CN116384778A - Importance analysis method, device and server for controllable influence factors - Google Patents
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Abstract
The invention provides an importance analysis method, a device and a server for controllable influence factors, which relate to the technical field of test design and comprise the following steps: acquiring each key index of a remote sensing satellite on-orbit test and a controllable influence factor set corresponding to each key index respectively, wherein one key index corresponds to a plurality of controllable influence factors, and the value range of each controllable influence factor corresponds to a plurality of horizontal numbers respectively; determining an experimental design table of the key index based on the key index of any item, a controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model; acquiring a key index measured value corresponding to an experimental design table of the key index; and determining the importance of each controllable influence factor based on the key index measured value through a preset analysis of variance model. The method can obtain the confidence level of the key index evaluation on the basis of determining the importance ordering of the controllable influence factors.
Description
Technical Field
The invention relates to the technical field of test design, in particular to an importance analysis method, an importance analysis device and a server for controllable influence factors.
Background
When the remote sensing satellite performs an orbit test, the more influence factors are needed to be considered when the test environment is constructed, the more the test conclusion is full and reliable, but the problems of long test period, high test cost and the like are brought at the same time, at present, the related technology proposes that the test influence factors can be sequenced in a mode of using a partial correlation analysis method, a computer simulation technology, an orthogonal test and the like, but the scheme does not discuss the confidence degree problem of evaluating the test conclusion by adopting different test influence factors. The remote sensing satellite is used as a space product, the development cost is high, the reliability requirement is high, and the confidence of the evaluation conclusion is as large as possible under the condition that the least influence factors are considered in the on-orbit test (each key index considers the most important influence factors).
Disclosure of Invention
In view of the above, the present invention aims to provide a method, an apparatus, and a server for analyzing importance of controllable influencing factors, which can obtain confidence level of key index evaluation based on determining importance ranking of the controllable influencing factors.
In a first aspect, an embodiment of the present invention provides a method for analyzing importance of a controllable influencing factor, where the method includes: acquiring each key index of a remote sensing satellite on-orbit test and a controllable influence factor set corresponding to each key index respectively, wherein one key index corresponds to a plurality of controllable influence factors, and the value range of each controllable influence factor corresponds to a plurality of horizontal numbers respectively; determining an experimental design table of the key index based on the key index of any item, a controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model; acquiring a key index measured value corresponding to an experimental design table of the key index; and determining the importance of each controllable influence factor based on the key index measured value through a preset analysis of variance model.
In one embodiment, the step of obtaining each key index of the remote sensing satellite on-orbit test and a controllable influence factor set corresponding to each key index respectively includes: acquiring various key indexes and influence conditions of a remote sensing satellite, wherein the influence conditions comprise: the working principle of the remote sensing satellite, equipment development requirements, similar types of on-orbit developed test subjects and existing accompanying test equipment; and analyzing and calculating each key index and influence condition by using a preset controllable influence factor analysis model, and determining a controllable influence factor set corresponding to each key index respectively.
In one embodiment, the step of determining the experimental design table of the key indicator comprises: obtaining the experimental design type of the key index; determining a target orthogonal design model from a preset orthogonal design model set according to the experimental design type; determining test subjects of an experimental design table based on any key index, a controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a target orthogonal design model, wherein the test subjects are used for representing the combination of different controllable influence factors at different levels; and determining an experimental design table of the key indexes based on the experimental subjects.
In one embodiment, the step of determining the importance of each controllable influencing factor based on the key indicator measurement value through a preset analysis of variance model includes: determining F ratio, significance value and R side statistic corresponding to each controllable influence factor in the controllable influence factor set based on the key index measured value through a preset analysis of variance model; and determining the importance of each controllable influence factor by using the F ratio and the significance value, and determining the confidence level of the key index evaluation by using the R-party statistic.
