CN109544352A - Sampling observation method, apparatus, computer equipment and storage medium based on random number - Google Patents
Sampling observation method, apparatus, computer equipment and storage medium based on random number Download PDFInfo
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Abstract
The sampling observation method based on random number that the invention discloses a kind of, for solving the problems, such as that business datum sampling observation timeliness is low.The method include that obtaining business datum to be inspected by random samples；Generate a target random number at random in preset random number range；Obtain the corresponding default sampling observation probability of the affiliated type of service of the business datum；Hit threshold is calculated according to the default sampling observation probability and the random number range；Judge whether the target random number is greater than the hit threshold；If the target random number is greater than the hit threshold, it is determined that the business datum is not included in quality inspection range；If the target random number is less than or equal to the hit threshold, it is determined that the business datum is included in quality inspection range.The present invention also provides casual inspection device, computer equipment and storage mediums based on random number.
Description
Technical field
The present invention relates to technical field of data processing, more particularly to the sampling observation method, apparatus based on random number, computer are set
Standby and storage medium.
Background technique
Insurance company can often inspect the business datum of insurance products by random samples, carry out quality examination to the business datum inspected by random samples,
Such as the contents such as authenticity, standardized degree of quality inspection personnel verification business datum for submitting to profession, to guarantee insurance sales mistake
The service quality and control risk of journey.
Currently, general to the business datum sampling observation of insurance products by the way of data pool accumulation sampling observation.Such as to life insurance
When the business datum sampling observation of product, in preset data pond the business datum accumulation of life insurance products to 100 when execute sampling observation link,
It brings into quality inspection range from a certain proportion of business datum is randomly selected in the business datum of 100 life insurance products, then holds
Row follow-up process.
However, the mode of this data pool accumulation sampling observation requires to start after business datum accumulation to certain amount grade
It inspects link by random samples, when the business datum deficiency for the insurance products that some period generates, will be unable to open sampling observation link, this is just delayed
The execution of follow-up process, reduces the timeliness to business data processing.
Summary of the invention
The embodiment of the present invention provides a kind of sampling observation method, apparatus, computer equipment and storage medium based on random number, with
Solve the problems, such as that business datum sampling observation timeliness is low.
A kind of sampling observation method based on random number, comprising:
Obtain business datum to be inspected by random samples；
Generate a target random number at random in preset random number range；
Obtain the corresponding default sampling observation probability of the affiliated type of service of the business datum；
Hit threshold is calculated according to the default sampling observation probability and the random number range；
Judge whether the target random number is greater than the hit threshold；
If the target random number is greater than the hit threshold, it is determined that the business datum is not included in quality inspection range；
If the target random number is less than or equal to the hit threshold, it is determined that the business datum is included in quality inspection model
It encloses.
A kind of casual inspection device based on random number, comprising:
Business datum obtains module, for obtaining business datum to be inspected by random samples；
Random number generation module, for generating a target random number at random in preset random number range；
It inspects probability by random samples and obtains module, for obtaining the corresponding default sampling observation probability of the affiliated type of service of the business datum；
Hit threshold computing module, for hit to be calculated according to the default sampling observation probability and the random number range
Threshold value；
Judgment module, for judging whether the target random number is greater than the hit threshold；
Module is included in determination, if the judging result for the judgment module is yes, it is determined that the business datum is not received
Enter quality inspection range；
Module is not included in determination, if the judging result for the judgment module is no, it is determined that the business datum is received
Enter quality inspection range.
A kind of computer equipment, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, the processor realize the above-mentioned sampling observation side based on random number when executing the computer program
The step of method.
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter
Calculation machine program realizes the step of above-mentioned sampling observation method based on random number when being executed by processor.
