CN110070475A - To the method and terminal device of family income analysis of Influential Factors - Google Patents
To the method and terminal device of family income analysis of Influential Factors Download PDFInfo
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Abstract
The present invention is suitable for analysis of Influential Factors technical field, provides the method and terminal device of a kind of pair of family income analysis of Influential Factors, this method comprises: by obtaining family income survey sample；The family income survey sample is handled, determines the factor for influencing family income；The factor of the influence family income is analyzed, determines the target factor for influencing family income, so as to obtain and in detail, comprehensively and accurately analyze as a result, providing targetedly service providing data foundation for government department by analyzing big data.
Description
Technical field
The invention belongs to the sides of analysis of Influential Factors technical field more particularly to a kind of pair of family income analysis of Influential Factors
Method and terminal device.
Background technique
Per capita income analysis of Influential Factors is the analysis to the maximum factor of disturbance degree in per capita income influence factor.This
Sample minimum living relief department pointedly can succour minimum living personnel according to the fructufy of per capita income impact analysis is existing,
Keep minimum living relief department more efficient when carrying out minimum living relief.
Currently used analysis method is mainly manually empirically determined, and carries out by the experience and knowledge of analysis personnel
Analysis, modelling is not-so-practical when using correlation analysis family income factor, not in one's hands middle grasped big
The data of amount are analyzed, and cause the result obtained general, unilateral, and accuracy, efficiency are all lower.
Summary of the invention
In view of this, the embodiment of the invention provides the methods of a kind of pair of family income analysis of Influential Factors and terminal to set
It is standby, to solve to analyze, cause by the experience and knowledge of analysis personnel in the prior art due to being manually empirically determined
It is general, unilateral to analyze result, and the problem that accuracy, efficiency are all lower.
The first aspect of the embodiment of the present invention provides the method for a kind of pair of family income analysis of Influential Factors, comprising:
Obtain family income survey sample；
The family income survey sample is handled, determines the factor for influencing family income；
The factor for influencing family income is analyzed, determines the target factor for influencing family income.
In one embodiment, described that the family income survey sample is handled, determine influence family income because
Element, comprising:
The family income survey sample is screened according to preset rules, obtains target household income survey sample；
Using layering sampling with unequal probability method, the target household income survey sample is sampled, is obtained wait divide
Analyse family income survey sample；
The family income survey sample to be analyzed is analyzed, according to each family income survey sample to be analyzed
This feature and macro-economy influence, determines the factor for influencing family income.
In one embodiment, described to analyze the factor for influencing family income, determining influences family income
Target factor, comprising:
The corresponding sample data of factor for influencing family income is standardized, it is corresponding to obtain the sample data
Vector；
According to the corresponding vector of the sample data, the weight of each factor for influencing family income is calculated；
It selects to influence factor corresponding to weight limit in the weight of each factor of family income to receive as family is influenced
The target factor entered.
In one embodiment, described according to the corresponding vector of the sample data, calculate each influence family income
Factor weight, comprising:
According to the corresponding vector of the sample data, the first factor in first sample that calculates accounts for the family income to be analyzed
The specific gravity of investigation sample, the first sample are any one sample in the family income survey sample to be analyzed, described the
One factor is any one factor in the first sample；
According to the specific gravity of the first factor in first sample, the comentropy of the first factor in first sample is calculated；
According to the comentropy of the first factor in first sample, the difference property coefficient of the first factor in first sample is calculated；
According to the difference property coefficient of the first factor in first sample, the weight of the first factor in first sample is determined；
According to the method for determining the weight of the first factor in first sample, each factor is calculated respectively in the family to be analyzed
Weight in the income survey sample of front yard.