In one embodiment, a method comprises: determining the significance relation between the key index measured value and each controllable influence factor by using the significance value; when the significance value corresponding to the controllable influence factor is larger than a preset threshold value, determining that the significance relation between the controllable influence factor and the key index measured value is not significant; and when the significance value corresponding to the controllable influence factor is not greater than a preset threshold value, determining that the significance relation between the controllable influence factor and the key index measured value is significant.
In one embodiment, the method further comprises: and aiming at the controllable influence factors with obvious significance relation, carrying out importance ranking by using F ratios, wherein the higher the F ratio is, the higher the importance ranking of the controllable influence factors corresponding to the F ratio is.
In one embodiment, the step of determining a confidence level for the key indicator assessment using the R-party statistic comprises: and aiming at the controllable influence factor set, the confidence of the controllable influence factor on the key index evaluation is represented by using the R-party statistic, wherein the larger the R-party statistic is, the higher the confidence of the key index evaluation is, and the higher the confidence of the conclusion of the importance ranking of the controllable influence factor is.
In a second aspect, an embodiment of the present invention further provides an importance analysis device for controllable influencing factors, where the device includes: the system comprises a controllable influence factor set construction module, a remote sensing satellite on-orbit test module and a remote sensing satellite on-orbit test module, wherein each key index corresponds to a plurality of controllable influence factors, and the value range of each controllable influence factor corresponds to a plurality of horizontal numbers; the experimental design table generation module is used for determining an experimental design table of the key index based on the key index of any item, the controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model; the data acquisition module acquires a key index measured value corresponding to an experimental design table of the key index; and the importance analysis module is used for determining the importance of each controllable influence factor based on the key index measured value through a preset variance analysis model.
In a third aspect, embodiments of the present invention also provide a server comprising a processor and a memory, the memory storing computer executable instructions executable by the processor, the processor executing the computer executable instructions to implement the method of any one of the first aspects.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions that, when invoked and executed by a processor, cause the processor to implement the method of any one of the first aspects.
The embodiment of the invention has the following beneficial effects:
according to the importance analysis method, the importance analysis device and the server for the controllable influence factors, after the key indexes and the controllable influence factor sets corresponding to the key indexes of the remote sensing satellite on-orbit test are obtained, an experimental design table of the key indexes is determined based on the key indexes of any item, the controllable influence factor sets corresponding to the key indexes and the level numbers corresponding to the controllable influence factors in the controllable influence factor sets through a preset orthogonal design model; acquiring a key index measured value corresponding to an experimental design table of the key index; and determining the importance of each controllable influence factor based on the key index measured value through a preset analysis of variance model. According to the method, aiming at the remote sensing satellite key index on-orbit test, the importance of the controllable influence factors is ordered through orthogonal test design and analysis of variance, and the R-party statistic of the evaluation model is calculated to serve as the evaluation confidence level of the key index when different controllable influence factors are considered and the confidence level of the importance ranking conclusion of the controllable influence factors.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an index influence factor importance analysis process provided by an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for analyzing importance of a controllable influencing factor according to an embodiment of the present invention;
FIG. 3 is a flow chart of another method for analyzing importance of controllable influencing factors according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an importance analysis device for controllable influencing factors according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
When the remote sensing satellite performs an orbit test, the more influence factors are needed to be considered when the test environment is constructed, the more the test conclusion is full and reliable, but the problems of long test period, high test cost and the like are brought at the same time, at present, the related technology proposes that the test influence factors can be sequenced in a mode of using a partial correlation analysis method, a computer simulation technology, an orthogonal test and the like, but the scheme does not discuss the confidence degree problem of evaluating the test conclusion by adopting different test influence factors. The remote sensing satellite is used as a space product, the development cost is high, the reliability requirement is high, and the confidence of the evaluation conclusion is as large as possible under the condition that the least influence factors are considered in the on-orbit test (each key index considers the most important influence factors). Based on the above, referring to the index influence factor importance analysis process block diagram shown in fig. 1, the importance analysis method of the controllable influence factors provided by the embodiment of the invention ranks the importance of the controllable influence factors through orthogonal test design and variance analysis according to the key index on-orbit test of the remote sensing satellite, and calculates the R-party statistic of the evaluation model as the evaluation confidence level of the key index when different controllable influence factors are considered, so that the confidence level of the key index evaluation can be obtained on the basis of determining the importance ranking of the controllable influence factors.
