CN112150008B - System structure evaluation method and system based on design data and experimental data - Google Patents
System structure evaluation method and system based on design data and experimental data Download PDFInfo
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Abstract
The invention provides a system structure evaluation method and a system thereof based on design data and experimental data, wherein the method comprises the following steps: acquiring system structure design data and experimental data; constructing a capacity index system according to the system structure design data; importing experimental data into a capacity index system, and determining the capacity index grade; and calculating the system maturity according to the capability index grade so as to evaluate the system structure according to the system maturity. The system comprises various modules corresponding to the method. The invention makes clear the effectiveness of the system structure design scheme in the system structure design stage, emphasizes the key of the combination of the system structure design and the simulation experiment, and can utilize the simulation experiment result to compare the system structure design data to carry out the system structure evaluation, so that the system structure evaluation result is more convincing.
Description
Technical Field
The invention relates to the field of system structures, and particularly discloses a system structure evaluation method and a system based on design data and experimental data.
Background
An architecture is a guide to the structure of the various system components, the relationships between the components, and to their design and evolution. The blueprint for guiding the construction of the military information system provides a way for various stakeholders of the system to know and understand the existing system and provides whole-course guidance for the analysis, design, implementation and maintenance of the military information system. The architecture design is helpful for promoting the communication and understanding of various personnel, assisting the design decision of the support system, guiding the development and integration of the system and guiding the evolution of the system.
The system structure is in the early stage of system construction, and is the key for carding system design factors and measuring the quality of future system construction. The efficient evaluation of the system structure design result is beneficial to the system construction and evolution of the next step. However, currently, evaluation of architecture design results is often achieved by means of human judgment or subjective decision, and although in recent years, data-centric architecture design ideas are emphasized, designed architecture data is often used for static architecture analysis, which is not strong in persuasion. In addition, the current architecture design achievement is difficult to effectively guide practice and combine with experimental simulation, so that reasonable and effective architecture evaluation data is difficult to provide, and the architecture evaluation work is difficult to effectively expand. The system maturity can be used as a key index for measuring the structural design result of the system, and is judged by analyzing the capability index in the structural capability view of the system. If the effect is better when one system structure design scheme meets all the capability indexes, the system maturity of the scheme can be considered to be higher. At present, the calculation of the system maturity is based on the development of specific system construction results, such as the support of each weapon in a weapon equipment system to a combat system. And at present, an analysis technology is not developed for the system maturity at the system design stage of system planning.
Disclosure of Invention
The invention aims to provide a system structure evaluation method and a system thereof based on design data and experimental data, so as to solve the technical defects that the system structure design achievement in the prior art is difficult to effectively guide practice and is difficult to combine with experimental simulation.
In order to achieve the above object, the present invention provides a method for evaluating an architecture based on design data and experimental data, comprising the steps of:
acquiring system structure design data and experimental data;
constructing a capacity index system according to the system structure design data;
importing experimental data into a capacity index system, and determining the level of a capacity index;
and calculating the system maturity according to the capability index grade so as to evaluate the system structure according to the system maturity.
Based on the above evolutionary algorithm, the present invention also provides a system structure evaluation system based on design data and experimental data, which is characterized by comprising:
a first module: for obtaining architectural design data and experimental data;
a second module: for constructing a capability index system from the architectural design data;
a third module: the system is used for importing experimental data into a capacity index system and determining the capacity index grade;
a fourth module: and the system is used for calculating the system maturity according to the capability index level so as to evaluate the system structure according to the system maturity.
The invention has the following beneficial effects:
the invention selects the system maturity evaluation based on the combination of the system structure design data and the simulation experiment data, and aims to analyze the maturity of each capability index of the system structure according to the system structure design data (such as capability, capability index and capability measurement standard) and the experiment data (such as activity attribute experiment factor level and capability index simulation result) so as to obtain the maturity of the system structure design scheme as the measurement basis of the system maturity. Therefore, the method can break through the traditional defects that the system structure evaluation lacks experimental data and the evaluation result is not strong enough, is combined with the system structure experimental scheme, achieves the closed loop of system structure design landing and system structure analysis, and has breakthrough significance.
The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a method for evaluating architecture based on design data and experimental data according to the present invention;
FIG. 2 is a schematic diagram of a capability decomposition relationship of the preferred embodiment of the present invention;
FIG. 3 is a block diagram of an architecture evaluation system based on design data and experimental data according to the present invention.
Detailed Description
Embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
The embodiment first proposes an architecture evaluation method based on design data and experimental data, and with reference to fig. 1, the method includes the following steps:
s1: architecture design data and experimental data are obtained.