Above-mentioned sampling observation method, apparatus, computer equipment and storage medium based on random number, firstly, obtaining to be inspected by random samples
Business datum；Then, a target random number is generated at random in preset random number range；Then, the business number is obtained
According to the corresponding default sampling observation probability of affiliated type of service；In addition, according to the default sampling observation probability and the random number range meter
Calculation obtains hit threshold；Judge whether the target random number is greater than the hit threshold；If so, determining the business datum
It is not included in quality inspection range；If not, it is determined that the business datum is included in quality inspection range.It is found that the present invention is without waiting for data pool
Accumulation directly can carry out sampling observation to each business datum and judge that the sampling observation to business datum can be realized, greatly improve industry
The real-time of data of being engaged in sampling observation, the execution for the follow-up process that avoids delay, to improve the timeliness to business data processing.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is an application environment schematic diagram of the sampling observation method in one embodiment of the invention based on random number；
Fig. 2 is a flow chart of the sampling observation method in one embodiment of the invention based on random number；
Fig. 3 is that the sampling observation method in one embodiment of the invention based on random number is preset at random under an application scenarios
The flow diagram of number range；
Fig. 4 is stream of the sampling observation method and step 203 under an application scenarios in one embodiment of the invention based on random number
Journey schematic diagram；
Fig. 5 is stream of the sampling observation method and step 104 under an application scenarios in one embodiment of the invention based on random number
Journey schematic diagram；
Fig. 6 is that the sampling observation method in one embodiment of the invention based on random number is tired out in combined data pond under an application scenarios
The flow diagram of product sampling observation mode；
Fig. 7 is the structural schematic diagram of the casual inspection device in one embodiment of the invention based on random number；
Fig. 8 is a schematic diagram of computer equipment in one embodiment of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Sampling observation method provided by the present application based on random number, can be applicable in the application environment such as Fig. 1, wherein client
End is communicated by network with server.Wherein, which can be, but not limited to various personal computers, notebook electricity
Brain, smart phone, tablet computer and portable wearable device.Server can use the either multiple services of independent server
The server cluster of device composition is realized.
In one embodiment, it as shown in Fig. 2, providing a kind of sampling observation method based on random number, is applied in this way in Fig. 1
In server for be illustrated, include the following steps:
101, business datum to be inspected by random samples is obtained；
In the present embodiment, server can obtain the business datum of generation as business to be inspected by random samples in sampling observation in real time
Data can also set certain trigger condition to the business datum of generation, when trigger condition meets, server property again
Obtain these business datums.In this regard, the present embodiment is not especially limited.
102, a target random number is generated at random in preset random number range；
It is understood that server can preset the number such as a random number range, such as 1-10 or 1-100
It is worth range, generates a random number at random in the random number range as target random number.It illustrates, it is assumed that the random number
Range is 1-10, and server generates a data as target random number at random from ten natural numbers, for example can be generated one
A 7 are used as the target random number.
Further, which can be manually set by administrative staff.But the random number range manually set
Possibly can not be suitable for all service conditions, this requires administrative staff set for different service conditions it is different random
Number range, undoubtedly increases administrative staff's workload.Therefore, in the present embodiment, in order to improve this method to all service conditions
Adaptability, specifically, as shown in figure 3, the random number range can be preset by following steps:
201, type of service belonging to the business datum is determined；
202, the business datum amount for belonging to the type of service in the preset duration nearest apart from present system time is obtained；
203, random number range is set according to the business datum amount.
For step 201, it is to be understood that all business datums have a type of service described in it, and server can be with
Determine type of service belonging to the business datum.For example, in insurance products, the type of service of business datum can be according to
Product type classification, for example serious illness insurance class, family's danger class, life insurance class can be divided into, etc..
For step 202, in the present embodiment, it is contemplated that the business datum of identical services type has more general character, especially
It is to business datum the future may appear the order of magnitude for have direct reference value.For example, in certain insurance company
The quantity of the life insurance product of sale in 1 year is 10,000, then the predicted quantity of insurance company sale in this year life insurance product to its
It is 10,000, this is reasonable.Similarly, server can also set a preset duration, then obtain apart from present system time most
The business datum amount for belonging to the type of service in close preset duration, the business datum amount got in this way will can be used as institute
State reference value of the business datum in the following preset duration.For example, it is assumed that preset duration is one month, then server is available
The business datum amount of the nearest month type of service.
For step 203, after getting the business datum amount, server can be set according to the business datum amount
Random number range.
It further,, generally as far as possible should be with when setting random number range for the ease of the calculating of subsequent sampling observation
The extent length of machine number range is set as 10 integral multiple.But the business datum amount that server is got may have greatly
There is integral multiple that is small, and being not necessarily 10, therefore before setting the random number range, it can also be to the business datum amount
Carry out judgement and processing appropriate.Specifically, as shown in figure 4, step 203 can specifically include:
301, judge whether the business datum amount is greater than preset data-quantity threshold, if so, 302 are thened follow the steps, if
It is no, then follow the steps 303；
302, tens is rounded to the business datum amount, obtains being rounded data volume, later with the rounding data volume
Random number range is set as extent length.