Referring to fig. 2, a flow chart of a method for analyzing importance of controllable influencing factors is shown, and the method mainly includes the following steps S202 to S208:
step S202, obtaining each key index of a remote sensing satellite on-orbit test and a controllable influence factor set corresponding to each key index respectively, wherein one key index corresponds to a plurality of controllable influence factors, the value range of each controllable influence factor corresponds to a plurality of horizontal numbers respectively, in one implementation mode, for each key index of the remote sensing satellite, all controllable influence factors influencing the key index are obtained by analyzing the working principle of the remote sensing satellite, equipment development requirements, test subjects developed on orbit with similar models, existing accompanying test equipment and the like, a controllable influence factor set corresponding to the key index is formed, the possible value range of each factor in the controllable influence factor set is divided into different levels, and the divided horizontal numbers of each controllable influence factor can be different.
Step S204, determining an experimental design table of the key index based on the key index of any item, the controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model, in one implementation mode, after determining the level selected by each influence factor in each experimental subject, constructing a corresponding experimental environment, and implementing the experimental subject, so as to test the measured value of the key index value under different environments, in another implementation mode, reasonably setting the experimental design table through orthogonal experimental design, so that the number of combinations of the experimental influence factors can be effectively reduced, the experimental period is shortened, and the experimental cost is reduced.
Step S206, obtaining a key index measured value corresponding to the experimental design table of the key index, wherein the key index measured value is a measured value of the key index to be measured under the combination of different levels of each controllable influence factor.
Step S208, determining the importance of each controllable influence factor based on the key index measured value through a preset variance analysis model, and in one embodiment, determining the F ratio, the significance value and the R side statistic corresponding to each controllable influence factor in the controllable influence factor set based on the key index measured value through a preset variance analysis model; and determining the importance of each controllable influence factor by using the F ratio and the significance value, and determining the confidence coefficient of the key index evaluation by using the R-party statistic, wherein the higher the F ratio is, the higher the importance ranking of the controllable influence factors corresponding to the F ratio is, the higher the R-party statistic is, and the higher the confidence coefficient of the key index evaluation is, and the higher the confidence coefficient of the conclusion of the importance ranking of the controllable influence factors is.
According to the importance analysis method of the controllable influence factors, which is provided by the embodiment of the invention, aiming at the remote sensing satellite key index on-orbit test, the importance of the controllable influence factors is ordered through orthogonal test design and variance analysis, and the R-party statistic of the evaluation model is calculated to serve as the evaluation confidence coefficient of the key index when different controllable influence factors are considered, so that the confidence coefficient of key index evaluation can be obtained on the basis of determining the importance ordering of the controllable influence factors.
The embodiment of the invention also provides an implementation mode for determining the experimental design table, and the implementation modes are specifically shown in the following (1) to (2):
(1) Acquiring various key indexes and influence conditions of a remote sensing satellite, wherein the influence conditions comprise: the working principle of the remote sensing satellite, equipment development requirements, on-orbit developed test subjects of similar types and existing accompanying test equipment are utilized to analyze and calculate each key index and each influence condition by utilizing a preset controllable influence factor analysis model, and a controllable influence factor set corresponding to each key index is determined.
