CN116414360A - Artificial intelligence-based application system integrated management method and system - Google Patents
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Abstract
The application relates to the technical field of system integrated management, and provides an application system integrated management method and system based on artificial intelligence, comprising the following steps: the method comprises the steps of interacting system data of an application system, performing multi-granularity segmentation on functional units of equipment to obtain multi-granularity segmentation results, wherein the multi-granularity segmentation results comprise association constraint of the functional units; performing task decomposition on the integrated task to obtain a subtask grade identification; inputting the multi-granularity segmentation result and the integration task into a function integration model, and outputting an integration scheme; performing association constraint calculation on the integrated scheme; performing task execution evaluation on the integrated scheme; and carrying out integrated scheme screening through the task execution evaluation value and the associated constraint evaluation value to generate an integrated management scheme. The method can solve the technical problem of poor integration quality of the application system caused by imperfect consideration of factors in various aspects in the process of integrated management of the application system, and can improve the scientificity and rationality of the integrated application system.
Description
Technical Field
The application relates to the technical field of system integrated management, in particular to an application system integrated management method and system based on artificial intelligence.
Background
Application system integration refers to a service that combines software, hardware, and communication technologies to solve information processing problems for users. The integration of the application system is required to adhere to a certain principle and mainly comprises a plurality of indexes such as a practicality principle, an economical principle, an innovation principle, a normalization principle, a safety principle and an expansibility principle. In the traditional application system integration process, comprehensive factors in multiple aspects are not comprehensively considered, so that the application system integration cannot meet the user requirements.
In summary, in the prior art, there is a technical problem that the integration quality of the application system is poor due to imperfect consideration of various factors in the process of integrated management of the application system.
Disclosure of Invention
Based on the above, it is necessary to provide an application system integrated management method and system based on artificial intelligence.
An application system integrated management method based on artificial intelligence, the method comprises the following steps: the method comprises the steps of interacting system data of an application system, and carrying out multi-granularity segmentation on functional units of equipment according to the system data to obtain multi-granularity segmentation results, wherein the multi-granularity segmentation results comprise association constraints of the functional units; acquiring an integrated task, and performing task decomposition on the integrated task to acquire a subtask grade identification; inputting the multi-granularity segmentation result and the integration task into a functional integration model, and outputting N integration schemes; performing association constraint calculation on the N integration schemes to generate association constraint evaluation values; performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values; and screening the N integration schemes through the task execution evaluation value and the association constraint evaluation value to generate an integration management scheme.
In one embodiment, the method further comprises: performing adaptation analysis of functional units on the integrated task and the multi-granularity segmentation result; adding a functional unit according to the adaptive analysis result; replacing the same functional units in the N integration schemes by the newly added functional units to generate M newly added integration schemes; and adding the M newly added integration schemes to the N integration schemes, and generating the integration management scheme according to an addition result.
In one embodiment, the method further comprises: setting an economical constraint coefficient; acquiring a unit new value of the newly-added functional unit, and taking the unit new value as basic value data; carrying out economic analysis on M newly-added integration schemes through the basic value data and the economic constraint coefficients to generate economic analysis results; and carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the economic analysis result.
In one embodiment, the method further comprises: setting an execution constraint coefficient of task execution; performing scheme execution analysis of the M newly added integration schemes and the N integration schemes through the execution constraint coefficients to generate execution analysis results; and carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the execution analysis result and the economic analysis result.
In one embodiment, the method further comprises: extracting a system stability coefficient of the application system; carrying out scheme comparison weighted calculation of N integration schemes and the M newly added integration schemes through the system stability coefficient; and finishing the scheme screening according to the weighted calculation result.
In one embodiment, the method further comprises: obtaining unit basic level information of the functional unit; performing viscosity evaluation on the units according to the unit foundation level information to generate viscosity constraint values; and generating the association constraint of the functional unit through the sticky constraint value.