303, random number range is set using the data-quantity threshold as extent length.
For step 301, server can set a data-quantity threshold, which is equivalent to setting random number
Minimum value needed for range is set if the business datum amount is not more than the data-quantity threshold without using the business datum amount
Determine random number range；, whereas if the business datum amount is greater than the data-quantity threshold, then business datum amount setting can be used
Random number range.
For step 302, it can be seen from the above, can make when the business datum amount is greater than preset data-quantity threshold
Random number range is set with the business datum amount, still, it is contemplated that set the extent length of random number range as 10 integral multiple
It is more suitable, in the present embodiment, it is also necessary to tens is rounded to the business datum amount, obtains being rounded data volume, then, with
The rounding data volume sets random number range as extent length.For example, it is assumed that the business datum amount is 55, then evidence obtaining to 10
After digit, 50 are obtained.Then, the random number range that server is set out using 10 as extent length is [1,50].
For step 303, it can be seen from the above, when the business datum amount is less than or equal to preset data-quantity threshold,
It is considered that without using the business datum amount set random number range, server can directly using the data-quantity threshold as
Extent length sets random number range.For example, it is assumed that the business datum amount is 8, which is 10, then server is with 10
The random number range set out as extent length is [1,10].
In view of the characteristic of sampling observation, each random number for needing to guarantee to generate at random as much as possible is preset random at this
Be uniformly distributed in number ranges namely the random number range in the probability that is generated of any two numerical value be equal.For this purpose, this
In embodiment, when server executes above-mentioned steps 102, following Generating Random Number can be used, with random number range [0,1]
For example:
ri=mod (a*ri-1+b,base)
pi=ri/base
In above formula, riFor the median updated every time with recursion, ri-1For the r generated when last generation random numberi,
piFor the target random number that this is generated, a, b and base are constant, are generally rule of thumb arranged, can in the present embodiment
To be set as a=17, b=139, base=256.Wherein, i=1,2,3 ... ...
According to above-mentioned two formula it is found that since the target random number generated every time will receive last generation target random number
When used ri-1Influence, therefore when the random number of generation is enough, it is ensured that in random number range [0,1] with
Machine number is that the probability that equally distributed namely each random number is generated is identical.Particularly, made when generating random number for the first time
R1A constant can be taken, for example 5 can be taken.
Specifically, above-mentioned Generating Random Number can be realized in programming by following c language:
103, the corresponding default sampling observation probability of the affiliated type of service of business datum is obtained；
It should be noted that corresponding sampling observation probability has been set separately for every kind of type of service in server, for example, can be with
The corresponding sampling observation probability of serious illness insurance class is set as 10%, the corresponding sampling observation probability of life insurance class is 20%.Therefore, learn it is described
After the affiliated type of service of business datum, the corresponding default sampling observation of the available affiliated type of service of business datum of server
Probability.
104, hit threshold is calculated according to the default sampling observation probability and the random number range；
After getting the default sampling observation probability and the random number range, server can be according to the default pumping
Hit threshold is calculated in inspection probability and the random number range.It is understood that the hit threshold is for judging to generate
The standard whether hit of target random number, and target random number is hit whether, directly determines whether the business datum is brought into
Quality inspection range.
For ease of understanding, as shown in figure 5, further, step 104 can specifically include:
401, the lower limit value and upper limit value of the random number range are obtained；
402, the extent length of the random number range is calculated according to the lower limit value and upper limit value；
403, the product for calculating default the sampling observation probability and the extent length being calculated, obtains hit numberical range
Length；
404, hit threshold is calculated according to the lower limit value and the hit numerical value extent length.
For step 401, server is after obtaining the random number range, its available lower limit value and upper limit value.For example,
Assuming that the random number range is [1,10], then lower limit value is 1, upper limit value 10.
For step 402, after getting the lower limit value and upper limit value, server can according to the lower limit value and
Upper limit value calculates the extent length of the random number range.The example above is accepted, lower limit value 1, upper limit value 10, then this is random
The extent length of number range is equal to 10-1+1=10.