In one embodiment, the corresponding vector of factor of the influence family income according to acquisition calculates first
The first factor accounts for the specific gravity of the family income survey sample to be analyzed in sample, comprising:
According toIt calculates the first factor in first sample and accounts for the family income survey sample to be analyzed
Specific gravity, the PijIndicate the specific gravity of the first factor in first sample, the XijIndicate that the first factor is corresponding in first sample
The vector of sample data；
The specific gravity according to the first factor in first sample calculates the comentropy of the first factor in first sample, comprising:
According toCalculate the comentropy of the first factor in first sample, the SijIndicate the
The comentropy of first factor in one sample；
The comentropy according to the first factor in first sample calculates the otherness system of the first factor in first sample
Number, comprising:
According to gij=1-Sij, calculate the difference property coefficient of the first factor in first sample, the gijIt indicates in first sample
The difference property coefficient of first factor；
The difference property coefficient according to the first factor in first sample, determines the weight of the first factor in first sample,
Include:
According toDetermine the weight of the first factor in first sample, aijIt indicates in first sample
The weight of first factor.
In one embodiment, described to calculate each factor power in the family income survey sample to be analyzed respectively
Weight, comprising:
According to the weight of the first factor in first sample, the first factor is calculated separately in the family income survey to be analyzed
Weight in sample；
Using the sum of weight of first factor in the family income survey sample to be analyzed as the first factor
Weight；
According to the method for the weight for first factor that determines, the weight of each factor is calculated.
The second aspect of the embodiment of the present invention provides the device of a kind of pair of family income analysis of Influential Factors, comprising:
Module is obtained, for obtaining family income survey sample；
Processing module determines the factor for influencing family income for handling the family income survey sample；
Analysis module determines the target for influencing family income for analyzing the factor for influencing family income
Factor.
In one embodiment, the processing module, comprising:
Acquiring unit obtains target household income and adjusts for screening the family income survey sample according to preset rules
Look into sample；
Sampling unit, for being carried out to the target household income survey sample using layering sampling with unequal probability method
Sampling, obtains family income survey sample to be analyzed；
Analytical unit, for analyzing the family income survey sample to be analyzed, according to each described to be analyzed
The feature and macro-economy influence of family income survey sample determine the factor for influencing family income.
The third aspect of the embodiment of the present invention provides a kind of terminal device, comprising: memory, processor and is stored in
In the memory and the computer program that can run on the processor, which is characterized in that described in the processor executes
The step as described in the method family income analysis of Influential Factors is realized when computer program.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, comprising: the computer can
It reads storage medium and is stored with computer program, which is characterized in that realize when the computer program is executed by processor such as to family
Step described in the method for analysis of Influential Factors is taken in front yard.
Existing beneficial effect is the embodiment of the present invention compared with prior art: by obtaining family income survey sample；
The family income survey sample is handled, determines the factor for influencing family income；On it is described influence family income because
Element is analyzed, and determines the target factor for influencing family income, so as to by analyzing big data, obtain in detail,
Comprehensively and accurately analysis is as a result, provide targetedly service providing data foundation for government department.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the implementation process schematic diagram of the method provided in an embodiment of the present invention to family income analysis of Influential Factors；
Fig. 2 is the implementation process schematic diagram of the determining factor for influencing family income provided in an embodiment of the present invention；
Fig. 3 is the flow diagram of the determining target factor for influencing family income provided in an embodiment of the present invention；
Fig. 4 is the process signal of the weight provided in an embodiment of the present invention for calculating each factor for influencing family income
Figure；
Fig. 5 is the exemplary diagram of the device provided in an embodiment of the present invention to family income analysis of Influential Factors；
Fig. 6 is the schematic diagram of processing module provided in an embodiment of the present invention；
Fig. 7 is the schematic diagram of terminal device provided in an embodiment of the present invention.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
Fig. 1 is the implementation process schematic diagram of the method provided in an embodiment of the present invention to family income analysis of Influential Factors,
Details are as follows.
Step 101, family income survey sample is obtained.
Optionally, family income survey sample is the data source analyzed family income influence factor in this step,
It can obtain data by the previous survey of government department, can also obtain data by indirect mode, in this application
The source of family income survey sample is not limited.
Step 102, the family income survey sample is handled, determines the factor for influencing family income.
Optionally, carrying out processing to family income survey sample is to guarantee the accuracy of subsequent analysis data, reliable
Property, as shown in Fig. 2, handling in step 102 the family income survey sample, determine that the factor for influencing family income can
To include the following steps.
Step 2201, the family income survey sample is screened according to preset rules, obtains target household income survey sample
This.