The architectural design data includes the following steps. :
s101: and decomposing the architecture according to the capacity to obtain a capacity decomposition relation of the architecture.
The capability resolution relationship represents a resolution relationship between capabilities of the architecture, and referring to fig. 2, for example, the search and rescue capability can be divided into an assistance capability, a search capability, a command and control capability, and a rescue capability.
S102: setting capability effect indexes of each capability in the capability decomposition relationship and setting capability correlation activities of each capability in the capability decomposition relationship.
The capability effect index describes an index required to achieve each capability, is an expression of coarse granularity of capability measurement, and needs to be further analyzed and measured through other factors or attributes. For example, the rescue ability can be measured by a rescue success rate index, the search ability can be measured by a search success rate index, and the command control ability can be measured by commanding timeliness. The measurement standards of the capacity index need to be set in the system design process and are generally divided into 4 standard levels, for example, for the rescue success rate, the standard one is 40%, the standard 2 is 60%, the standard three is 80%, and the standard four is 100%, and these data are set by the user in the system structure design process and are key indexes for measuring the system maturity. The following table 1 is a capability effect index table.
TABLE 1 capability and effect index Table
The mapping relationship between the abilities and the activities represents the support relationship between the fighting activities and the abilities, can be a many-to-many relationship and is often described in a form of a table or a matrix, for example, the activities related to the rescue abilities comprise the activities of positioning victims, monitoring bodies, receiving rescue information, searching activities, turning to safe areas and the like. Table 2 below is a capability to activity mapping, i.e., a capability-associated activity.
TABLE 2 capability to Activity mapping
S103: and setting relevant indexes of the capacity associated activities.
The activity effect attribute represents a relevant index of activity execution, is obtained by determining an effect attribute of each activity of the combat activity model, and is often described in a table form, for example, positioning the effect attribute of a victim to positioning the time of the victim, monitoring the effect attribute of a body to be the physical condition, and the like. Table 3 below is the activity effect attribute, i.e. the relevant index of the ability-related activity.
TABLE 3 Activity Effect attributes
| Movement of | Effect attributes |
| Locating victims | Locating victim time |
| Monitoring a body | Physical condition |
| Receiving rescue information | Time of signal transmission |
| Go to a safe area | Time to transfer to safe area |
| Local aid | Probability of local assistance |
| Issuing a search plan | Time of signal transmission |
| Performing a search | Execution of search time |
| Local aid | Probability of local assistance |
| Performing a search | Execution of search time |
| Transmitting alarm commands | Time of signal transmission |
| Analysing alarm signals | Target detection time |
| Making a search plan | Search planning time |
| Finger controlled activity | Finger-controlled activity processing time |
S104: and taking the capability effect index, the capability correlation activity and the capability correlation activity as the architecture design data.
The method for acquiring the system structure experiment data comprises the following steps:
s111: and forming an experimental scheme by taking the relevant indexes of the capacity-related activities as experimental factors.
S112: the experimental level was determined for each experimental factor.
S113: and generating an experimental sample according to the experimental scheme and the experimental level.
The test scheme associated with each capability index corresponds to a number of test samples, each test sample being a combination of different levels of a plurality of test factors. For each test protocol, any corresponding test sample is selected as the capability index to be analyzed and evaluated. And obtaining a combination of the test samples of the plurality of test schemes, namely the design scheme of the system structure under the scene. The two steps are the derivation of the test scheme execution result based on the architecture design data, and are the analysis and evaluation of the architecture simulation test result.
S114: and obtaining an experimental structure according to the experimental sample as the system structure experimental data.
For selected combinations of test samples, test results for each sample may be obtained. And comparing the test result with the measurement standard of the capability index in the system structure data to obtain the actual grade value of each capability index, and using the actual grade value as the bottom input for measuring the system maturity. The step is the key content of the invention, and the measurement result of the capability index is obtained by comparing the system structure design data with the system test data and is used as the basis of the system analysis, thereby realizing the system analysis technology based on the test and distinguishing the qualitative and static analysis of the system effect attribute from the traditional method. The step uses the system structure design data as the analysis basis again, which shows that the system structure design data can effectively support the practice.
The experimental scheme referred to in this embodiment is a scheme set for measuring each capability index, for example, for the rescue success rate in table 2, an experimental scheme is set, the activity attribute corresponding to the rescue capability is used as an experimental factor, and the rescue success rate under each experimental level combination is analyzed by determining different experimental level setting experimental schemes. The experimental plan setup process is described below, and the results of obtaining the performance indicators can be output as an input to the system maturity measure of the present invention through the execution of the experimental plan.