(2) Obtaining the experimental design type of the key index; determining a target orthogonal design model from a preset orthogonal design model set according to the experimental design type; determining test subjects of an experimental design table based on any key index, a controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a target orthogonal design model, wherein the test subjects are used for representing the combination of different controllable influence factors at different levels; and determining an experimental design table of the key indexes based on the experimental subjects. In one embodiment, for a certain key index of a remote sensing satellite, if there are N controllable influencing factors after analysis, each influencing factor is divided into M levels, then a uniform design method is adopted, a total of MN test subjects need to be designed, and the values of the key indexes are tested respectively in each test subject. To reduce trial subjects, the trial subjects may be designed using orthogonal design methods. The orthogonal design table commonly used in the orthogonal test design process comprises
、
、/>
、/>
、/>
Etc., wherein->
Representing orthogonal table->
The lower right hand corner number represents the number of trial subjects to be designed, the superscript in brackets represents the number of influencing factors that are most allowed to be arranged, and the other numbers represent the number of levels of influencing factors.
In practical application, controllable influence factors considered in the test process are different, the level number is different, the number of designed test subjects is also different, one test subject represents the combination of different levels of different controllable influence factors, for different test subjects obtained through test design, a corresponding test environment is constructed, a corresponding test subject is implemented, under the combination of different influence factor levels, the value of a key index is tested, in one embodiment, 3 controllable influence factors A, B, C are assumed to exist in a key index of a remote sensing satellite, each influence factor takes 3 levels, an orthogonal design method is adopted, and the method is utilized
Orthogonal tables only 9 trial subjects need to be designed, each subject having a controlled combination of influencing factor levels as shown in table 1.
TABLE 1 Key indicator orthogonal test subject design examples
The embodiment of the invention also provides an implementation mode for determining the importance of each controllable influence factor, and the implementation mode is specifically described in the following (A) to (B):
(A) Determining the significance relation between the key index measured value and each controllable influence factor by using the significance value; when the significance value corresponding to the controllable influence factor is larger than a preset threshold value, determining the significance of the controllable influence factor and the key index measured valueThe sexual relationship is not significant; when the significance value corresponding to the controllable influence factor is not greater than the preset threshold, determining that the significance relation between the controllable influence factor and the key index measured value is significant, in one embodiment, performing importance sorting by using an F ratio aiming at the controllable influence factor with the significant significance relation, wherein the higher the F ratio is, the higher the importance ranking of the controllable influence factor corresponding to the F ratio is, and in another embodiment, the F ratio of each controllable influence factor is: calculating each controllable influencing factor
At a given level of significance +.>
(generally 0.05) determining the reject domain +.>
. If the controllable influencing factor is->
F ratio of->
Indicating the influence factor->
Different levels have significant influence on key indexes, and +.>
The greater the value, the greater the significance of the influencing factor, the greater the significance of the key index test, and therefore, by comparing +.>
The values can sort the importance of all controllable influence factors influencing the key index, and in the follow-up on-orbit test process of satellites with the same model, only the important controllable influence factors are considered according to the actual situation, so that the aim of reducing the test subjects is fulfilled.
(B) For the controllable influence factor set, the confidence of the controllable influence factors on the key index evaluation is represented by using the R-party statistic, wherein the larger the R-party statistic is, the higher the confidence of the key index evaluation is, and the higher the confidence of the conclusion of the importance ranking of the controllable influence factors is, in one embodiment, the R-party statistic is used for describing the interpretability degree of all the controllable influence factors in the evaluation model on the variance change of the measured value of the key index, and when different numbers of controllable influence factors are used in the evaluation model (different controllable influence factors are considered in the test process), the R-party statistic of the evaluation model is different.
In order to facilitate understanding of the method for analyzing the importance of the controllable influencing factor provided in the above embodiment, the embodiment of the present invention provides an application example of the importance analysis of the controllable influencing factor for the sensitivity of a system during the in-orbit test of a commercial SAR remote sensing satellite, referring to a flow chart of another method for analyzing the importance of the controllable influencing factor shown in fig. 3, the method mainly includes the following steps S302 to S306:
step S302, a controllable influence factor set and a level number of the controllable influence factors are obtained. In one embodiment, during the on-orbit test of the SAR remote sensing satellite scientific research satellite, the controllable influencing factors of the system sensitivity are 3 signal frequencies, azimuth angles and pitching angles, wherein the signal frequencies, the azimuth angles and the pitching angles respectively take 5 horizontal numbers, and
. The controllable influencing factors and 5 horizontal values thereof are shown in table 2 respectively:
TABLE 2 sensitive and controllable influencing factors and level numbers of remote sensing satellite system
Step S304, determining an experimental design table according to the controllable influence factor set and the level number of the controllable influence factors, and determining a key index measured value. In one embodiment, an orthogonal design table is used for a system sensitivity 3 factor 5 level
The development of the test design requires the design of 25 test subjects in total, each corresponding to a horizontal combination. For each subject, the sensitivity of the remote sensing satellite system was tested separately and the test values for the sensitivity were recorded as shown in table 3.
