CN112580258A - Engine design simulation artificial intelligence analysis method and device based on data driving - Google Patents
Engine design simulation artificial intelligence analysis method and device based on data driving Download PDFInfo
- Publication number
- CN112580258A CN112580258A CN202011483801.XA CN202011483801A CN112580258A CN 112580258 A CN112580258 A CN 112580258A CN 202011483801 A CN202011483801 A CN 202011483801A CN 112580258 A CN112580258 A CN 112580258A
- Authority
- CN
- China
- Prior art keywords
- data
- simulation
- model
- simulation data
- analysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000004088 simulation Methods 0.000 title claims abstract description 166
- 238000013461 design Methods 0.000 title claims abstract description 82
- 238000004458 analytical method Methods 0.000 title claims abstract description 59
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 52
- 230000008569 process Effects 0.000 claims abstract description 41
- 238000012545 processing Methods 0.000 claims abstract description 35
- 238000007405 data analysis Methods 0.000 claims abstract description 12
- 238000012938 design process Methods 0.000 claims description 10
- 230000006399 behavior Effects 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000000354 decomposition reaction Methods 0.000 claims description 7
- 230000000007 visual effect Effects 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 description 10
- 230000008901 benefit Effects 0.000 description 4
- 238000010801 machine learning Methods 0.000 description 4
- 238000003754 machining Methods 0.000 description 3
- 230000002265 prevention Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000004083 survival effect Effects 0.000 description 2
- 208000025721 COVID-19 Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/26—Visual data mining; Browsing structured data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0633—Workflow analysis
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- Human Resources & Organizations (AREA)
- Software Systems (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Quality & Reliability (AREA)
- Evolutionary Computation (AREA)
- Educational Administration (AREA)
- General Business, Economics & Management (AREA)
- Geometry (AREA)
- Game Theory and Decision Science (AREA)
- Computer Hardware Design (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Medical Informatics (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Computational Linguistics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a data-driven engine design simulation artificial intelligence analysis method and a data-driven engine design simulation artificial intelligence analysis device, wherein the method comprises the following steps: acquiring initial simulation data of a transmitter design in a data simulation process; processing and modeling the initial simulation data to obtain final simulation data; and performing data analysis on the final simulation data, and providing a service corresponding to the analysis result according to the content showing the corresponding analysis result. The method improves the flexibility and the intelligent level of design simulation, and enables the design simulation process to be changed from a primary process to an intelligent process, thereby greatly improving the efficiency and the performance.
Description
Technical Field
The invention relates to the technical field of design simulation, in particular to an engine design simulation artificial intelligence analysis method and device based on data driving.
Background
In the related art, design simulation is generally based on a flow, a design simulation flow is set up by a master and a member designer, and then a design simulation tool is called by each member designer according to the flow to carry out design activities.
However, there is still a need in the related art for flow-driven design simulation activities that greatly reduce intelligence and efficiency. A solution is needed.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, one objective of the present invention is to provide an artificial intelligence analysis method for engine design simulation based on data driving, which improves the flexibility and intelligence level of design simulation, and makes the design simulation process change from a primary process to an intelligent process, thereby greatly improving efficiency and performance.
The invention also aims to provide a data-driven engine design simulation artificial intelligence analysis device.
It is a further object of the invention to propose an electronic device.
It is yet another object of the present invention to provide a computer-readable storage medium.
In order to achieve the above object, an embodiment of the invention provides a data-driven engine design simulation artificial intelligence analysis method, which includes the following steps: acquiring initial simulation data of a transmitter design in a data simulation process; processing and modeling the initial simulation data to obtain final simulation data; and performing data analysis on the final simulation data, and providing a service corresponding to the analysis result according to the content showing the corresponding analysis result.
According to the artificial intelligent analysis method for the engine design simulation based on the data driving, provided by the embodiment of the invention, the design simulation data is mined through means of big data, machine learning, artificial intelligent analysis and the like, the design process is refined, the design simulation process is automatically constructed, the design simulation model is driven, and the design simulation activity based on the model is developed, so that the limitation of the traditional process-driven design simulation activity is eliminated, the flexibility and the intelligent level of the design simulation are improved, the design simulation process is changed from a primary process to an intelligent process, and the efficiency and the performance are greatly improved.
In addition, the artificial intelligence analysis method based on the data-driven engine design simulation according to the above embodiment of the present invention may further have the following additional technical features:
further, in one embodiment of the invention, the simulation data includes one or more of designer behavior data, design process data, and simulation result data.