In the experimental scheme setting process, each capability index is used as an experimental scheme, then an activity attribute set associated with each capability index is determined according to the mapping relation between the capability and the activity, the activity attributes are used as experimental factors of the capability index, and other activity attributes are used as uncontrollable variables to be assigned in the experimental process. As shown in table 4, each ability index is used as an experimental plan, and the activity attribute corresponding to the ability index is used as an experimental factor to form the experimental plan.
TABLE 4 Experimental protocols
Then, for the experiment factor associated with each experiment scheme, the experiment level is determined, which mainly includes the contents of the level number, the level setting mode, the minimum value, the maximum value, the unit and the like of the experiment factor, as shown in table 5.
TABLE 5 setting of Experimental levels
Based on the determined experimental protocol and the level values of the experimental factors, experimental samples may then be generated according to different experimental sample generation methods, as shown in table 6. For example, for the experimental plan 1, 9 experimental samples are generated in an orthogonal design, and these experimental samples are used as input of the experiment, and the determination of the capability index value is performed through the experiment.
TABLE 6 Generation of Experimental samples
The whole step S1 is mainly to import data such as capability, capability decomposition relation, capability index and the like required by system maturity evaluation according to a system structure description model and design data, and import the data according to an XML format.
S2: a capability index system is constructed from the architectural design data.
And establishing a capacity index system according to the structural design data of the system, wherein the capacity index system comprises a multi-layer corresponding relation of capacity and capacity indexes, and the maturity level of the bottom-layer capacity index is determined according to the test result. And the construction of the capability index system is convenient for converging and calculating the maturity of the system from bottom to top. The first two steps are the export of the data of the architecture design, and the idea that the architecture design takes the data as the center is embodied.
S3: and importing the experimental data into a capacity index system, and determining the capacity index grade.
And obtaining a simulation result of the test scheme according to the test scheme constructed by the execution capacity index and the activity attribute, wherein the simulation result is mainly expressed as the test scheme, the corresponding test factor and the test result under each test level combination condition. The test result is used as the basis for analyzing the maturity of the system.
S4: and calculating the system maturity according to the capability index grade so as to evaluate the system structure according to the system maturity.
Before the system maturity is calculated, a maturity calculation method needs to be selected, and the maturity calculation method comprises a weighted summation method or a bucket rule. Calculating the weight by a weighted sum method according to a matrix method or directly inputting the weight by a user, and then converging the grade of the capability index to obtain the integral system maturity; the bucket rule considers the lowest value of the capacity index grade as the maturity of the system.
According to the first two steps of the above process, the architecture design data is imported and a capability index system is generated, and the capability index to be evaluated is determined, as shown in table 7.
TABLE 7 capability index System
Then, according to the third and fourth steps of the above-mentioned flow, test data is imported according to the test scheme name, the capability index, the test sample, the test factor level, the test result, and the like, to obtain the test results of the plurality of samples associated with each test scheme, as shown in table 8.
TABLE 8 test results
According to the above test results, for each test protocol, the test sample to be analyzed is selected, as shown in table 9, each row in table 9 can be selected only one, which represents the basis for selecting this test sample as the capability index level determination for the test protocol.
TABLE 9
According to the selected test sample combination, the combination corresponds to the capability index measurement standard in the system structure design data, as shown in table 10, for example, if the test result of the test sample corresponding to the rescue success rate is 60%, and the result is greater than or equal to the measurement standard 2, the index grade of the rescue success rate can be considered as 2, and the maturity of the index can also be considered as 2; for the controlled aging performance, the test result is 75%, and if the test result is greater than the measurement standard 1 but less than the measurement standard 2, the index grade of the controlled aging performance can be considered to be 1.
Watch 10
And further determining a calculation method of the system maturity according to the obtained index grade of each capability index. For example, the bucket rule is adopted to calculate the overall maturity, and for the capacity index system established in table 7, according to the calculation result in table 10, the index level for controlling timeliness is the lowest, and the system maturity is considered to be 1.
Based on the steps, the system maturity calculation method combining the system structure design data and the system test data is realized. The invention can convert the system structure design data into the test design and simulation requirements, further carry out the system capability and efficiency analysis according to the test result, form the system analysis closed loop, verify the effectiveness of the system design and facilitate the optimization of the system design scheme.
In a word, according to the invention, firstly, the effectiveness of the system structure design scheme is clarified in the system structure design stage, meanwhile, the key of the combination of the system structure design and the simulation experiment is emphasized, the system structure evaluation can be carried out by comparing the system structure design data with the simulation test result, and the system structure evaluation result is more convincing.
