CN110765414B - Performance index data evaluation method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a performance index data evaluation method, a device, equipment and a storage medium. Wherein the method comprises the following steps: acquiring a set number of sample data, the set number of sample data corresponding to a first product property; determining sample average values corresponding to the set number of sample data; determining sample variances corresponding to the set number of sample data; determining a value corresponding to the T distribution based on the numerical value of the set number and the probability set value; and determining a confidence interval corresponding to the first product performance based on the sample mean, the sample variance and the value corresponding to the T distribution, wherein the probability set value characterizes the confidence of the confidence interval. Whether the performance index data of the first product performance is valid or not can be judged scientifically and reasonably according to the confidence interval.
Description
Technical Field
The present invention relates to the field of performance evaluation, and in particular, to a performance index data evaluation method, apparatus, device, and storage medium.
Background
The performance index data of the product is often affected by a number of factors. For example, performance index data of a storage product is often affected by factors such as a testing tool and a testing environment, and even performance index data tested by the same tester using the same testing environment are different. In the related art, there is no scientific and effective determination method for performance index data of a product, and still remains in a stage of subjective determination, so that a scientific and effective performance index data evaluation method for a product needs to be designed, so that the performance index data is as close to the actual performance of the product as possible.
Disclosure of Invention
In view of this, the embodiments of the present invention provide a performance index data evaluation method, apparatus, device, and storage medium, which aim to improve the effectiveness of performance index data evaluation of a product.
The technical scheme of the embodiment of the invention is realized as follows:
the embodiment of the invention provides a performance index data evaluation method, which comprises the following steps:
acquiring a set number of sample data, the set number of sample data corresponding to a first product property;
determining sample average values corresponding to the set number of sample data;
determining sample variances corresponding to the set number of sample data;
determining a value corresponding to the T distribution based on the numerical value of the set number and the probability set value; the probability set value characterizes the confidence coefficient corresponding to the confidence interval;
determining a confidence interval corresponding to the first product performance based on the sample mean, the sample variance, and the value corresponding to the T distribution; wherein the probability set point characterizes the confidence of the confidence interval.
The embodiment of the invention also provides a performance index data evaluation device, which comprises:
the acquisition module is used for acquiring a set number of sample data, and the set number of sample data corresponds to the first product performance;
the first determining module is used for determining sample average values corresponding to the set number of sample data;
the second determining module is used for determining sample variances corresponding to the set number of sample data;
the table look-up module is used for determining a value corresponding to the T distribution based on the numerical value of the set quantity and the probability set value;
a third determining module, configured to determine a confidence interval corresponding to the first product performance based on the sample mean, the sample variance, and a value corresponding to the T distribution;
wherein the probability set point characterizes the confidence of the confidence interval.
The embodiment of the invention also provides performance index data evaluation equipment, which comprises the following steps: a processor and a memory for storing a computer program capable of running on the processor, wherein,
the processor is configured to execute the steps of the method according to the embodiment of the present invention when running the computer program.
The embodiment of the invention also provides a storage medium, and the storage medium stores a computer program which realizes the steps of the method of the embodiment of the invention when being executed by a processor.
According to the technical scheme provided by the embodiment of the invention, the set number of sample data corresponding to the first product performance is obtained, the confidence interval corresponding to the first product performance is determined based on the sample mean value, the sample variance and the value corresponding to the T distribution corresponding to the set number of sample data, and the confidence interval is the distribution interval of the first product performance under the corresponding probability set value, so that whether the performance index data of the first product performance is effective or not can be judged scientifically and reasonably according to the confidence interval.
Drawings
FIG. 1 is a flow chart of a performance index data evaluation method according to an embodiment of the present invention;
FIG. 2 is a flowchart of a performance level data evaluation method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a performance index data evaluation device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a performance index data evaluation apparatus according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
Before describing embodiments of the present invention in further detail, the terms and terminology involved in the embodiments of the present invention will be described, and the terms and terminology involved in the embodiments of the present invention are suitable for the following explanation:
central limit theorem: in nature and production, some phenomena are affected by a number of random factors independent of each other, and if the effect of each factor is very small, the total effect can be regarded as obeying normal distribution.