TABLE 3 sensitivity test subject design and test results for remote sensing satellite system
Step S306, the importance of each controllable influence factor is determined through variance analysis. In one embodiment, SPSS software may be used to perform analysis of variance, and the results are shown in Table 4, where the effects of correction model, intercept, frequency, azimuth angle on system sensitivity are significant
Less than or equal to 0.05), the pitching angle has no obvious influence on the sensitivity of the system, and the F value of each controllable influence factor in the table can be seen that the importance degree of the 3 controllable influence factors on the sensitivity change of the system is as follows: frequency (23.712)>Azimuth (4.960) > pitch (0.312); and when 3 controllable influence factors are considered, the confidence coefficient of the system sensitivity index evaluation model is 0.906 (R square value).
TABLE 4 results of inter-subject effect test for sensitivity variance analysis of systems
In another embodiment, when considering the most important 2 control influencing factors, namely frequency and azimuth angle, the orthogonal design still needs to adopt an orthogonal design table
The development of the test design requires designing 25 test subjects in total. Analysis of variance was performed using SPSS software, and the results are shown in Table 5, with a confidence level of the system sensitivity index evaluation model of 0.896 (R-square value）。
TABLE 5 sensitivity analysis of variance inter-subject effect test results (2 most important controllable influencing factors)
In another embodiment, when considering the most important 1 controlling influencing factors, i.e., frequency, a total of 5 trial subjects need to be designed for orthogonal design. Analysis of variance was performed using SPSS software, and the results are shown in Table 6, with a confidence level of 0.741 (R-square) for the system sensitivity index assessment model.
TABLE 6 sensitivity analysis of variance inter-subject effect test results (1 most important controllable influencing factors)
In summary, according to the remote sensing satellite key index on-orbit test, the importance of the controllable influence factors is ordered through orthogonal test design and analysis of variance, and the R-party statistic of the evaluation model is calculated to serve as the evaluation confidence level of the key index when different controllable influence factors are considered, so that the confidence level of key index evaluation can be obtained on the basis of determining the importance ordering of the controllable influence factors.
For the method for analyzing the importance of the controllable influencing factor provided in the foregoing embodiment, the embodiment of the present invention provides an apparatus for analyzing the importance of the controllable influencing factor, referring to a schematic structural diagram of the apparatus for analyzing the importance of the controllable influencing factor shown in fig. 4, where the apparatus includes the following parts:
the controllable influence factor set construction module 402 is used for acquiring each key index of the remote sensing satellite on-orbit test and a controllable influence factor set corresponding to each key index respectively, wherein one key index corresponds to a plurality of controllable influence factors, and the value range of each controllable influence factor corresponds to a plurality of horizontal numbers respectively;
the experiment design table generating module 404 determines an experiment design table of the key index based on the key index of any one item, the controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model;
the data acquisition module 406 acquires a key index measured value corresponding to the experimental design table of the key index;
the importance analysis module 408 determines the importance of each controllable influencing factor based on the key index measurement value through a preset analysis of variance model.
According to the data processing device provided by the embodiment of the application, aiming at the remote sensing satellite key index on-orbit test, the importance of the controllable influence factors is ordered through orthogonal test design and analysis of variance, and the R-party statistic of the evaluation model is calculated to serve as the evaluation confidence coefficient of the key index when different controllable influence factors are considered.