Optionally, screening the family income survey sample according to preset rules in step 2201 may include: rejecting nothing
Answer and be not suitable as the family income survey sample of investigation object.Remaining family income survey sample is target man
Front yard income survey sample can carry out subsequent processing.
Step 2202, using layering sampling with unequal probability method, the target household income survey sample is sampled,
Obtain family income survey sample to be analyzed.
Optionally, the layering sampling with unequal probability method in this step includes layered sampling method and sampling with unequal probability side
Method.Wherein, layered sampling method is according to the size of each layer basic unit standard deviation, to determine each layer sample number purposive sampling side
Method.Optionally, each section is known as one layer, carries out simple random sampling in each layer, for target household income survey
The number of plies of sample point, determines according to actual conditions, but can be the need to ensure that the difference of sample in every layer wants small, and different layers it
Between difference it is as big as possible.Sampling with unequal probability method refers to a certain auxiliary of constituent parts are drawn in totality probability and these units
Help variable size directly proportional, for example, target household income survey sample is from different areas, the area big for auxiliary variable
The probability that middle sample may be drawn is big, and the sample size of extraction is more, and sample may be taken out in the area small for auxiliary variable
In probability it is small, the sample size of extraction is few, and auxiliary variable may be determines according to actual conditions.
Step 2203, the family income survey sample to be analyzed is analyzed, according to each family to be analyzed
The feature and macro-economy influence of income survey sample determine the factor for influencing family income.
Optionally, it is analyzed by treating analysis family income survey sample, determines that the factor for influencing family income can
To include: level, the style of economic increase, urbanization rate and the unemployment rate etc. of economic growth.
There is direct correlation property in the economic level of country and the family income of resident, therefore family income growth increases with economical
Long horizontal mutually coordination is the reasonable basic demand of national society's economical operation.Income increase it is too fast or excessively slowly can all occur it is unfavorable
As a result, too fast will lead to inflation and then unfavorable to economic development；Crossing can then be difficult to push economic development and people's lives slowly
It is horizontal.Therefore the level of economic growth can be used as one of the factor for influencing family income.
The style of economic increase and the family income level of resident, which have, directly to be contacted, and the different styles of economic increase is to family
Front yard income has opposite impacts on degree.Therefore the style of economic increase can be used as one of the factor for influencing family income.
For rural area and city, family income is different, in addition, infrastructure construction, public service and society
The level of coverage of ensure etc. is also different, and therefore, urbanization degree to a certain extent can generate the family income of resident
Certain influence.Therefore urbanization rate can be used as one of the factor for influencing family income.
Income from wage and salary is still the main source of family income, therefore the height of unemployment rate can also generate family income
It is corresponding to influence.Therefore unemployment rate can be used as one of the factor for influencing family income.
In addition to the level of economic growth, the style of economic increase, urbanization rate and unemployment rate as influence family income because
Plain outer, education, household member age, kinsfolk's quantity, kinsfolk's health status and inflation etc. can also be used as shadow
Ring the factor of family income.
After determining the factor for influencing family income, step 103 is continued to execute.
Step 103, the factor for influencing family income is analyzed, determines the target factor for influencing family income.
Optionally, as shown in figure 3, determining that the target factor for influencing family income may comprise steps of in step 103.
Step 3301, the corresponding sample data of factor for influencing family income is standardized, obtains the sample
The corresponding vector of notebook data.
Since the original value unit for influencing the corresponding sample data of each factor of family income is not identical, and the order of magnitude also phase
Difference is larger, for the accuracy that subsequent analysis compares, needs to be standardized each sample data.Optionally, it will acquire first
Sample data be divided into Positive positive sample and Negative negative sample, positive sample refers to that the sample data of income increase is corresponding
Family income survey sample to be analyzed, negative sample, which refers to, takes in the reduced corresponding family income survey sample to be analyzed of sample data
This, by the way that sample data is classified, and then calculates the entropy of different sample datas；Then according to these entropy come judgement sample number
According to corresponding influence family income factor presence or absence to the influence degree of family income, i.e., received when this influences family
The factor entered there are when the trend or downward trend of growth are showed to the influence degree of family income, and work as this
It is which type of trend showed again to the influence degree of family income in the absence of the factor of influence family income.