In one embodiment, the method further comprises: generating a unit synergistic coefficient in the multi-granularity segmentation result through historical data; calculating the total solution synergy value of the N integrated solutions based on the unit synergy coefficients to obtain a synergy reference value; and screening the N integration schemes according to the cooperative reference value, the task execution evaluation value and the association constraint evaluation value to generate an integration management scheme.
An artificial intelligence based application system integrated management system comprising:
the system comprises a functional unit multi-granularity segmentation module, a multi-granularity segmentation module and a multi-granularity segmentation module, wherein the functional unit multi-granularity segmentation module is used for interacting system data of an application system, and performing multi-granularity segmentation on a functional unit of equipment according to the system data to obtain a multi-granularity segmentation result, and the multi-granularity segmentation result comprises association constraint of the functional unit;
the subtask grade identification obtaining module is used for acquiring and obtaining an integrated task, and decomposing the task of the integrated task to obtain a subtask grade identification;
the integration scheme output module is used for inputting the multi-granularity segmentation result and the integration task into a functional integration model and outputting N integration schemes;
the association constraint computing module is used for carrying out association constraint computation on the N integration schemes and generating association constraint evaluation values;
the task execution evaluation module is used for performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values;
and the integrated management scheme generation module is used for carrying out the N integrated scheme screening according to the task execution evaluation value and the association constraint evaluation value to generate an integrated management scheme.
The application system integrated management method and system based on the artificial intelligence can solve the technical problem of poor integration quality of the application system caused by imperfect consideration of various factors in the process of integrated management of the application system. Firstly, carrying out different granularity segmentation on functional units of equipment according to system data to obtain a multi-granularity segmentation result, wherein the multi-granularity segmentation result is a functional unit set under different segmentation standards and comprises association constraint among the functional units; performing task decomposition on the integrated task, and performing grade identification on the decomposed subtasks according to the importance degree of the task; constructing a functional integration model, and inputting the multi-granularity segmentation result and the integration task into the functional integration model to perform functional unit random combination to obtain N integration schemes; performing association constraint calculation according to the N integration schemes and the integration tasks to generate association constraint evaluation values; performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values; obtaining a unit cooperative coefficient in the multi-granularity segmentation result through historical data, and calculating a scheme total cooperative value of the N integrated schemes according to the unit cooperative coefficient to obtain a cooperative reference value; and finally, screening the N integration schemes according to the task execution evaluation value, the association constraint evaluation value and the cooperative reference value to obtain an integration management scheme. By the method, scientificity and rationality of application system integration can be improved.
The foregoing description is merely an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
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FIG. 1 is a schematic flow chart of an application system integrated management method based on artificial intelligence;
FIG. 2 is a schematic flow chart of generating association constraints of functional units in an artificial intelligence-based integrated management method for an application system;
FIG. 3 is a schematic flow chart of an integrated management scheme generated in an artificial intelligence based integrated management method for an application system;
fig. 4 is a schematic structural diagram of an application system integrated management system based on artificial intelligence.
Reference numerals illustrate: the system comprises a functional unit multi-granularity segmentation module 1, a subtask grade identification obtaining module 2, an integration scheme output module 3, an association constraint calculation module 4, a task execution evaluation module 5 and an integration management scheme generation module 6.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
As shown in fig. 1, the present application provides an artificial intelligence based integrated management method for an application system, where the method includes:
step S100: the method comprises the steps of interacting system data of an application system, and carrying out multi-granularity segmentation on functional units of equipment according to the system data to obtain multi-granularity segmentation results, wherein the multi-granularity segmentation results comprise association constraints of the functional units;
as shown in fig. 2, in one embodiment, step S100 of the present application further includes:
step S110: obtaining unit basic level information of the functional unit;
step S120: performing viscosity evaluation on the units according to the unit foundation level information to generate viscosity constraint values;
step S130: and generating the association constraint of the functional unit through the sticky constraint value.