For step 403, it is assumed that the default sampling observation probability is 20%, then when extent length is 10, the hit numerical value
Extent length is equal to 10*20%=2.It is found that in random number range [1,10], what the target random number that server generates was hit
Range is 2, and this represent the probability hit in the random number range in random number.
For step 404, after obtaining the lower limit value and the hit numerical value extent length, server can basis
Hit threshold is calculated in the lower limit value and the hit numerical value extent length.Specifically, the example above, the hit threshold are accepted
Value is equal to 1+2-1=2, i.e. hit threshold is 2.It is found that the hit threshold is whether target random number orders in random number range
In standard, which, which is equivalent to, is divided into two ranges for random number range, respectively [1,2] and (2,10], work as mesh
When mark random number is dropped into [1,2] range, target number hit at any time is represented；Conversely, when target random number drops into (2,
When 10] in range, representing the target, number is not hit at any time.
105, judge whether the target random number is greater than the hit threshold, if so, 106 are thened follow the steps, if it is not, then
Execute step 107；
106, determine that the business datum is not included in quality inspection range；
107, determine that the business datum is included in quality inspection range.
For above-mentioned steps 105-107, as shown in the above, when the target random number be greater than the hit threshold,
It represents the target random number not hit, then server can determine that the business datum is not included in quality inspection range；Conversely, working as
It when the target random number is less than or equal to the hit threshold, represents the target random number and hits, then server can be with
Determine that the business datum is included in quality inspection range.
Further, in order to expand the practicability of this method, this method can be combined with existing data pool accumulation sampling observation
Mode sampling observation processing is carried out to business datum, when the accumulation duration of business datum is too long and the order of magnitude of not up to data pool is wanted
When asking, the step 101-107 that this method provides is executed；Conversely, business datum is then continued to build up into data pool, until accumulation
Business datum meets the order of magnitude requirement of data pool and then carries out sampling observation processing.As it can be seen that in the side of combined data pond accumulation sampling observation
After formula, the timeliness of business data processing not only ensure that, but also improve the scope of application to business datum sampling observation.Specifically
Ground, as shown in fig. 6, before step 101, this method further include:
501, after detecting that goal systems generates new business data, the new business data are stored to being used to store
The data pool of business datum to be inspected by random samples；
502, judge whether the data volume for the business datum to be inspected by random samples accumulated in the data pool has reached preset threshold,
If so, 503 are thened follow the steps, if it is not, thening follow the steps 504；
503, the business datum to be inspected by random samples in the data pool is inspected by random samples by the way of data pool accumulation sampling observation；
504, whether the duration for judging this accumulation of the data pool is more than preset duration threshold value, if so, executing step
Rapid 101, it is accumulated in data pool if it is not, then continuing waiting for the business datum to be inspected by random samples, the duration of this accumulation refers to
The duration of the storage time apart from present system time wait inspect oldest stored in business datum to the data pool by random samples.
It, can will be described firstly, server is after detecting that goal systems generates new business data for step 501
New business data are stored to the data pool for storing business datum to be inspected by random samples.Wherein, the goal systems can be the service
System on device, the system being also possible on other servers or terminal device, is not construed as limiting herein.
For step 502 and step 503, server may determine that the business datum to be inspected by random samples accumulated in the data pool
Data volume whether have reached preset threshold, when the data volume for the business datum to be inspected by random samples accumulated in the data pool has reached
When preset threshold, illustrate that the data volume of business datum to be inspected by random samples is carried out at sampling observation by the way of data pool accumulation sampling observation enough
Reason, therefore server can take out the business datum to be inspected by random samples in the data pool in such a way that data pool accumulates sampling observation
Inspection.
For step 504, when the not up to default threshold of the data volume for the business datum to be inspected by random samples accumulated in the data pool
When value, illustrate that the data volume of the business datum to be inspected by random samples is also not enough to carry out at sampling observation in such a way that data pool accumulates sampling observation
Reason, being somebody's turn to do business datum to be inspected by random samples at this time there is a possibility that two kinds, the first may be that the business datum to be inspected by random samples also needs to add up
A period of time can reach the order of magnitude of data pool requirement, and second when may be that this has added up very long wait inspect business datum by random samples
Between but still be not up to data pool require the order of magnitude.For this purpose, server also need to judge the data pool this accumulation when
Whether long be more than preset duration threshold value, wherein the duration of this accumulation refers to described wait inspect oldest stored in business datum by random samples
Extremely duration of the storage time of the data pool apart from present system time.