Further, in an embodiment of the present invention, before the processing and modeling the initial simulation data, the method further includes: generating a business model for solving the decomposition and programming of the business layer; and/or generating a domain model for performing abstract processing on the business model; and/or generating a logical model for database-level logical representation of the concept entities and the relationships between the entities of the domain model; and/or generating a physical model for solving the physics, chemistry and performance of the logic model aiming at different relational databases.
Further, in an embodiment of the present invention, the processing and modeling the initial simulation data includes: and inputting the initial simulation data into the business model, the field model, the logic model and/or the physical model to obtain the final simulation data.
Further, in an embodiment of the present invention, the performing data analysis on the final simulation data includes: performing visual presentation on the final simulation data; and/or index calculation is carried out on the final simulation data; and/or using the final simulation data to train a preset model; and/or portray a user representation based on the simulation data.
In order to achieve the above object, an embodiment of another aspect of the present invention provides an artificial intelligence analysis apparatus for engine design simulation based on data driving, including: the acquisition module is used for acquiring initial simulation data of the transmitter design in the data simulation process; the processing module is used for processing and modeling the initial simulation data to obtain final simulation data; and the analysis module is used for carrying out data analysis on the final simulation data, and providing services corresponding to the analysis results according to the contents showing the corresponding analysis results.
The artificial intelligent analysis device for the engine design simulation based on the data driving provided by the embodiment of the invention excavates design simulation data through means such as big data, machine learning and artificial intelligent analysis, extracts the design process, automatically constructs the design simulation process, drives the design simulation model and develops the design simulation activity based on the model, thereby getting rid of the limitation of the traditional process driven design simulation activity, improving the flexibility and the intelligent level of the design simulation, converting the design simulation process from a primary process to an intelligent process and further greatly improving the efficiency and the performance.
In addition, the artificial intelligence analysis device for engine design simulation based on data driving according to the above embodiment of the present invention may further have the following additional technical features:
further, in one embodiment of the invention, the simulation data includes one or more of designer behavior data, design process data, and simulation result data.
Further, in an embodiment of the invention, before the processing and modeling the initial simulation data, the processing module is further configured to: generating a business model for solving the decomposition and programming of the business layer; and/or generating a domain model for performing abstract processing on the business model; and/or generating a logical model for database-level logical representation of the concept entities and the relationships between the entities of the domain model; and/or generating a physical model for solving the physics, chemistry and performance of the logic model aiming at different relational databases.
Further, in an embodiment of the present invention, the processing module is specifically configured to: and inputting the initial simulation data into the business model, the field model, the logic model and/or the physical model to obtain the final simulation data.
Further, in an embodiment of the present invention, the analysis module is specifically configured to: performing visual presentation on the final simulation data; and/or index calculation is carried out on the final simulation data; and/or using the final simulation data to train a preset model; and/or portray a user representation based on the simulation data.
In order to achieve the above object, an embodiment of another aspect of the present invention provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor and configured to perform the data-driven based engine design simulation artificial intelligence analysis method described above.
To achieve the above object, according to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, where the computer program is executed by a processor to implement the above-mentioned artificial intelligence analysis method for engine design simulation based on data driving.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a method for artificial intelligence analysis based on data-driven engine design simulation according to an embodiment of the present invention;
FIG. 2 is a block diagram of an artificial intelligence analysis apparatus for engine design simulation based on data driving according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes an engine design simulation artificial intelligence analysis method and apparatus based on data driving according to an embodiment of the present invention with reference to the accompanying drawings, and first, the engine design simulation artificial intelligence analysis method based on data driving according to an embodiment of the present invention will be described with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for artificial intelligence analysis of engine design simulation based on data driving according to an embodiment of the present invention.
As shown in FIG. 1, the artificial intelligence analysis method for the engine design simulation based on data driving comprises the following steps:
in step S101, initial simulation data of a transmitter design in a data simulation process is collected.
In one embodiment of the invention, the simulation data includes one or more of designer behavior data, design process data, and simulation result data.
Generally, the epidemic situation is high in outbreak, strong in infectivity, wide in diffusivity, high in risk, difficult in prevention and control work task, urgent in time and severe in situation. In the epidemic situation fighting, the new generation information communication technology rapidly developed by big data, cloud computing, artificial intelligence and the like is accelerated to be deeply fused with the fields of traffic, medical treatment, education and the like, so that the organization and execution of epidemic situation prevention and control are more efficient, and data driving also becomes a powerful weapon for fighting the epidemic situation.