Specifically, system data of an application system is obtained, the application system consists of the application system, system software and system hardware, the system data refers to data which can be possibly segmented in theory, such as attribute data, multi-granularity segmentation is carried out on functional units of equipment according to the system data, the multi-granularity segmentation refers to segmentation of the equipment according to different segmentation standards, multi-granularity segmentation results are obtained, the multi-granularity segmentation results comprise a plurality of different functional unit sets, and the functional units are part of functions of the equipment. Wherein the multi-granularity segmentation result comprises an association constraint of a functional unit. Obtaining unit base level information of the functional units, wherein the unit base level information is used for expressing the association degree between the functional units and the device functions, and the unit base level information can be set in a user-defined way by a person skilled in the art, for example: when the equipment function is a heat dissipation function, the association degree of the heat dissipation fan and the equipment function is higher compared with the display card, and when the equipment function is the enhanced image quality, the association degree of the display card and the heat dissipation fan is higher compared with the equipment function. And carrying out viscosity evaluation of the units according to the unit foundation level information, wherein the viscosity evaluation refers to the association degree of the functional units and the functions of the equipment, generating viscosity constraint values, wherein the viscosity constraint values are used for representing the integrity of any functional unit, the higher the viscosity constraint values are, the higher the viscosity degree is indicated, specific numerical values of the viscosity constraint values can be set by a user in the field, and finally, the association constraint of the functional units is generated according to the viscosity constraint values. By obtaining the multi-granularity segmentation result, support is provided for generating an integration scheme in the next step.
Step S200: acquiring an integrated task, and performing task decomposition on the integrated task to acquire a subtask grade identification;
step S300: inputting the multi-granularity segmentation result and the integration task into a functional integration model, and outputting N integration schemes;
specifically, a system integration task is obtained, wherein the system integration task comprises task types such as hardware integration, software integration, data and information integration and the like, the task is decomposed to obtain a plurality of subtasks, subtask grades are obtained according to the importance degree of the subtasks on the integration task, the higher the importance degree is, the higher the subtask grades are, and grade identification is carried out on the subtasks according to the subtask grades.
A functional integration model is constructed, which can be constructed based on a neural network, in which a large amount of knowledge and experience related to functional integration are stored, can be inferred and judged based on the stored knowledge and experience, and can be updated continuously. And inputting the multi-granularity segmentation result and the integration task into the functional integration model to perform random matching of integration schemes, and obtaining N integration schemes. And through generating the N integration schemes, support is provided for screening the integration schemes in the next step.
Step S400: performing association constraint calculation on the N integration schemes to generate association constraint evaluation values;
step S500: performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values;
specifically, association constraint calculation is performed on each functional unit in the N integration schemes according to association constraint of the functional unit, addition summation is performed on association constraint calculation results of each functional unit, and the summation result of each integration scheme is used as an association constraint evaluation value corresponding to the integration scheme to obtain association constraint evaluation values of the N integration schemes. And by obtaining the association constraint evaluation value, an analysis index is provided for screening the integrated scheme in the next step.
Performing evaluation on the target integrated task according to the subunits in the N integrated schemes, wherein the result of performing evaluation is represented by the task completion degree, for example: the target integrated task is a heat dissipation task, wherein one functional unit can complete 20% of the heat dissipation task, and the task completion degree of the functional unit is 20%. And multiplying the task execution evaluation result of each functional unit in the N integration schemes by the corresponding task completion degree to carry out summation and addition to obtain N task execution evaluation values corresponding to the N integration schemes. And generating the task execution evaluation value to provide a screening basis for screening the next step of integration scheme.
Step S600: and screening the N integration schemes through the task execution evaluation value and the association constraint evaluation value to generate an integration management scheme.