When the data pool, this duration accumulated is more than preset duration threshold value, then explanation should business datum be inspected by random samples
Belong to above-mentioned second possible situation, therefore it is not suitable for carrying out sampling observation processing in such a way that data pool accumulates sampling observation, it can
To execute above-mentioned steps 101, handled by way of the forms data sampling observation that this method provides.
It should be noted that if the duration of this accumulation of the data pool is less than preset duration threshold value, then explanation should
Business datum to be inspected by random samples belongs to the first above-mentioned possible situation, can continue waiting for the business datum to be inspected by random samples at this time in data
It is accumulated in pond, temporarily without handling these business datums to be inspected by random samples.
As shown in the above, this method removes the radix inspected by random samples in the mode of traditional data pool accumulation sampling observation, nothing
Business datum accumulation in data pool is needed to wait for be instead based on single business datum to certain amount grade and carry out random number probability pumping
Inspection, by probability theory it is found that single business datum was inspected by random samples when being inspected by random samples according to preset sampling observation probability by random number
Possibility, with high-volume business datum according to preset sampling observation probability sampling observation after inspected by random samples to a possibility that it is identical.Therefore, our
Method overcomes the defect of the mode of traditional data pool accumulation sampling observation, limits when can release sampling observation the order of magnitude of business datum
System, can carry out sampling observation processing after generating a business datum, improve the timeliness of business data processing.
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.
In one embodiment, a kind of casual inspection device based on random number is provided, should casual inspection device based on random number with it is upper
The sampling observation method in embodiment based on random number is stated to correspond.As shown in fig. 7, being somebody's turn to do the casual inspection device based on random number includes industry
Be engaged in data acquisition module 601, random number generation module 602, sampling observation probability obtain module 603, hit threshold computing module 604,
Judgment module 605 determines that being included in module 606 and determination is not included in module 607.Detailed description are as follows for each functional module:
Business datum obtains module 601, for obtaining business datum to be inspected by random samples；
Random number generation module 602, for generating a target random number at random in preset random number range；
It inspects probability by random samples and obtains module 603, it is general for obtaining the corresponding default sampling observation of the affiliated type of service of the business datum
Rate；
Hit threshold computing module 604, for being calculated according to the default sampling observation probability and the random number range
Hit threshold；
Judgment module 605, for judging whether the target random number is greater than the hit threshold；
Module 606 is included in determination, if the judging result for the judgment module is yes, it is determined that the business datum is not
It is included in quality inspection range；
Module 607 is not included in determination, if the judging result for the judgment module is no, it is determined that the business datum
It is included in quality inspection range.
Further, the random number range can be by being preset with lower module:
Type of service determining module, for determining type of service belonging to the business datum；
Data volume obtains module, belongs to the service class for obtaining in the preset duration nearest apart from present system time
The business datum amount of type；
Range setting module, for setting random number range according to the business datum amount.
Further, the range setting module may include:
Data volume judging unit, for judging whether the business datum amount is greater than preset data-quantity threshold；
First setup unit, if the judging result for the data volume judging unit be it is yes, to the business datum
Amount is rounded to tens, obtains being rounded data volume, sets random number range using the rounding data volume as extent length later.
Second setup unit, if the judging result for the data volume judging unit be it is no, with the data volume threshold
Value sets random number range as extent length.
Further, the hit threshold computing module may include:
Bound acquiring unit, for obtaining the lower limit value and upper limit value of the random number range；
Extent length computing unit, the range for calculating the random number range according to the lower limit value and upper limit value are long
Degree；
Hit length computation unit, for calculate the default sampling observation probability and the extent length that is calculated it
Product obtains hit numerical value extent length；
Hit threshold computing unit, for hit to be calculated according to the lower limit value and the hit numerical value extent length
Threshold value.