The internet, big data and data mining are three elements of a data-driven mode. On the battlefield of resisting COVID-19, the data warfare is completely attacked. Ice-cold data constantly sublimes its value: from global monitoring of epidemic situations to isolation prevention and control of gridding, the method is very promising even in guidance of epidemic situation research and public opinion analysis.
Therefore, the embodiment of the invention can be applied to the intelligent design of the aerospace power engine by analyzing the big data and artificial intelligence.
In particular, the data driver may include four links, data acquisition, data modeling, data analysis, and data decision, each of which is part of the data driver. When data acquisition is carried out, the embodiment of the invention can record the data of the design simulation process through a certain data acquisition means, and the table structure of the design science is structurally stored. The simulation data may include: designer behavior data, design process data, simulation result data, and the like.
It should be noted that the data acquisition process may include two points of interest: one is that data needs to be collected comprehensively and carefully; the other is to carry out scientific storage, and the structured data has value. Structured data, also called row data, is data logically represented and implemented by a two-dimensional table structure, strictly following the data format and length specifications, and mainly stored and managed by a relational database. If the stage is similar to the collection society, people rely on the most original nature resources for nutrition intake and survival, and the nature can obtain what, which can only meet the basic requirements of survival.
In step S102, the initial simulation data is subjected to machining modeling processing to obtain final simulation data.
Further, in an embodiment of the present invention, before the machining modeling processing is performed on the initial simulation data, the method further includes: generating a business model for solving the decomposition and programming of the business layer; and/or generating a domain model for performing abstract processing on the business model; and/or generating a logical model for database-level logical representation of the concept entities of the domain model and the relationships between the entities; and/or generating a physical model that solves the physics, chemistry, and performance of the logical model for different relational databases.
Further, in an embodiment of the present invention, the processing modeling process performed on the initial simulation data includes: and inputting the initial simulation data into a business model, a field model, a logic model and/or a physical model to obtain final simulation data.
It can be understood that the processing modeling processing of the initial simulation data may also be referred to as data processing, and is generally to clean, process, calculate and finally generate the data required by the user for a certain purpose, where the original data is not added with any logic therein, and has a low utilization value.
For example, for an order form, the basic information that each data row is recorded is that a certain sku is placed by a certain user at a certain price at a certain time, but the performance of a single sku is generally not analyzed for value and utilization value, and what is more valuable is the placing behavior of a certain group of skus at a certain time, so that the subsequent decision is more facilitated. This is a process of performing a process modeling process.
Further, data modeling may generally include the following four modeling classifications: business modeling, domain modeling, logical modeling, and physical modeling. Specifically, business modeling can generate a business model, and mainly solves the decomposition and programming of a business layer; the domain modeling can generate a domain model, and mainly comprises the steps of carrying out abstract processing on a business model to generate a domain concept model; the logical modeling can generate a logical model, and mainly carries out database level logical transformation on concept entities and relations among the entities of the field model; the physical modeling can generate a physical model, and mainly solves some specific technical problems of the physical and performance of different relational databases and the like of a logic model. Therefore, according to the application scene of the model, the four models can supplement each other or be independent of each other.
In step S103, the final simulation data is subjected to data analysis, and a service corresponding to the analysis result is provided according to the content showing the corresponding analysis result.
Further, in an embodiment of the present invention, the data analysis of the final simulation data includes: performing visual presentation on the final simulation data; and/or index calculation is carried out on the final simulation data; and/or using the final simulation data to train a preset model; and/or portray a user representation based on the simulation data.
It is understood that data analysis of the final simulated data may be a preliminary stage where the data truly exerts its value, by visually presenting the data, performing index calculations on the data, the data being used to train model algorithms, the data being used to characterize user portraits, and so forth.
It should be noted that the real data driver should be a more intelligent and automatic driver, that is, the entire data link starts to run at the moment the user comes in to decide what content is presented to the designer and what services are provided.
According to the artificial intelligent analysis method for the engine design simulation based on the data driving, provided by the embodiment of the invention, the design simulation data is mined by means of big data, machine learning, artificial intelligent analysis and the like, the design process is refined, the design simulation process is automatically constructed, the design simulation model is driven, and the design simulation activity based on the model is developed, so that the advantage that the traditional process drives the design simulation activity is eliminated, the flexibility and the intelligent level of the design simulation are improved, the design simulation process is changed from a primary process to an intelligent process, and the efficiency and the performance are greatly improved.