Step 3302, according to the corresponding vector of the sample data, each factor for influencing family income is calculated
Weight.
Optionally, as shown in figure 4, step 3302 can wrap when calculating the weight of each factor for influencing family income
Include following steps.
Step 3401, according to the corresponding vector of the sample data, the first factor in first sample that calculates accounts for described wait divide
Analyse the specific gravity of family income survey sample.
Optionally, first sample described in this step is any one sample in the family income survey sample to be analyzed
This, first factor is any one factor in the first sample.
Optionally, this step calculates the ratio that the first factor in first sample accounts for the family income survey sample to be analyzed
Weight, can also include: basisIt calculates the first factor in first sample and accounts for the family income tune to be analyzed
Look into the specific gravity of sample, the PijIndicate the specific gravity of the first factor in first sample, the XijIndicate the first factor in first sample
The vector of corresponding sample data.
Step 3402, according to the specific gravity of the first factor in first sample, the comentropy of the first factor in first sample is calculated.
It optionally, can also include: basis when this step calculates the comentropy of the first factor in first sampleCalculate the comentropy of the first factor in first sample, the SijIt indicates first in first sample
The comentropy of factor.In general, comentropy is bigger, and the uncertainty of information is higher, and the value of utility of information is with regard to smaller；Conversely,
Comentropy is smaller, and the uncertainty of information is lower, and the value of utility of information is bigger.
Step 3403, according to the comentropy of the first factor in first sample, the difference of the first factor in first sample is calculated
Property coefficient.
Optionally, when calculating the difference property coefficient of the first factor in first sample in this step, can also include:
According to gij=1-Sij, calculate the difference property coefficient of the first factor in first sample, the gijIt indicates in first sample
The difference property coefficient of first factor.
Step 3404, according to the difference property coefficient of the first factor in first sample, the first factor in first sample is determined
Weight.
Optionally, when this step determines the weight of the first factor in first sample, can also include:
According toDetermine the weight of the first factor in first sample, aijIt indicates in first sample
The weight of first factor.
Step 3405, according to the method for determining the weight of the first factor in first sample, each factor is calculated respectively in institute
State the weight in family income survey sample to be analyzed.
Optionally, this step calculate each factor respectively weight in the family income survey sample to be analyzed when,
It can also include: that the first factor is calculated separately in the family income to be analyzed according to the weight of the first factor in first sample
Weight in investigation sample；Using the sum of weight of first factor in the family income survey sample to be analyzed as
The weight of one factor；According to the method for the weight for first factor that determines, the weight of each factor is calculated.
Step 3303, factor corresponding to weight limit is selected to influence in the weight of each factor of family income as shadow
Ring the target factor of family income.
Optionally, in this step, in order to determine different regions influence family income target factor, can be right respectively
The family income survey sample to be analyzed of different regions is analyzed, and the family income to be analyzed of different regions is found by analysis
In investigation sample, the target factor for influencing family income is also different.
It optionally, can also be by another factor and target after this step determines the target factor for influencing family income
Factor, which is put together, to be analyzed, and whether the addition for detecting another factor can generate big influence, the shadow of generation to family income
Loud occurrence is how many, so that government department be facilitated to propose correct and suitable countermeasure and suggestion for analysis result.To
We also some available factors be for the growth of family income small aspect influence, can be with when doing decision
It does not pay attention to wherein.
Optionally, it when determining the target factor for influencing family income, can also be determined by way of modeling, for example,
Be analysed to the corresponding sample data of family income survey sample and be divided into training data and verify data, by training data and
Re -training in rule input pre-training model, obtains new model, in the new model for then obtaining verify data input,
It can be obtained monitoring result, that is, influence the factor of family income.In addition, family income growth can also be obtained by modeling analysis
The reason of slowly or slightly causing fastly, to these influence factors, we need the strategy taken to be to continue with encouragement still to change
Become, the family income situation for the different home that departments of government can be made to be well understood in recent years.Differentiation to family income
Process and status carry out overall merit, and the comprehensive various theoretical factors to income are screened, and inquiring into influences family per capita
The mechanism of action of income.