The big number theorem: in a large number of repeated occurrences of random events, almost certain rules are often presented, which are the big number theorem. In colloquial terms, this theorem is that the trial is repeated a number of times under the condition that the trial is unchanged, the frequency of the random event approximating its probability.
Normal distribution: if the random variable X obeys a mathematical expectation of μ and variance of σ 2 Is expressed as N (mu, sigma) 2 ). The expected value μ determines the position of the center point of the normal distribution, and the standard deviation σ determines the distribution amplitude of the normal distribution. The normal distribution when μ=0, σ=1 is a standard normal distribution.
T distribution (T-distribution): in probability theory and statistics, the T-distribution is used to estimate the mean of the population in normal distribution and unknown variance from small samples.
Unbiased estimation: unbiased estimation is an unbiased inference when sample statistics are used to estimate overall parameters. The mathematical expectation of an estimated quantity is equal to the true value of the estimated parameter, and the estimated quantity is called an unbiased estimate of the estimated parameter, i.e. with unbiasedness, which is a criterion for evaluating the superiority of the estimated quantity.
Confidence interval (Confidence interval): the confidence interval refers to an estimated interval of the overall parameter constructed from the sample statistics. In statistics, the confidence interval of a probability sample is an estimate of the distribution interval of some overall parameter of the sample. The confidence interval shows that the true value of the parameter falls in the distribution interval with a certain probability, and the distribution interval corresponds to the set probability of the measured value of the measured parameter, wherein the set probability is the confidence of the confidence interval.
In the related art, a scientific and effective judging method for the performance index data of the product is not available, and the subjective judging stage is remained, namely whether the performance index data corresponding to the product test is effective or not cannot be judged effectively. Based on this, in various embodiments of the present invention, according to the obtained set number of sample data, a confidence interval of the performance index data of the product is determined, where the confidence interval is a distribution interval of the product performance under the corresponding probability set value, so that whether the performance index data of the product performance is valid can be scientifically and reasonably judged according to the confidence interval.
As shown in fig. 1, an embodiment of the present invention provides a performance index data evaluation method, which includes:
step 101, a set number of sample data is obtained, the set number of sample data corresponding to a first product property.
In the embodiment of the present invention, the first product performance may be a specific performance of a product, for example, an energy consumption parameter of an air conditioner, a storage capacity of a storage product, a data transmission speed of the storage product, and the like, which are not limited herein.
Here, the sample data corresponding set number n may be determined based on the big theorem for the first product performance. Theoretically, the larger the value of n is, the more the overall characteristics (namely, the corresponding rules) of the performance index data can be reflected.
In an embodiment, a set number n of sample data corresponding to a first product property is obtained, where a test condition corresponding to the set number n of sample data is within a fluctuation range allowed by the first product property. If the test condition includes a plurality of external influence factors, a repeated test experiment can be performed within an error fluctuation range of the plurality of external influence factors, to obtain n sample data x1, x2. In this way, the obtained n sample data can objectively reflect the objective distribution rule of the first product performance within the test error range.
Step 102, determining a sample mean value corresponding to the set number of sample data.
And determining a corresponding sample mean value according to the obtained n sample data x1, x2. Specifically, the values of the n sample data are summed and divided by a set number n to obtain a corresponding sample mean value
According to the central limit theorem and the large number theorem, there are a plurality of random variables in objective practice, which are influenced by a plurality of mutually independent random factors, and each factor plays a very small role in the total influence, and the random variables tend to be approximately subjected to normal distribution, that is, when the samples are enough, the average value of the samples isApproximately obeys a normal distribution, i.e. +.>Obeys N (mu, sigma) 2 /n)。
Step 103, determining the sample variance corresponding to the set number of sample data.