In one embodiment, step S600 of the present application further includes:
step S610: performing adaptation analysis of functional units on the integrated task and the multi-granularity segmentation result;
step S620: adding a functional unit according to the adaptive analysis result;
step S630: replacing the same functional units in the N integration schemes by the newly added functional units to generate M newly added integration schemes;
specifically, the adaptation analysis of the functional unit is performed on the integration task and the multi-granularity segmentation result, where the adaptation analysis refers to determining whether the functional unit meets the requirement of the integration task, for example: assuming that the integration task is 100 in heat dissipation capacity, and the heat dissipation capacity of each functional unit is 10, 10 functional units can meet the integration task; assuming that the integration task is the operation smoothness of the system, one i7 processor is required to meet the requirement, but each functional unit is the processor of i3, a plurality of functional units cannot meet the integration task, and an adaptation analysis result of the functional units is obtained. And when the adaptation analysis result of the functional unit is unsatisfiable, the functional unit needs to be newly added according to the integration task demand. And replacing the same functional units in the N integration schemes by the newly added functional units to generate M newly added integration schemes. The utility principle in the integrated management of the application system can be satisfied by adding the functional units.
Step S640: and adding the M newly added integration schemes to the N integration schemes, and generating the integration management scheme according to an addition result.
In one embodiment, step S640 of the present application further includes:
step S641: setting an economical constraint coefficient;
step S642: acquiring a unit new value of the newly-added functional unit, and taking the unit new value as basic value data;
step S643: carrying out economic analysis on M newly-added integration schemes through the basic value data and the economic constraint coefficients to generate economic analysis results;
step S644: and carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the economic analysis result.
Specifically, an economic constraint coefficient is set, which can be set by a person skilled in the art in a customized manner, and is used to limit the cost of the newly added unit. For example: the economic constraint coefficient can be set according to the increasing proportion of the cost of the newly-added unit, and the economic constraint coefficient is set to be 3 on the assumption that the cost of the newly-added unit is 3 times that of the original functional unit. And performing functional value analysis on the newly added units, and obtaining the newly added values of the units according to the functional value analysis result. For example: assuming that the processors of i7 are replaced with the processors of i3, the system operation speed is improved by 5 times, the unit added value can be set to 5, and the unit added value is taken as basic value data. Carrying out economic analysis of M newly-added integration schemes through the basic value data and the economic constraint coefficients, wherein the economic analysis refers to comparing the basic value data with the economic constraint coefficients, if the basic value data is larger than the economic constraint data, the actual value of the newly-added functional units is larger than cost, and the economic analysis result is positive; if the basic value data is smaller than the economic constraint data, the actual value of the newly added functional unit is smaller than the cost, and the economic analysis result is negative; and generating the economic analysis result. Finally, screening the M newly-added integration schemes and the N integration schemes according to the economic analysis result, and when the economic analysis result is positive, reserving the newly-added integration scheme corresponding to the economic analysis result and deleting the integration scheme corresponding to the economic analysis result; when the economic analysis result is negative, deleting the newly added integration scheme corresponding to the economic analysis result, and reserving the integration scheme corresponding to the economic analysis result; by setting an economic constraint coefficient and comparing with the new added value of the unit, the practicability and the economical efficiency of the system integration can be comprehensively evaluated, so that the rationality of the application system integration is improved.
In one embodiment, step S640 of the present application further includes:
step S645: setting an execution constraint coefficient of task execution;
step S646: performing scheme execution analysis of the M newly added integration schemes and the N integration schemes through the execution constraint coefficients to generate execution analysis results;
step S647: and carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the execution analysis result and the economic analysis result.
Specifically, an execution constraint coefficient of task execution is set, and the execution constraint coefficient is used for judging an execution result of the integration scheme, wherein a specific value of the execution constraint coefficient can be set in a customized manner based on actual conditions by a person skilled in the art. For example: the execution constraint coefficient may be set to 80% of the task execution completion. Judging the M newly added integration schemes and the N integration schemes according to the execution constraint coefficients, and generating an execution analysis result, wherein the execution analysis result comprises the execution constraint coefficients and the execution constraint coefficients which are not satisfied. And then screening the M newly-added integrated schemes and the N integrated schemes according to the execution constraint coefficients, reserving schemes which are in the M newly-added integrated schemes and the N integrated schemes and have the execution analysis results meeting the execution constraint coefficients, and deleting the schemes which do not meet the execution constraint coefficients. And deleting the M newly added integration schemes and the N integration schemes by setting an execution constraint coefficient, so that the practicability principle in the integrated management of the application system can be met.
