification method and device based on multiple PCAs |
| CN118608013A (en) * | 2024-08-07 | 2024-09-06 | 深圳特斯联智能科技有限公司 | Data index abnormal monitoring method and device |
-
2018
- 2018-02-28 CN CN201810167527.1A patent/CN108320109A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523054A (en) * | 2018-09-29 | 2019-03-26 | 中山大学 | A kind of season Runoff Forecast selecting predictors method based on random walk |
| CN112329271A (en) * | 2020-12-04 | 2021-02-05 | 国网山东省电力公司电力科学研究院 | Thermal power generating unit peak regulation key index identification method and device based on multiple PCAs |
| CN118608013A (en) * | 2024-08-07 | 2024-09-06 | 深圳特斯联智能科技有限公司 | Data index abnormal monitoring method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wikström et al. | Solving the stand management problem under biodiversity-related considerations | |
| CN109784779B (en) | Financial risk prediction method, device and storage medium | |
| CN109859052B (en) | Intelligent recommendation method and device for investment strategy, storage medium and server | |
| CN108833458B (en) | Application recommendation method, device, medium and equipment | |
| WO2018103718A1 (en) | Application recommendation method and apparatus, and server | |
| Yun et al. | Ecosystem-based management and the wealth of ecosystems | |
| CN107169573A (en) | Using composite machine learning model come the method and system of perform prediction | |
| CN110738564A (en) | Post-loan risk assessment method and device and storage medium | |
| Tayalı | A novel backtesting methodology for clustering in mean–variance portfolio optimization | |
| US20150095756A1 (en) | Method and apparatus for multi-loop, real-time website optimization | |
| Kapaun et al. | Does the optimal size of a fish stock increase with environmental uncertainties? | |
| CN108320109A (en) | A kind of key index determines method and apparatus | |
| DE112021003262T5 (en) | RECOGNIZING SOURCE RECORDS THAT MATCH A TRANSFER LEARNING METHOD FOR A TARGET DOMAIN | |
| CN105260171A (en) | Virtual item generation method and apparatus | |
| CN107169574A (en) | Using nested machine learning model come the method and system of perform prediction | |
| Özpeynirci et al. | An interactive algorithm for multiple criteria constrained sorting problem | |
| Fielke et al. | Co-innovation to increase community resilience: influencing irrigation efficiency in the Waimakariri Irrigation Scheme | |
| Davis et al. | Good timing: The economics of optimal stopping | |
| CN107016398A (en) | Data processing method and device | |
| US20210256479A1 (en) | Retirement Score Calculator | |
| Gyurkó et al. | Monte Carlo methods via a dual approach for some discrete time stochastic control problems | |
| Pflug et al. | The AURORA financial management system: Model and parallel implementation design | |
| TW202133089A (en) | Method for optimally promoting decisions and computer program product thereof | |
| Błażejczyk-Majka | Application of DEA for evaluating the efficiency of economic policy as exemplified by EU agriculture | |
| Mußhoff et al. | What benefits are to be derived from improved farm program planning approaches?–The role of time series models and stochastic optimization |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180724 |