The above-mentioned method to family income analysis of Influential Factors, by obtaining family income survey sample；To the family
Income survey sample is handled, and determines the factor for influencing family income；The factor for influencing family income is analyzed,
The target factor for influencing family income is determined, so as to obtain in detail, comprehensively and accurately by analyzing big data
Analysis is as a result, provide targetedly service providing data foundation for government department.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Corresponding to, to the method for family income analysis of Influential Factors, Fig. 5 shows of the invention real described in foregoing embodiments
The exemplary diagram of the device to family income analysis of Influential Factors of example offer is provided.As shown in figure 5, the apparatus may include: it obtains
Module 501, processing module 502 and analysis module 503.
Module 501 is obtained, for obtaining family income survey sample；
Processing module 502, for handling the family income survey sample, determine influence family income because
Element；
Analysis module 503 determines the mesh for influencing family income for analyzing the factor for influencing family income
Mark factor.
Optionally, as shown in fig. 6, the processing module 502, can also include: acquiring unit 601,602 and of sampling unit
Analytical unit 603.
Acquiring unit 601 obtains target household income for screening the family income survey sample according to preset rules
Investigation sample；
Sampling unit 602, for using layering sampling with unequal probability method, to the target household income survey sample into
Line sampling obtains family income survey sample to be analyzed；
Analytical unit 603, for analyzing the family income survey sample to be analyzed, according to each described wait divide
The feature and macro-economy influence of family income survey sample are analysed, determines the factor for influencing family income.
Optionally, it when the analysis module 503 determines the target factor for influencing family income, can be also used for: will be described
The corresponding sample data of factor for influencing family income is standardized, and obtains the corresponding vector of the sample data；According to institute
The corresponding vector of sample data is stated, the weight of each factor for influencing family income is calculated；Selection influences family income
Factor corresponding to weight limit is as the target factor for influencing family income in the weight of each factor.
Optionally, it when the analysis module 503 calculates the weight of each factor for influencing family income, can also use
In: according to the corresponding vector of the sample data, the first factor in first sample that calculates accounts for the family income survey to be analyzed
The specific gravity of sample, the first sample be the family income survey sample to be analyzed in any one sample, described first because
Element is any one factor in the first sample；According to the specific gravity of the first factor in first sample, calculate in first sample
The comentropy of first factor；According to the comentropy of the first factor in first sample, the difference of the first factor in first sample is calculated
Property coefficient；According to the difference property coefficient of the first factor in first sample, the weight of the first factor in first sample is determined；According to true
The method for determining the weight of the first factor in first sample calculates each factor respectively in the family income survey sample to be analyzed
In weight.
Optionally, the analysis module 503 calculates each factor respectively in the family income survey sample to be analyzed
Weight, can be also used for the weight according to the first factor in first sample, calculate separately the first factor in the family to be analyzed
Weight in the income survey sample of front yard；By the sum of weight of first factor in the family income survey sample to be analyzed
Weight as the first factor；According to the method for the weight for first factor that determines, the weight of each factor is calculated.
The above-mentioned device to family income analysis of Influential Factors obtains family income survey sample by obtaining module；Place
Reason module handles the family income survey sample, determines the factor for influencing family income；Analysis module is to the shadow
The factor for ringing family income is analyzed, and the target factor for influencing family income is determined, so as to by carrying out to big data
Analysis is obtained and in detail, is comprehensively and accurately analyzed as a result, providing targetedly service providing data foundation for government department.
Fig. 7 is the schematic diagram for the terminal device that one embodiment of the invention provides.As shown in fig. 7, the terminal of the embodiment is set
Standby 700 include: processor 701, memory 702 and are stored in the memory 702 and can transport on the processor 701
Capable computer program 703, such as the program to family income analysis of Influential Factors.The processor 701 executes the calculating
The step in the above-mentioned embodiment of the method to family income analysis of Influential Factors, such as step shown in FIG. 1 are realized when machine program 703
Rapid 101 to 103 perhaps step 2201 shown in Fig. 2 to step 2203 or step 3301 shown in Fig. 3 to step 3303, or
Person's step 3401 shown in Fig. 4 to step 3405, realize above-mentioned each when executing the computer program 703 by the processor 701
The function of each module in Installation practice, such as the function of module 501 to 503 shown in Fig. 5.