In one embodiment, when the step of obtaining each key index of the remote sensing satellite on-orbit test and the controllable influence factor set corresponding to each key index are performed, the controllable influence factor set building module 402 is further configured to: acquiring various key indexes and influence conditions of a remote sensing satellite, wherein the influence conditions comprise: the working principle of the remote sensing satellite, equipment development requirements, similar types of on-orbit developed test subjects and existing accompanying test equipment; and analyzing and calculating each key index and influence condition by using a preset controllable influence factor analysis model, and determining a controllable influence factor set corresponding to each key index respectively.
In one embodiment, when performing the step of determining the experimental design table of the key index, the experimental design table generating module 404 is further configured to: obtaining the experimental design type of the key index; determining a target orthogonal design model from a preset orthogonal design model set according to the experimental design type; determining test subjects of an experimental design table based on any key index, a controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a target orthogonal design model, wherein the test subjects are used for representing the combination of different controllable influence factors at different levels; and determining an experimental design table of the key indexes based on the experimental subjects.
In one embodiment, when performing the step of determining the importance of each controllable influencing factor based on the key indicator measurement value by using a preset analysis of variance model, the importance analysis module 408 is further configured to: determining F ratio, significance value and R side statistic corresponding to each controllable influence factor in the controllable influence factor set based on the key index measured value through a preset analysis of variance model; and determining the importance of each controllable influence factor by using the F ratio and the significance value, and determining the confidence level of the key index evaluation by using the R-party statistic.
In one embodiment, the importance analysis module 408 is further configured to: determining the significance relation between the key index measured value and each controllable influence factor by using the significance value; when the significance value corresponding to the controllable influence factor is larger than a preset threshold value, determining that the significance relation between the controllable influence factor and the key index measured value is not significant; and when the significance value corresponding to the controllable influence factor is not greater than a preset threshold value, determining that the significance relation between the controllable influence factor and the key index measured value is significant.
In one embodiment, the importance analysis module 408 is further configured to: and aiming at the controllable influence factors with obvious significance relation, carrying out importance ranking by using F ratios, wherein the higher the F ratio is, the higher the importance ranking of the controllable influence factors corresponding to the F ratio is.
In one embodiment, in performing the step of determining a confidence level for the key indicator assessment using the R-party statistic, the importance analysis module 408 is further configured to: and aiming at the controllable influence factor set, the confidence of the controllable influence factor on the key index evaluation is represented by using the R-party statistic, wherein the larger the R-party statistic is, the higher the confidence of the key index evaluation is, and the higher the confidence of the conclusion of the importance ranking of the controllable influence factor is.
The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.
The embodiment of the invention provides electronic equipment, which comprises a processor and a storage device; the storage means has stored thereon a computer program which, when executed by the processor, performs the method of any of the embodiments described above.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 100 includes: a processor 50, a memory 51, a bus 52 and a communication interface 53, the processor 50, the communication interface 53 and the memory 51 being connected by the bus 52; the processor 50 is arranged to execute executable modules, such as computer programs, stored in the memory 51.
The memory 51 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is achieved via at least one communication interface 53 (which may be wired or wireless), and the internet, wide area network, local network, metropolitan area network, etc. may be used.
Bus 52 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 5, but not only one bus or type of bus.
The memory 51 is configured to store a program, and the processor 50 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 50 or implemented by the processor 50.
The processor 50 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware in the processor 50 or by instructions in the form of software. The processor 50 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 51 and the processor 50 reads the information in the memory 51 and in combination with its hardware performs the steps of the above method.
The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for analyzing the importance of a controllable influencing factor, the method comprising:
acquiring each key index of a remote sensing satellite on-orbit test and a controllable influence factor set corresponding to each key index respectively, wherein one key index corresponds to a plurality of controllable influence factors, and the value range of each controllable influence factor corresponds to a plurality of horizontal numbers respectively;
determining an experimental design table of the key index based on the key index of any one item, the controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model;
acquiring the key index measured value corresponding to the experimental design table of the key index;
and determining the importance of each controllable influence factor based on the key index measured value through a preset analysis of variance model.