Here, the sample variance σ corresponding to the sample data may be determined from the standard deviation S corresponding to the sample data 2 . The standard deviation S is the square root of the arithmetic mean of the standard value of each unit of the population and the square of the mean value from the mean deviation, and reflects the degree of inter-individual dispersion in the sample values of the performance index data, and the total sigma of the performance index data is unknown 2 In consideration of S 2 Is sigma 2 The confidence interval for μ can be found by S instead of σ.
In the embodiment of the invention, the determining step of S is as follows: for n sample data, respectively and sample mean valueThe n average differences are obtained by subtraction, the squares of the average differences are summed and averaged to obtain an average value, and the square root of the average value is obtained to obtain S, which reflects the degree of dispersion among individuals in the performance index data sample value.
And 104, determining a value corresponding to the T distribution based on the numerical value of the set number and the probability set value.
In the embodiment of the invention, the probability set value characterizes the confidence coefficient corresponding to the confidence interval, and the probability set value can be reasonably selected according to the confidence probability (namely the confidence coefficient) required by the product performance in practical application. A probability set point α may be set, where α represents the confidence level corresponding to the confidence interval, i.e., the user believes the accuracy of the performance index data with the probability of α.
In an embodiment, the determining the value corresponding to the T distribution based on the numerical value of the set number and a preset probability set value includes:
determining a corresponding degree of freedom of the T-profile based on the set number of values;
determining a corresponding confidence level of the T distribution based on the probability set point;
corresponding values of the T-profile are determined based on the degrees of freedom and the confidence.
In an application example, a value corresponding to the T distribution is determined based on a lookup table of the T distribution. Assuming a is 0.95, the confidence interval can be considered to have a 95% probability of being trustworthy, i.e., if the measured set of performance metric data values are within the confidence interval, the 95% probability is considered to be accurate. Determining confidence coefficient of 0.475 corresponding to the lookup table of T distribution according to alpha of 0.95, determining degree of freedom of n-1 corresponding to the lookup table of T distribution according to a preset number n, substituting 0.475 and n-1 into the lookup table of T distribution to obtain corresponding lookup value
Step 105, determining a confidence interval corresponding to the first product performance based on the sample mean, the sample variance and the value corresponding to the T distribution.
In the embodiment of the invention, the confidence interval is determined based on the sample mean, the sample variance, the value corresponding to the T distribution and a set operation formula.
In one embodiment, the confidence interval determined by the operational formula is as follows:
wherein,for the sample mean->And S is the standard deviation corresponding to the sample data, and n is the preset number corresponding to the sample data.
According to the method, the set number of sample data corresponding to the first product performance is obtained, the confidence interval corresponding to the first product performance is determined based on the sample mean value, the sample variance and the value corresponding to the T distribution corresponding to the set number of sample data, and the confidence interval is the distribution interval of the first product performance under the corresponding probability set value, so that whether the performance index data of the first product performance is effective or not can be judged scientifically and reasonably according to the confidence interval.
As shown in fig. 2, in an application embodiment, the performance index data evaluation method includes the following steps:
obtaining a sample value;
calculating a sample mean value;
calculating a sample variance;
setting confidence;
querying a T distribution table;
the formula calculates the confidence interval.
The obtaining of the sample value may refer to the step 101, the calculating of the sample mean may refer to the step 102, the calculating of the sample variance may refer to the step 103, the setting of the confidence and the querying of the T distribution table may refer to the step 104, the calculating of the confidence interval by the formula may refer to the step 105, and the description thereof will be omitted.
In an embodiment, the method further comprises:
and determining whether the sample data corresponding to the newly tested first product performance is valid or not based on the confidence interval corresponding to the first product performance.