Illustratively, the computer program 703 can be divided into one or more program modules, it is one or
Multiple program modules are stored in the memory 702, and are executed by the processor 701, to complete the present invention.Described one
A or multiple program modules can be the series of computation machine program instruction section that can complete specific function, and the instruction segment is for retouching
State implementation procedure of the computer program 703 in the device or terminal device 700 to family income analysis of Influential Factors.
For example, the computer program 703, which can be divided into, obtains module 501, processing module 502 and analysis module 503, each module
Concrete function is as shown in figure 5, this is no longer going to repeat them.
The terminal device 700 can be the calculating such as desktop PC, notebook, palm PC and cloud server and set
It is standby.The terminal device may include, but be not limited only to, processor 701, memory 702.It will be understood by those skilled in the art that
Fig. 7 is only the example of terminal device 700, does not constitute the restriction to terminal device 700, may include more or more than illustrating
Few component perhaps combines certain components or different components, such as the terminal device can also be set including input and output
Standby, network access equipment, bus etc..
Alleged processor 701 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 702 can be the internal storage unit of the terminal device 700, such as terminal device 700 is hard
Disk or memory.The memory 702 is also possible to the External memory equipment of the terminal device 700, such as the terminal device
The plug-in type hard disk being equipped on 700, intelligent memory card (Smart Media Card, SMC), secure digital (Secure
Digital, SD) card, flash card (Flash Card) etc..Further, the memory 702 can also both include the terminal
The internal storage unit of equipment 700 also includes External memory equipment.The memory 702 for store the computer program with
And other programs and data needed for the terminal device 700.The memory 702 can be also used for temporarily storing defeated
Out or the data that will export.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal device and method, it can be with
It realizes by another way.For example, device described above/terminal device embodiment is only schematical, for example, institute
The division of module or unit is stated, only a kind of logical function partition, there may be another division manner in actual implementation, such as
Multiple units or components can be combined or can be integrated into another system, or some features can be ignored or not executed.Separately
A bit, shown or discussed mutual coupling or direct-coupling or communication connection can be through some interfaces, device
Or the INDIRECT COUPLING or communication connection of unit, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..Computer-readable Jie
Matter may include: can carry the computer program code any entity or device, recording medium, USB flash disk, mobile hard disk,
Magnetic disk, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as does not include electric carrier signal and electricity according to legislation and patent practice, computer-readable medium in certain jurisdictions
Believe signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. the method for a kind of pair of family income analysis of Influential Factors characterized by comprising
Obtain family income survey sample；
The family income survey sample is handled, determines the factor for influencing family income；
The factor for influencing family income is analyzed, determines the target factor for influencing family income.
2. as described in claim 1 to the method for family income analysis of Influential Factors, which is characterized in that described to the family
Income survey sample is handled, and determines the factor for influencing family income, comprising:
The family income survey sample is screened according to preset rules, obtains target household income survey sample；
Using layering sampling with unequal probability method, the target household income survey sample is sampled, family to be analyzed is obtained
Front yard income survey sample；
The family income survey sample to be analyzed is analyzed, according to each family income survey sample to be analyzed
Feature and macro-economy influence determine the factor for influencing family income.
3. as claimed in claim 2 to the method for family income analysis of Influential Factors, which is characterized in that described on the influence
The factor of family income is analyzed, and determines the target factor for influencing family income, comprising:
By it is described influence family income the corresponding sample data of factor be standardized, obtain the sample data it is corresponding to
Amount；
According to the corresponding vector of the sample data, the weight of each factor for influencing family income is calculated；
Factor corresponding to weight limit is selected to influence in the weight of each factor of family income as influence family income
Target factor.