In one embodiment, step S640 of the present application further includes:
step S648: extracting a system stability coefficient of the application system;
step S649: carrying out scheme comparison weighted calculation of N integration schemes and the M newly added integration schemes through the system stability coefficient;
step S6410: and finishing the scheme screening according to the weighted calculation result.
Specifically, a system stability coefficient of the application system is extracted, the system stability coefficient is used for representing stability of each functional unit in the application system, the larger the system stability coefficient is, the higher the stability of the functional unit is indicated, and specific values of the system stability coefficient can be set in a self-defined manner by a person skilled in the art. And multiplying the functional units of each of the N integration schemes by corresponding system stability coefficients to add, so as to obtain weighted calculation results of the N integration schemes, namely system stability results. And multiplying the functional units of each newly added integration scheme in the M newly added integration schemes by corresponding system stability coefficients to obtain weighted calculation results of the M newly added integration schemes, namely system stability results. And setting a weighted calculation result threshold, wherein the weighted calculation result threshold can be set by a person skilled in the art in a self-defined manner, screening the weighted calculation result according to the weighted calculation result threshold, reserving the integration schemes and the newly added integration schemes of which the N integration schemes and the M newly added integration schemes meet the weighted calculation result threshold, and deleting the integration schemes and the newly added integration schemes which do not meet the weighted calculation result threshold. And the N integration schemes and the M newly added integration schemes are screened by setting system stability coefficients, so that the reliability principle in the integrated management of the application system can be met. And finally, adding the M newly added integration schemes to the N integration schemes according to scheme screening results, and generating the integration management scheme according to the adding results.
As shown in fig. 3, in one embodiment, step S600 of the present application further includes:
step S650: generating a unit synergistic coefficient in the multi-granularity segmentation result through historical data;
step S660: calculating the total solution synergy value of the N integrated solutions based on the unit synergy coefficients to obtain a synergy reference value;
step S670: and screening the N integration schemes according to the cooperative reference value, the task execution evaluation value and the association constraint evaluation value to generate an integration management scheme.
Specifically, the adaptation condition among the functional units in the multi-granularity segmentation result is analyzed according to historical data to obtain a unit coordination coefficient, wherein the unit coordination coefficient is used for representing the adaptation degree between the two functional units, and the larger the unit coordination coefficient is, the higher the adaptation degree between the two functional units is. And adding and summing the unit synergy coefficients between two adjacent functional units in the N integration schemes to obtain a scheme total synergy value of the N integration schemes, and taking the scheme total synergy value as a synergy reference value of the N integration schemes. Presetting a cooperative reference value standard coefficient, a task execution evaluation value standard coefficient and an associated constraint evaluation value standard coefficient, wherein the cooperative reference value standard coefficient, the task execution evaluation value standard coefficient and the associated constraint evaluation value standard coefficient can be custom set by a person skilled in the art based on actual conditions. And finally, extracting the integration schemes of which the collaborative reference values of the integration schemes in the N integration schemes meet the collaborative reference value standard coefficient, the task execution evaluation value meets the task execution evaluation value standard coefficient and the associated constraint evaluation value meets the associated constraint evaluation value standard coefficient, and generating the integrated management scheme. The method solves the technical problem of poor integration quality of the application system caused by imperfect consideration of factors in various aspects in the process of system integration management, and can improve the scientificity and rationality of the integration of the application system.