In the embodiment of the present invention, the determining whether the sample data corresponding to the first product performance of the new test is valid based on the confidence interval corresponding to the first product performance includes:
acquiring sample data corresponding to the newly tested first product performance;
if the value of the sample data newly tested falls into the confidence interval, determining that the sample data newly tested is valid;
and if the numerical value of the sample data of the new test does not fall into the confidence interval, determining that the sample data of the new test is invalid.
For example, the confidence interval [ a, b ] under the probability set value α determined by the method in the embodiment of the present invention represents that the actually measured performance index data falls into the confidence interval with the probability of α, and if the measured data is not within the confidence interval [ a, b ], it may be determined that the measured data is invalid and not adopted. If the measured data is within the confidence interval a, b, it can be determined that the measured data is true at the probability of α, which can be adopted. Therefore, the method provided by the embodiment of the invention provides a credibility method for evaluating the performance index data, and has certain guiding significance for related personnel such as test, development, technical service, market, users and the like.
In order to implement the method of the embodiment of the present invention, the embodiment of the present invention further provides a performance index data evaluation device, as shown in fig. 3, where the device includes:
an obtaining module 301, configured to obtain a set number of sample data, where the set number of sample data corresponds to a first product performance;
a first determining module 302, configured to determine a sample mean value corresponding to the set number of sample data;
a second determining module 303, configured to determine a sample variance corresponding to the set number of sample data;
a table look-up module 304, configured to determine a value corresponding to the T distribution based on the numerical value of the set number and the probability set value;
a third determining module 305 is configured to determine a confidence interval corresponding to the first product performance based on the sample mean, the sample variance, and the value corresponding to the T distribution.
In some embodiments, the obtaining module 301 is specifically configured to:
and acquiring the set number of sample data within a fluctuation range allowed by the test condition of the first product performance.
In some embodiments, the lookup module 304 is specifically configured to:
determining the degree of freedom corresponding to the T distribution based on the numerical value of the set number;
determining the confidence corresponding to the T distribution based on the probability set value;
and determining a value corresponding to the T distribution based on the degree of freedom and the confidence.
In some embodiments, the third determining module 305 is specifically configured to:
and respectively determining the maximum value and the minimum value of the confidence interval based on the sample mean value, the sample variance and the value corresponding to the T distribution.
In some embodiments, the apparatus further comprises:
a fourth determining module 306, configured to determine whether the sample data corresponding to the first product performance that is newly tested is valid based on the confidence interval corresponding to the first product performance.
In some embodiments, the fourth determination module 306 is specifically configured to:
acquiring sample data corresponding to the newly tested first product performance;
if the value of the sample data of the new test falls into the confidence interval, determining that the sample data of the new test is valid;
and if the numerical value of the sample data of the new test does not fall into the confidence interval, determining that the sample data of the new test is invalid.
In practical application, the acquiring module 301, the first determining module 302, the second determining module 303, the look-up table module 304, the third determining module 305 and the fourth determining module 306 may be implemented by a processor in the performance index data evaluating device. Of course, the processor needs to run a computer program in memory to implement its functions.
It should be noted that: in the performance index data evaluation device provided in the above embodiment, only the division of each program module is used for illustration when performing performance index data evaluation, and in practical application, the process allocation may be performed by different program modules according to needs, that is, the internal structure of the device is divided into different program modules, so as to complete all or part of the processes described above. In addition, the performance index data evaluation device and the performance index data evaluation method provided in the foregoing embodiments belong to the same concept, and detailed implementation processes of the performance index data evaluation device and the performance index data evaluation method are detailed in the method embodiments and are not repeated here.
Based on the hardware implementation of the program modules, and in order to implement the method of the embodiment of the present invention, the embodiment of the present invention further provides a performance index data evaluation device. Fig. 4 shows only an exemplary structure of the apparatus, not all the structure, and some or all of the structures shown in fig. 4 may be implemented as needed.