4. as claimed in claim 3 to the method for family income analysis of Influential Factors, which is characterized in that described according to the sample
The corresponding vector of notebook data calculates the weight of each factor for influencing family income, comprising:
According to the corresponding vector of the sample data, the first factor in first sample that calculates accounts for the family income survey to be analyzed
The specific gravity of sample, the first sample be the family income survey sample to be analyzed in any one sample, described first because
Element is any one factor in the first sample；
According to the specific gravity of the first factor in first sample, the comentropy of the first factor in first sample is calculated；
According to the comentropy of the first factor in first sample, the difference property coefficient of the first factor in first sample is calculated；
According to the difference property coefficient of the first factor in first sample, the weight of the first factor in first sample is determined；
According to the method for determining the weight of the first factor in first sample, calculates each factor and received respectively in the family to be analyzed
Enter the weight in investigation sample.
5. as claimed in claim 4 to the method for family income analysis of Influential Factors, which is characterized in that
The corresponding vector of factor of the influence family income according to acquisition, the first factor in first sample that calculates account for institute
State the specific gravity of family income survey sample to be analyzed, comprising:
According toCalculate the ratio that the first factor in first sample accounts for the family income survey sample to be analyzed
Weight, the PijIndicate the specific gravity of the first factor in first sample, the XijIndicate the corresponding sample of the first factor in first sample
The vector of data；
The specific gravity according to the first factor in first sample calculates the comentropy of the first factor in first sample, comprising:
According toCalculate the comentropy of the first factor in first sample, the SijIndicate the first sample
The comentropy of first factor in this；
The comentropy according to the first factor in first sample calculates the difference property coefficient of the first factor in first sample, packet
It includes:
According to gij=1-Sij, calculate the difference property coefficient of the first factor in first sample, the gijIt indicates first in first sample
The difference property coefficient of factor；
The difference property coefficient according to the first factor in first sample, determines the weight of the first factor in first sample, comprising:
According toDetermine the weight of the first factor in first sample, aijIt indicates first in first sample
The weight of factor.
6. as described in claim 4 or 5 to the method for family income analysis of Influential Factors, which is characterized in that described to calculate respectively
A factor weight in the family income survey sample to be analyzed respectively, comprising:
According to the weight of the first factor in first sample, the first factor is calculated separately in the family income survey sample to be analyzed
In weight；
Using the sum of weight of first factor in the family income survey sample to be analyzed as the weight of the first factor；
According to the method for the weight for first factor that determines, the weight of each factor is calculated.
7. the device of a kind of pair of family income analysis of Influential Factors characterized by comprising
Module is obtained, for obtaining family income survey sample；
Processing module determines the factor for influencing family income for handling the family income survey sample；
Analysis module determines the target factor for influencing family income for analyzing the factor for influencing family income.
8. as claimed in claim 7 to the device of family income analysis of Influential Factors, which is characterized in that the processing module,
Include:
Acquiring unit obtains target household income survey sample for screening the family income survey sample according to preset rules
This；
Sampling unit, for being sampled to the target household income survey sample using layering sampling with unequal probability method,
Obtain family income survey sample to be analyzed；
Analytical unit, for analyzing the family income survey sample to be analyzed, according to each family to be analyzed
The feature and macro-economy influence of income survey sample determine the factor for influencing family income.
9. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer program of operation, which is characterized in that the processor realizes such as claim 1 to 6 when executing the computer program
The step of any one the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 6 of realization the method.
Priority Applications (1)
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| CN201910204231.7A CN110070475A (en) | 2019-03-18 | 2019-03-18 | To the method and terminal device of family income analysis of Influential Factors |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910204231.7A CN110070475A (en) | 2019-03-18 | 2019-03-18 | To the method and terminal device of family income analysis of Influential Factors |
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| CN110070475A true CN110070475A (en) | 2019-07-30 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111105266A (en) * | 2019-11-11 | 2020-05-05 | 中国建设银行股份有限公司 | Client grouping method and device based on improved decision tree |
-
2019
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111105266A (en) * | 2019-11-11 | 2020-05-05 | 中国建设银行股份有限公司 | Client grouping method and device based on improved decision tree |
| CN111105266B (en) * | 2019-11-11 | 2023-10-27 | 建信金融科技有限责任公司 | Client grouping method and device based on improved decision tree |
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Application publication date: 20190730 |