In one embodiment, as shown in FIG. 4, an artificial intelligence based integrated management system for an application system is provided, comprising: the system comprises a functional unit multi-granularity segmentation module 1, a subtask grade identification obtaining module 2, an integration scheme output module 3, an association constraint calculation module 4, a task execution evaluation module 5 and an integration management scheme generation module 6, wherein:
the system comprises a functional unit multi-granularity segmentation module 1, wherein the functional unit multi-granularity segmentation module 1 is used for interacting system data of an application system, and carrying out multi-granularity segmentation on functional units of equipment according to the system data to obtain multi-granularity segmentation results, wherein the multi-granularity segmentation results comprise association constraints of the functional units;
the subtask grade identification obtaining module 2 is used for acquiring and obtaining an integrated task, and decomposing the integrated task to obtain a subtask grade identification;
the integration scheme output module 3 is used for inputting the multi-granularity segmentation result and the integration task into a functional integration model and outputting N integration schemes;
the association constraint computing module 4 is used for performing association constraint computation on the N integration schemes to generate association constraint evaluation values;
the task execution evaluation module 5 is used for performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values;
and the integrated management scheme generation module 6 is used for carrying out the N integrated scheme screening according to the task execution evaluation value and the association constraint evaluation value to generate an integrated management scheme.
In one embodiment, the system further comprises:
the adaptation analysis module is used for carrying out adaptation analysis of the functional units on the integrated tasks and the multi-granularity segmentation result;
the function unit adding module is used for adding a function unit according to the adaptive analysis result;
the same-function unit replacement module is used for replacing the same-function units in the N integration schemes by the newly added function units to generate M newly added integration schemes;
and the integrated management scheme generation module is used for adding the M newly added integrated schemes to the N integrated schemes and generating the integrated management scheme according to an addition result.
In one embodiment, the system further comprises:
the economic constraint coefficient setting module is used for setting economic constraint coefficients;
the basic value data acquisition module is used for acquiring the unit newly-added value of the newly-added functional unit and taking the unit newly-added value as basic value data;
the economic analysis module is used for carrying out economic analysis of M newly-added integration schemes through the basic value data and the economic constraint coefficients to generate economic analysis results;
and the scheme screening module is used for carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the economic analysis result.
In one embodiment, the system further comprises:
the execution constraint coefficient setting module is used for setting an execution constraint coefficient of task execution;
the scheme execution analysis module is used for carrying out scheme execution analysis of the M newly-added integrated schemes and the N integrated schemes through the execution constraint coefficients to generate execution analysis results;
and the scheme screening module is used for carrying out scheme screening of the M newly added integrated schemes and the N integrated schemes according to the execution analysis result and the economic analysis result.
In one embodiment, the system further comprises:
the system stability coefficient extraction module is used for extracting the system stability coefficient of the application system;
the scheme comparison weighting calculation module is used for carrying out scheme comparison weighting calculation of N integration schemes and the M newly added integration schemes through the system stability coefficient;
and the scheme screening completion module is used for completing the scheme screening according to the weighted calculation result.
In one embodiment, the system further comprises:
the unit foundation level information obtaining module is used for obtaining unit foundation level information of the functional unit;
the viscosity constraint value generation module is used for evaluating the viscosity of the unit according to the unit foundation level information and generating a viscosity constraint value;
and the association constraint generation module is used for generating association constraints of the functional units through the sticky constraint values.
In one embodiment, the system further comprises:
the unit co-operation coefficient generation module is used for generating unit co-operation coefficients in the multi-granularity segmentation result through historical data;
the cooperative reference value obtaining module is used for calculating the total cooperative values of the N integrated schemes based on the unit cooperative coefficients to obtain cooperative reference values;
and the integrated management scheme generation module is used for carrying out the screening of the N integrated schemes according to the collaborative reference value, the task execution evaluation value and the association constraint evaluation value to generate an integrated management scheme.
In summary, the application provides an application system integrated management method and system based on artificial intelligence, which have the following technical effects:
1. the technical problem of poor integrated quality of the application system due to imperfect consideration of factors in various aspects in the integrated management process of the application system is solved, and the scientificity and rationality of the integrated application system can be improved by carrying out N integrated scheme screening according to the collaborative reference value, the task execution evaluation value and the associated constraint evaluation value to generate an integrated management scheme.