As shown in fig. 4, the performance index data evaluation apparatus 400 provided by the embodiment of the present invention includes: at least one processor 401, a memory 402, a user interface 403 and at least one network interface 404. The various components in the performance level data evaluation device 400 are coupled together by a bus system 405. It is understood that the bus system 405 is used to enable connected communications between these components. The bus system 305 includes a power bus, a control bus, and a status signal bus in addition to the data bus. But for clarity of illustration the various buses are labeled as bus system 405 in fig. 4.
The user interface 403 may include, among other things, a display, keyboard, mouse, trackball, click wheel, keys, buttons, touch pad, or touch screen, etc.
The memory 402 in embodiments of the present invention is used to store various types of data to support the operation of the performance index data assessment device. Examples of such data include: any computer program for operating on a performance index data evaluation device.
The performance index data evaluation method disclosed by the embodiment of the invention can be applied to the processor 401 or realized by the processor 401. The processor 401 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the performance index data evaluation method may be performed by integrated logic circuits of hardware in the processor 401 or instructions in the form of software. The processor 401 described above may be a general purpose processor, a digital signal processor (DSP, digital Signal Processor), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 401 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiment of the invention can be directly embodied in the hardware of the decoding processor or can be implemented by combining hardware and software modules in the decoding processor. The software module may be located in a storage medium, where the storage medium is located in the memory 402, and the processor 401 reads information in the memory 402, and in combination with its hardware, performs the steps of the performance index data evaluation method provided by the embodiment of the present invention.
In an exemplary embodiment, the performance index data evaluation device may be implemented by one or more application specific integrated circuits (ASIC, application Specific Integrated Circuit), DSPs, programmable logic devices (PLD, programmable Logic Device), complex programmable logic devices (CPLD, complex Programmable Logic Device), FPGAs, general purpose processors, controllers, microcontrollers (MCU, micro Controller Unit), microprocessors (Microprocessor), or other electronic elements for performing the aforementioned methods.
It is to be appreciated that memory 402 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Wherein the nonvolatile Memory may be Read Only Memory (ROM), programmable Read Only Memory (PROM, programmable Read-Only Memory), erasable programmable Read Only Memory (EPROM, erasable Programmable Read-Only Memory), electrically erasable programmable Read Only Memory (EEPROM, electrically Erasable Programmable Read-Only Memory), magnetic random access Memory (FRAM, ferromagnetic random access Memory), flash Memory (Flash Memory), magnetic surface Memory, optical disk, or compact disk Read Only Memory (CD-ROM, compact Disc Read-Only Memory); the magnetic surface memory may be a disk memory or a tape memory. The volatile memory may be random access memory (RAM, random Access Memory), which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available, such as static random access memory (SRAM, static Random Access Memory), synchronous static random access memory (SSRAM, synchronous Static Random Access Memory), dynamic random access memory (DRAM, dynamic Random Access Memory), synchronous dynamic random access memory (SDRAM, synchronous Dynamic Random Access Memory), double data rate synchronous dynamic random access memory (ddr SDRAM, double Data Rate Synchronous Dynamic Random Access Memory), enhanced synchronous dynamic random access memory (ESDRAM, enhanced Synchronous Dynamic Random Access Memory), synchronous link dynamic random access memory (SLDRAM, syncLink Dynamic Random Access Memory), direct memory bus random access memory (DRRAM, direct Rambus Random Access Memory). The memory described by embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
In an exemplary embodiment, the present embodiment further provides a storage medium, i.e. a computer storage medium, which may specifically be a computer readable storage medium, for example, including a memory 402 storing a computer program, where the computer program may be executed by the processor 401 of the performance index data evaluation device to perform the steps described in the method according to the embodiment of the present invention. The computer readable storage medium may be ROM, PROM, EPROM, EEPROM, flash Memory, magnetic surface Memory, optical disk, or CD-ROM.
It should be noted that: "first," "second," etc. are used to distinguish similar objects and not necessarily to describe a particular order or sequence.