Based on the above method, the present invention further provides an architecture evaluation system based on design data and experimental data, referring to fig. 3, including:
a first module: for obtaining architecture design data and experimental data;
a second module: for constructing a capability index system from the architectural design data;
a third module: the system is used for importing experimental data into a capacity index system and determining the capacity index grade;
a fourth module: and the system is used for calculating the system maturity according to the capability index level so as to evaluate the system structure according to the system maturity.
Preferably, the first module comprises the following units:
a first unit; the capability decomposition relation is used for decomposing the architecture according to the capability to obtain the architecture;
a second unit: the capability effect indexes are used for setting various capabilities in the capability decomposition relationship and the capability correlation activities are used for setting various capabilities in the capability decomposition relationship;
a third unit: for setting a relevant index of the capability-related activity;
a fourth unit: the method is used for taking the capability effect index, the capability correlation activity and the capability correlation activity as the architecture design data.
Preferably, the first module further comprises the following units:
a fifth unit; the system is used for forming an experimental scheme by taking the relevant indexes of the capacity-related activities as experimental factors;
a sixth unit: for determining the experimental level of each experimental factor;
a seventh unit: for generating experimental samples according to experimental protocols and experimental levels;
an eighth unit: and the system is used for obtaining an experimental structure according to the experimental sample so as to serve as system structure experimental data.
Preferably, the fourth module calculates the system maturity and further comprises a maturity calculation method selection module, and the maturity calculation method selected by the maturity calculation method selection module comprises a weighted sum method or a bucket method.
Preferably, the weighting and summing method calculates the weight according to a matrix method or the weight is directly input by a user, and then the integral system maturity is obtained in a mode of converging the grade of the capability index; the bucket rule considers the lowest value of the capacity index grade as the maturity of the system.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. The architecture evaluation method based on design data and experimental data is characterized by comprising the following steps of:
obtaining architecture design data;
wherein the obtaining architecture design data comprises: decomposing the architecture according to the capability to obtain capability decomposition relationship of the architecture, setting capability effect indexes of each capability in the capability decomposition relationship, setting a measurement standard of the capability effect indexes, setting capability correlation activities of each capability in the capability decomposition relationship, setting related indexes of the capability correlation activities, and taking the capability effect indexes, the capability correlation activities and the related indexes of the capability correlation activities as the design data of the architecture,
the ability comprises search and rescue ability, the ability corresponding to the decomposition of the search and rescue ability comprises search ability, rescue ability, command and control ability and assistance ability, the ability related activities corresponding to the search and rescue ability comprise monitoring activities, rescue activities, search activities and control activities, the ability related activities corresponding to the search ability comprise local assistance, search activities, issuing of search plans and execution of search, the ability related activities corresponding to the rescue ability comprise positioning of victims, monitoring of bodies, receiving of rescue information, rescue activities and transfer to a safe area, the ability related activities corresponding to the command and control ability comprise transmitting of alarm commands, analyzing of alarm signals, monitoring activities, control activities and designation of search plans, and the ability related activities corresponding to the assistance ability comprise local assistance and execution of search;
constructing a capacity index system according to the system structure design data;
acquiring system structure experiment data, importing the experiment data into a capacity index system, and determining the capacity index grade;
wherein, the acquiring of the system structure experiment data comprises using the relevant indexes of the ability-related activities as experiment factors to form an experiment scheme, the experiment scheme is a scheme set for measuring each ability effect index, in the setting process of the experiment scheme, each ability effect index is used as an experiment scheme, then according to the ability-related activities associated with each ability effect index, the relevant indexes of the ability-related activities are used as the experiment factors of the corresponding ability effect indexes, the experiment level of each experiment factor is determined, the experiment samples are generated according to the experiment scheme and the experiment level, each ability effect index-related experiment scheme can correspond to a plurality of experiment samples, different experiment samples are the combination of the different levels of the plurality of experiment factors, the experiment result is obtained according to the experiment samples to be used as the system structure experiment data,
for each test scheme, selecting any corresponding test sample, obtaining a combination of the test samples of a plurality of test schemes as a design scheme of the system structure under the scene, and for the test result of the test sample of any test scheme, comparing the test result with the measurement standard of the capability effect index in the design data of the system structure, thus obtaining the capability index grade of the capability effect index corresponding to each test scheme;
and calculating the system maturity according to the capability index grade of each capability effect index so as to evaluate the design scheme of the system structure according to the system maturity, wherein a maturity calculation method is required to be selected before calculating the system maturity, and the maturity calculation method comprises a weighted sum method or a bucket rule.