2. By setting an economic constraint coefficient and comparing with the new added value of the unit, the practicability and the economical efficiency of the system integration can be comprehensively evaluated, so that the rationality of the application system integration is improved. And deleting the M newly added integration schemes and the N integration schemes by setting an execution constraint coefficient, so that the practicability principle in the integrated management of the application system can be met. And the N integration schemes and the M newly added integration schemes are screened by setting system stability coefficients, so that the reliability principle in the integrated management of the application system can be met.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (8)
1. The integrated management method of the application system based on the artificial intelligence is characterized by comprising the following steps:
the method comprises the steps of interacting system data of an application system, and carrying out multi-granularity segmentation on functional units of equipment according to the system data to obtain multi-granularity segmentation results, wherein the multi-granularity segmentation results comprise association constraints of the functional units;
acquiring an integrated task, and performing task decomposition on the integrated task to acquire a subtask grade identification;
inputting the multi-granularity segmentation result and the integration task into a functional integration model, and outputting N integration schemes;
performing association constraint calculation on the N integration schemes to generate association constraint evaluation values;
performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values;
and screening the N integration schemes through the task execution evaluation value and the association constraint evaluation value to generate an integration management scheme.
2. The method of claim 1, wherein the method further comprises:
performing adaptation analysis of functional units on the integrated task and the multi-granularity segmentation result;
adding a functional unit according to the adaptive analysis result;
replacing the same functional units in the N integration schemes by the newly added functional units to generate M newly added integration schemes;
and adding the M newly added integration schemes to the N integration schemes, and generating the integration management scheme according to an addition result.
3. The method of claim 2, wherein the method further comprises:
setting an economical constraint coefficient;
acquiring a unit new value of the newly-added functional unit, and taking the unit new value as basic value data;
carrying out economic analysis on M newly-added integration schemes through the basic value data and the economic constraint coefficients to generate economic analysis results;
and carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the economic analysis result.
4. A method as claimed in claim 3, wherein the method further comprises:
setting an execution constraint coefficient of task execution;
performing scheme execution analysis of the M newly added integration schemes and the N integration schemes through the execution constraint coefficients to generate execution analysis results;
and carrying out scheme screening of the M newly added integration schemes and the N integration schemes according to the execution analysis result and the economic analysis result.
5. The method of claim 4, wherein the method further comprises:
extracting a system stability coefficient of the application system;
carrying out scheme comparison weighted calculation of N integration schemes and the M newly added integration schemes through the system stability coefficient;
and finishing the scheme screening according to the weighted calculation result.
6. The method of claim 1, wherein the method further comprises:
obtaining unit basic level information of the functional unit;
performing viscosity evaluation on the units according to the unit foundation level information to generate viscosity constraint values;
and generating the association constraint of the functional unit through the sticky constraint value.
7. The method of claim 1, wherein the method further comprises:
generating a unit synergistic coefficient in the multi-granularity segmentation result through historical data;
calculating the total solution synergy value of the N integrated solutions based on the unit synergy coefficients to obtain a synergy reference value;
and screening the N integration schemes according to the cooperative reference value, the task execution evaluation value and the association constraint evaluation value to generate an integration management scheme.
8. An artificial intelligence based application system integrated management system, the system comprising:
the system comprises a functional unit multi-granularity segmentation module, a multi-granularity segmentation module and a multi-granularity segmentation module, wherein the functional unit multi-granularity segmentation module is used for interacting system data of an application system, and performing multi-granularity segmentation on a functional unit of equipment according to the system data to obtain a multi-granularity segmentation result, and the multi-granularity segmentation result comprises association constraint of the functional unit;
the subtask grade identification obtaining module is used for acquiring and obtaining an integrated task, and decomposing the task of the integrated task to obtain a subtask grade identification;
the integration scheme output module is used for inputting the multi-granularity segmentation result and the integration task into a functional integration model and outputting N integration schemes;
the association constraint computing module is used for carrying out association constraint computation on the N integration schemes and generating association constraint evaluation values;
the task execution evaluation module is used for performing task execution evaluation on the N integration schemes through the subtask grade identifiers to generate task execution evaluation values;
and the integrated management scheme generation module is used for carrying out the N integrated scheme screening according to the task execution evaluation value and the association constraint evaluation value to generate an integrated management scheme.
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