Next, an artificial intelligence analysis apparatus for engine design simulation based on data driving according to an embodiment of the present invention will be described with reference to the accompanying drawings.
FIG. 2 is a block diagram of an artificial intelligence analysis device for engine design simulation based on data driving according to an embodiment of the present invention.
As shown in fig. 2, the artificial intelligence analysis device 10 for engine design simulation based on data driving includes: an acquisition module 100, a processing module 200 and an analysis module 300.
The acquisition module 100 is configured to acquire initial simulation data of a transmitter design in a data simulation process. The processing module 200 is configured to perform processing modeling processing on the initial simulation data to obtain final simulation data. The analysis module 300 is configured to perform data analysis on the final simulation data, and provide a service corresponding to the analysis result according to the content of the corresponding analysis result.
Further, in one embodiment of the invention, the simulation data includes one or more of designer behavior data, design process data, and simulation result data.
Further, in an embodiment of the invention, before the machining modeling process is performed on the initial simulation data, the processing module 200 is further configured to: generating a business model for solving the decomposition and programming of the business layer; and/or generating a domain model for performing abstract processing on the business model; and/or generating a logical model for database-level logical representation of the concept entities of the domain model and the relationships between the entities; and/or generating a physical model that solves the physics, chemistry, and performance of the logical model for different relational databases.
Further, in an embodiment of the present invention, the processing module 200 is specifically configured to: and inputting the initial simulation data into a business model, a field model, a logic model and/or a physical model to obtain final simulation data.
Further, in an embodiment of the present invention, the analysis module 300 is specifically configured to: performing visual presentation on the final simulation data; and/or index calculation is carried out on the final simulation data; and/or using the final simulation data to train a preset model; and/or portray a user representation based on the simulation data.
It should be noted that the foregoing explanation of the embodiment of the data-driven-based engine design simulation artificial intelligence analysis method is also applicable to the data-driven-based engine design simulation artificial intelligence analysis apparatus of the embodiment, and details are not repeated here.
According to the artificial intelligent analysis device for the engine design simulation based on the data driving, provided by the embodiment of the invention, the design simulation data is mined by means of big data, machine learning, artificial intelligent analysis and the like, the design process is refined, the design simulation process is automatically constructed, the design simulation model is driven, and the design simulation activity based on the model is developed, so that the advantage that the traditional process drives the design simulation activity is eliminated, the flexibility and the intelligent level of the design simulation are improved, the design simulation process is changed from a primary process to an intelligent process, and the efficiency and the performance are greatly improved.
An embodiment of the present invention provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions configured to perform the above-described data-driven-based engine design simulation artificial intelligence analysis method.
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor, so as to implement the above-mentioned artificial intelligence analysis method for engine design simulation based on data driving.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A data-driven engine design simulation artificial intelligence analysis method is characterized by comprising the following steps:
acquiring initial simulation data of a transmitter design in a data simulation process;
processing and modeling the initial simulation data to obtain final simulation data; and
and performing data analysis on the final simulation data, and providing a service corresponding to the analysis result according to the content showing the corresponding analysis result.
2. The method of claim 1, wherein the simulation data includes one or more of designer behavior data, design process data, and simulation results data.
3. The method of claim 1, further comprising, prior to said processing modeling said initial simulation data:
generating a business model for solving the decomposition and programming of the business layer; and/or
Generating a domain model for performing abstract processing on the business model; and/or
Generating a logical model for performing database-level logicalization on the concept entities of the field model and the relationship between the entities; and/or
And generating a physical model for solving the physics, chemistry and performance of the logic model aiming at different relational databases.
4. The method of claim 3, wherein said processing the initial simulation data to model comprises:
and inputting the initial simulation data into the business model, the field model, the logic model and/or the physical model to obtain the final simulation data.
5. The method of claim 1, wherein the performing data analysis on the final simulation data comprises:
performing visual presentation on the final simulation data; and/or
Performing index calculation on the final simulation data; and/or
Using the final simulation data to train a preset model; and/or
And depicting the user portrait according to the simulation data.
6. An engine design simulation artificial intelligence analytical equipment based on data drive, characterized by, includes:
the acquisition module is used for acquiring initial simulation data of the transmitter design in the data simulation process;
the processing module is used for processing and modeling the initial simulation data to obtain final simulation data; and
and the analysis module is used for carrying out data analysis on the final simulation data and providing services corresponding to the analysis results according to the contents displaying the corresponding analysis results.