Further, the casual inspection device based on random number can also include:
Data memory module, for detect goal systems generate new business data after, by the new business data
It stores to the data pool for storing business datum to be inspected by random samples；
Accumulative sampling observation module, if the data volume of the business datum to be inspected by random samples for having been accumulated in the data pool have reached it is pre-
If threshold value, then the business datum to be inspected by random samples in the data pool is inspected by random samples by the way of data pool accumulation sampling observation；
Time duration judgment module, if the data volume of the business datum to be inspected by random samples for having accumulated in the data pool does not reach
To preset threshold, then judge whether the duration of this accumulation of the data pool is more than preset duration threshold value, this described accumulation
Duration refer to the storage time wait inspect oldest stored in business datum to the data pool by random samples apart from present system time
Duration；
Trigger module, if the judging result for the time duration judgment module be it is yes, trigger the business datum
Obtain module.
Specific restriction about the casual inspection device based on random number may refer to above for the sampling observation based on random number
The restriction of method, details are not described herein.Modules in the above-mentioned casual inspection device based on random number can be fully or partially through
Software, hardware and combinations thereof are realized.Above-mentioned each module can be embedded in the form of hardware or independently of the place in computer equipment
It manages in device, can also be stored in a software form in the memory in computer equipment, in order to which processor calls execution or more
The corresponding operation of modules.
In one embodiment, a kind of computer equipment is provided, which can be server, internal junction
Composition can be as shown in Figure 8.The computer equipment include by system bus connect processor, memory, network interface and
Database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory packet of the computer equipment
Include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system, computer program and data
Library.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
The database of machine equipment is for storing the data being related in the sampling observation method based on random number.The network of the computer equipment connects
Mouth with external terminal by network connection for being communicated.When the computer program is executed by processor with realize it is a kind of based on
The sampling observation method of machine number.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, processor are realized in above-described embodiment when executing computer program based on random
The step of several sampling observation methods, such as step 101 shown in Fig. 2 is to step 107.Alternatively, when processor executes computer program
Realize above-described embodiment in the casual inspection device based on random number each module/unit function, such as module 601 shown in Fig. 7 to
The function of module 607.To avoid repeating, which is not described herein again.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program realizes the step of sampling observation method in above-described embodiment based on random number when being executed by processor, such as shown in Fig. 2
Step 101 is to step 107.Alternatively, realizing the pumping in above-described embodiment based on random number when computer program is executed by processor
The function of each module/unit of checking device, such as module 601 shown in Fig. 7 is to the function of module 607.To avoid repeating, here not
It repeats again.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
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.
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. a kind of sampling observation method based on random number characterized by comprising
Obtain business datum to be inspected by random samples；
Generate a target random number at random in preset random number range；
Obtain the corresponding default sampling observation probability of the affiliated type of service of the business datum；
Hit threshold is calculated according to the default sampling observation probability and the random number range；
Judge whether the target random number is greater than the hit threshold；
If the target random number is greater than the hit threshold, it is determined that the business datum is not included in quality inspection range；
If the target random number is less than or equal to the hit threshold, it is determined that the business datum is included in quality inspection range.
2. the sampling observation method according to claim 1 based on random number, which is characterized in that the random number range by with
Lower step is preset:
Determine type of service belonging to the business datum；
Obtain the business datum amount for belonging to the type of service in the preset duration nearest apart from present system time；
Random number range is set according to the business datum amount.
3. the sampling observation method according to claim 2 based on random number, which is characterized in that described according to the business datum
Amount sets random number range
Judge whether the business datum amount is greater than preset data-quantity threshold；
If the business datum amount is greater than preset data-quantity threshold, tens is rounded to the business datum amount, is obtained
It is rounded data volume, sets random number range using the rounding data volume as extent length later；
If the business datum amount is less than or equal to preset data-quantity threshold, using the data-quantity threshold as extent length
Set random number range.
4. the sampling observation method according to claim 1 based on random number, which is characterized in that described according to the default sampling observation
Probability and the random number range are calculated hit threshold and include:
Obtain the lower limit value and upper limit value of the random number range；
The extent length of the random number range is calculated according to the lower limit value and upper limit value；
The product for calculating default the sampling observation probability and the extent length being calculated, obtains hit numerical value extent length；
Hit threshold is calculated according to the lower limit value and the hit numerical value extent length.