In addition, the embodiments of the present invention may be arbitrarily combined without any collision.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (9)
1. A performance index data evaluation method, comprising:
acquiring a set number of sample data, the set number of sample data corresponding to a first product property;
determining sample average values corresponding to the set number of sample data;
determining sample variances corresponding to the set number of sample data;
determining the degree of freedom corresponding to the T distribution based on the numerical value of the set number;
determining the confidence corresponding to the T distribution based on a probability set value;
determining a value corresponding to the T distribution based on the degrees of freedom and the confidence;
determining a confidence interval corresponding to the first product performance based on the sample mean, the sample variance, and the value corresponding to the T distribution; wherein the probability set point characterizes the confidence of the confidence interval.
2. The method of claim 1, wherein the obtaining a set number of sample data comprises:
and acquiring the set number of sample data within a fluctuation range allowed by the test condition of the first product performance.
3. The method of claim 1, wherein the determining the confidence interval for the first product performance based on the sample mean, the sample variance, and the value for the T distribution comprises:
and respectively determining the maximum value and the minimum value of the confidence interval based on the sample mean value, the sample variance and the value corresponding to the T distribution.
4. The method according to claim 1, wherein the method further comprises:
and determining whether the sample data corresponding to the newly tested first product performance is valid or not based on the confidence interval corresponding to the first product performance.
5. The method of claim 4, wherein the determining whether the sample data corresponding to the first product performance of the new test is valid based on the confidence interval corresponding to the first product performance comprises:
acquiring sample data corresponding to the newly tested first product performance;
if the value of the sample data of the new test falls into the confidence interval, determining that the sample data of the new test is valid;
and if the numerical value of the sample data of the new test does not fall into the confidence interval, determining that the sample data of the new test is invalid.
6. A performance index data evaluation device, comprising:
the acquisition module is used for acquiring a set number of sample data, and the set number of sample data corresponds to the first product performance;
the first determining module is used for determining sample average values corresponding to the set number of sample data;
the second determining module is used for determining sample variances corresponding to the set number of sample data;
the table look-up module is used for determining the degree of freedom corresponding to the T distribution based on the numerical value of the set quantity; determining the confidence corresponding to the T distribution based on a probability set value; determining a value corresponding to the T distribution based on the degrees of freedom and the confidence;
a third determining module, configured to determine a confidence interval corresponding to the first product performance based on the sample mean, the sample variance, and a value corresponding to the T distribution;
wherein the probability set point characterizes the confidence of the confidence interval.
7. The apparatus of claim 6, wherein the apparatus further comprises:
and a fourth determining module, configured to determine whether the sample data corresponding to the newly tested first product performance is valid based on the confidence interval corresponding to the first product performance.
8. A performance index data evaluation apparatus, characterized by comprising: a processor and a memory for storing a computer program capable of running on the processor, wherein,
the processor being adapted to perform the steps of the method of any of claims 1 to 5 when the computer program is run.
9. A storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method according to any of claims 1 to 5.
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| CN106908258A (en) * | 2015-12-23 | 2017-06-30 | 阿里巴巴集团控股有限公司 | The method and device of performance test |
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| CN101771758A (en) * | 2008-12-31 | 2010-07-07 | 北京亿阳信通软件研究院有限公司 | Dynamic determine method for normal fluctuation range of performance index value and device thereof |
| CN106908258A (en) * | 2015-12-23 | 2017-06-30 | 阿里巴巴集团控股有限公司 | The method and device of performance test |
| CN106201829A (en) * | 2016-07-18 | 2016-12-07 | 中国银联股份有限公司 | Monitoring Threshold and device, monitoring alarm method, Apparatus and system |
| CN107093022A (en) * | 2017-04-24 | 2017-08-25 | 中国工程物理研究院化工材料研究所 | The small sample appraisal procedure for firing product reliability of high confidence level |
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