2. The method according to claim 1, wherein the step of obtaining each key indicator of the remote sensing satellite on-orbit test and the controllable influence factor set corresponding to each key indicator respectively includes:
acquiring each key index and each influence condition of the remote sensing satellite, wherein the influence conditions comprise: the working principle of the remote sensing satellite, equipment development requirements, similar types of on-orbit developed test subjects and existing accompanying test equipment;
and analyzing and calculating the key indexes and the influence conditions by using a preset controllable influence factor analysis model, and determining the controllable influence factor sets corresponding to the key indexes respectively.
3. The method of claim 1, wherein the step of determining the experimental design table of key indicators comprises:
acquiring the experimental design type of the key index;
determining a target orthogonal design model from a preset orthogonal design model set according to the experimental design type;
determining, by the target orthogonal design model, a test subject of the experiment design table based on the key indicator of any one item, the controllable influence factor set corresponding to the key indicator, and the level numbers corresponding to the controllable influence factors in each item in the controllable influence factor set, where the test subject is used to characterize combinations of different controllable influence factors at different levels;
and determining an experimental design table of the key index based on the experimental subjects.
4. The method of claim 1, wherein the step of determining the importance of each of the controllable influencing factors based on the key indicator measurements by a predetermined analysis of variance model comprises:
determining F ratio, significance value and R side statistic corresponding to each controllable influence factor in the controllable influence factor set based on the key index measured value through a preset analysis of variance model;
and determining the importance of each controllable influence factor by using the F ratio and the significance value, and determining the confidence level of the key index evaluation by using the R-party statistic.
5. The method according to claim 4, characterized in that the method comprises:
determining the significance relation between the key index measured value and each controllable influence factor by using a significance value;
when the significance value corresponding to the controllable influence factor is larger than a preset threshold value, determining that the significance relation between the controllable influence factor and the key index measured value is not significant;
and when the significance value corresponding to the controllable influence factor is not greater than a preset threshold value, determining that the significance relation between the controllable influence factor and the key index measured value is significant.
6. The method of claim 5, wherein the method further comprises:
and aiming at the controllable influence factors with the significant relation, carrying out importance ranking by utilizing the F ratio, wherein the higher the F ratio is, the higher the importance ranking of the controllable influence factors corresponding to the F ratio is.
7. The method of claim 4, wherein the step of determining a confidence level for the key indicator assessment using R-party statistics comprises:
and aiming at the controllable influence factor set, the confidence coefficient of the controllable influence factor on the key index evaluation is represented by the R-party statistic, wherein the larger the R-party statistic is, the higher the confidence coefficient of the key index evaluation is, and the higher the conclusion confidence coefficient of the importance ranking of the controllable influence factor is.
8. An apparatus for analyzing the importance of a controllable influencing factor, said apparatus comprising:
the system comprises a controllable influence factor set construction module, a remote sensing satellite on-orbit test module and a remote sensing satellite on-orbit test module, wherein each key index of the remote sensing satellite on-orbit test module is used for acquiring a plurality of controllable influence factors corresponding to each key index, and the value range of each controllable influence factor is respectively corresponding to a plurality of horizontal numbers;
the experimental design table generation module is used for determining an experimental design table of the key index based on the key index of any one item, the controllable influence factor set corresponding to the key index and the level number corresponding to each controllable influence factor in the controllable influence factor set through a preset orthogonal design model;
the data acquisition module is used for acquiring the key index measured value corresponding to the experiment design table of the key index;
and the importance analysis module is used for determining the importance of each controllable influence factor based on the key index measured value through a preset analysis of variance model.
9. A server comprising a processor and a memory, the memory storing computer executable instructions executable by the processor, the processor executing the computer executable instructions to implement the method of any one of claims 1 to 7.
10. A computer readable storage medium storing computer executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of claims 1 to 7.
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