5. the sampling observation method according to any one of claim 1 to 4 based on random number, which is characterized in that obtain to
Before the business datum of sampling observation, further includes:
After detecting that goal systems generates new business data, the new business data are stored to being used to store industry to be inspected by random samples
The data pool for data of being engaged in；
It is tired using data pool if the data volume for the business datum to be inspected by random samples accumulated in the data pool has reached preset threshold
The mode of product sampling observation inspects the business datum to be inspected by random samples in the data pool by random samples；
If the data volume for the business datum to be inspected by random samples accumulated in the data pool is not up to preset threshold, the data are judged
Whether the duration of this accumulation of pond is more than preset duration threshold value, and the duration of this accumulation refers to the business number to be inspected by random samples
Duration according to the storage time of middle oldest stored to the data pool apart from present system time；
If duration of this accumulation of the data pool is more than preset duration threshold value, executes and described obtain business number to be inspected by random samples
According to the step of.
6. a kind of casual inspection device based on random number characterized by comprising
Business datum obtains module, for obtaining business datum to be inspected by random samples；
Random number generation module, for generating a target random number at random in preset random number range；
It inspects probability by random samples and obtains module, for obtaining the corresponding default sampling observation probability of the affiliated type of service of the business datum；
Hit threshold computing module, for hit threshold to be calculated according to the default sampling observation probability and the random number range
Value；
Judgment module, for judging whether the target random number is greater than the hit threshold；
Module is included in determination, if the judging result for the judgment module is yes, it is determined that the business datum is not included in matter
Examine range；
Module is not included in determination, if the judging result for the judgment module is no, it is determined that the business datum is included in matter
Examine range.
7. the casual inspection device according to claim 6 based on random number, which is characterized in that the random number range by with
Lower module is preset:
Type of service determining module, for determining type of service belonging to the business datum；
Data volume obtains module, belongs to the type of service for obtaining in the preset duration nearest apart from present system time
Business datum amount；
Range setting module, for setting random number range according to the business datum amount.
8. the casual inspection device according to claim 7 based on random number, which is characterized in that the range setting module packet
It includes:
Data volume judging unit, for judging whether the business datum amount is greater than preset data-quantity threshold；
First setup unit, if the judging result for the data volume judging unit be it is yes, to the business datum measure
It is whole to arrive tens, it obtains being rounded data volume, sets random number range using the rounding data volume as extent length later；
Second setup unit, if the judging result for the data volume judging unit be it is no, with the data-quantity threshold work
Random number range is set for extent length.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
The step of sampling observation method described in any one of 5 based on random number.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In realization is as described in any one of claims 1 to 5 based on the sampling observation of random number when the computer program is executed by processor
The step of method.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811208295.6A CN109544352A (en) | 2018-10-17 | 2018-10-17 | Sampling observation method, apparatus, computer equipment and storage medium based on random number |
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| CN201811208295.6A CN109544352A (en) | 2018-10-17 | 2018-10-17 | Sampling observation method, apparatus, computer equipment and storage medium based on random number |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111221707A (en) * | 2020-01-17 | 2020-06-02 | 中体彩科技发展有限公司 | Method and system for monitoring body color random number generator |
| CN111507869A (en) * | 2020-03-10 | 2020-08-07 | 文思海辉智科科技有限公司 | Translation quality inspection extraction method and device, computer equipment and storage medium |
| CN113672763A (en) * | 2021-07-30 | 2021-11-19 | 北京奇艺世纪科技有限公司 | Video data extraction method and device, electronic equipment and storage medium |
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2018
- 2018-10-17 CN CN201811208295.6A patent/CN109544352A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111221707A (en) * | 2020-01-17 | 2020-06-02 | 中体彩科技发展有限公司 | Method and system for monitoring body color random number generator |
| CN111221707B (en) * | 2020-01-17 | 2024-03-26 | 中体彩科技发展有限公司 | Method and system for monitoring physical color random number generator |
| CN111507869A (en) * | 2020-03-10 | 2020-08-07 | 文思海辉智科科技有限公司 | Translation quality inspection extraction method and device, computer equipment and storage medium |
| CN113672763A (en) * | 2021-07-30 | 2021-11-19 | 北京奇艺世纪科技有限公司 | Video data extraction method and device, electronic equipment and storage medium |
| CN113672763B (en) * | 2021-07-30 | 2023-10-10 | 北京奇艺世纪科技有限公司 | Video data extraction method and device, electronic equipment and storage medium |
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