2. The method for evaluating an architecture based on design data and experimental data according to claim 1, wherein a weighted summation method calculates weights according to a matrix method or weights are directly input by a user, and then grades of various capability and effect indexes are gathered to obtain an overall system maturity; the bucket rule is that the lowest value of the capacity index grade is taken as the maturity of the system.
3. An architecture evaluation system based on design data and experimental data, comprising:
a first module: for obtaining architectural design data and experimental data;
wherein the first module comprises the following units:
a first unit: the capability decomposition relation is used for decomposing the architecture according to the capability to obtain the architecture;
a second unit: the capability effect indexes are used for setting various capabilities in the capability decomposition relationship, the measuring standard of the capability effect indexes is set, and the capability correlation activities of the various capabilities in the capability decomposition relationship are set;
a third unit: relevant indexes for setting capacity associated activities;
a fourth unit: for using the capability effect indicators, the capability-related activities, the related indicators of the capability-related activities as the architectural design data,
the ability comprises search and rescue ability, the ability corresponding to the decomposition of the search and rescue ability comprises search ability, rescue ability, command and control ability and assistance ability, the ability related activities corresponding to the search and rescue ability comprise monitoring activities, rescue activities, search activities and control activities, the ability related activities corresponding to the search ability comprise local assistance, search activities, issuing of search plans and execution of search, the ability related activities corresponding to the rescue ability comprise positioning of victims, monitoring of bodies, receiving of rescue information, rescue activities and transfer to a safe area, the ability related activities corresponding to the command and control ability comprise transmitting of alarm commands, analyzing of alarm signals, monitoring activities, control activities and designation of search plans, and the ability related activities corresponding to the assistance ability comprise local assistance and execution of search;
a second module: for constructing a capability index system from the architectural design data;
a third module: the system is used for acquiring system structure experiment data, importing the experiment data into a capacity index system and determining the capacity index grade;
wherein, the first module still includes the following unit:
a fifth unit: the experimental scheme is a scheme set for measuring each ability effect index, each ability effect index is used as an experimental scheme in the setting process of the experimental scheme, and then the relevant indexes of the ability associated activities are used as the experimental factors of the corresponding ability effect indexes according to the ability associated activities associated with each ability effect index;
a sixth unit: for determining the experimental level of each experimental factor;
a seventh unit: the system comprises a plurality of capacity effect indexes, a plurality of test factors and a plurality of test samples, wherein the capacity effect indexes are used for generating test samples according to the test schemes and the test levels, each capacity effect index-related test scheme can correspond to a plurality of test samples, and different test samples are combinations of a plurality of test factors at different levels;
an eighth unit: the system structure testing device is used for obtaining an experimental structure according to experimental samples to serve as the system structure experimental data, selecting any corresponding experimental sample for each experimental scheme to obtain a combination of the experimental samples of a plurality of experimental schemes, namely a design scheme of the system structure under the scene, and comparing the test result of the experimental sample of any experimental scheme with a measurement standard of the capability effect index in the system structure design data to obtain the capability index grade of the capability effect index corresponding to each experimental scheme;
a fourth module: and the fourth module is used for calculating the system maturity according to the capability index grade of each capability effect index so as to evaluate the design scheme of the system structure according to the system maturity, and a maturity calculation method is required to be selected before calculating the system maturity, wherein the maturity calculation method comprises a weighted sum-of-sums method or a bucket method.
4. The system for evaluating an architecture based on design data and experimental data as claimed in claim 3, wherein the weighting and summing method calculates the weights according to a matrix method or the weights are directly input by a user, and then the levels of the various capability and effect indexes are gathered to obtain the overall system maturity; the bucket rule is that the lowest value of the capacity index grade is taken as the system maturity.
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| CN103150476A (en) * | 2013-03-13 | 2013-06-12 | 北京理工大学 | System efficiency evaluation method based on data station field |
| CN105825022A (en) * | 2016-03-24 | 2016-08-03 | 中国人民解放军装甲兵工程学院 | Multi-Agent-based dynamic equipment security system efficiency evaluation method and system |
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| US20120197686A1 (en) * | 2011-01-31 | 2012-08-02 | Accretive Technologies, Inc. | Predictive deconstruction of dynamic complexity |
| CN103150476A (en) * | 2013-03-13 | 2013-06-12 | 北京理工大学 | System efficiency evaluation method based on data station field |
| CN105825022A (en) * | 2016-03-24 | 2016-08-03 | 中国人民解放军装甲兵工程学院 | Multi-Agent-based dynamic equipment security system efficiency evaluation method and system |
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