7. The apparatus of claim 6, wherein prior to said processing modeling said initial simulation data, said processing module is further configured to:
generating a business model for solving the decomposition and programming of the business layer; and/or
Generating a domain model for performing abstract processing on the business model; and/or
Generating a logical model for performing database-level logicalization on the concept entities of the field model and the relationship between the entities; and/or
And generating a physical model for solving the physics, chemistry and performance of the logic model aiming at different relational databases.
8. The apparatus of claim 6, wherein the analysis module is specifically configured to:
performing visual presentation on the final simulation data; and/or
Performing index calculation on the final simulation data; and/or
Using the final simulation data to train a preset model; and/or
And depicting the user portrait according to the simulation data.
9. An electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor and configured to perform the data-driven based engine design simulation artificial intelligence analysis method of any of claims 1-5.
10. A computer-readable storage medium having stored thereon a computer program, the program being executable by a processor for implementing the data-driven-based engine design simulation artificial intelligence analysis method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011483801.XA CN112580258B (en) | 2020-12-15 | 2020-12-15 | Data-driven-based engine design simulation artificial intelligence analysis method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011483801.XA CN112580258B (en) | 2020-12-15 | 2020-12-15 | Data-driven-based engine design simulation artificial intelligence analysis method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112580258A true CN112580258A (en) | 2021-03-30 |
| CN112580258B CN112580258B (en) | 2024-05-31 |
Family
ID=75135329
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011483801.XA Active CN112580258B (en) | 2020-12-15 | 2020-12-15 | Data-driven-based engine design simulation artificial intelligence analysis method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112580258B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004185539A (en) * | 2002-12-06 | 2004-07-02 | Yunitekku:Kk | Trading area analyzing system, method, program, and record medium |
| EP1659468A2 (en) * | 2004-11-16 | 2006-05-24 | Rockwell Automation Technologies, Inc. | Universal run-time interface for agent-based simulation and control systems |
| US20150178425A1 (en) * | 2013-12-20 | 2015-06-25 | The Procter & Gamble Company | Method for modeling graphics on a flexible form |
| WO2019113508A1 (en) * | 2017-12-07 | 2019-06-13 | Fractal Industries, Inc. | A system and methods for multi-language abstract model creation for digital environment simulations |
| CN110557385A (en) * | 2019-08-22 | 2019-12-10 | 西安电子科技大学 | information hiding access method and system based on behavior confusion, and server |
| CN111597176A (en) * | 2020-05-09 | 2020-08-28 | 山东财经大学 | Teaching simulation training method and system for delaying supply chain generation |
-
2020
- 2020-12-15 CN CN202011483801.XA patent/CN112580258B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004185539A (en) * | 2002-12-06 | 2004-07-02 | Yunitekku:Kk | Trading area analyzing system, method, program, and record medium |
| EP1659468A2 (en) * | 2004-11-16 | 2006-05-24 | Rockwell Automation Technologies, Inc. | Universal run-time interface for agent-based simulation and control systems |
| US20150178425A1 (en) * | 2013-12-20 | 2015-06-25 | The Procter & Gamble Company | Method for modeling graphics on a flexible form |
| WO2019113508A1 (en) * | 2017-12-07 | 2019-06-13 | Fractal Industries, Inc. | A system and methods for multi-language abstract model creation for digital environment simulations |
| CN110557385A (en) * | 2019-08-22 | 2019-12-10 | 西安电子科技大学 | information hiding access method and system based on behavior confusion, and server |
| CN111597176A (en) * | 2020-05-09 | 2020-08-28 | 山东财经大学 | Teaching simulation training method and system for delaying supply chain generation |
Non-Patent Citations (5)
| Title |
|---|
| 化柏林;李广建;: "智能情报分析系统的架构设计与关键技术研究", 图书与情报, no. 06 * |
| 吴丹;陆柳杏;: "智慧信息服务大数据分析框架", 图书与情报, no. 02 * |
| 崔晓龙;郭茜;边胜琴;张德政;: "支持模型复用的通用大数据分析平台", 实验室研究与探索, no. 07 * |
| 王军平;张文生;王勇飞;孙正雅;: "面向大数据领域的事理认知图谱构建与推断分析", 中国科学:信息科学, no. 07 * |
| 龚成勇;韩伟;王之君;何香如;: "构建虚拟仿真实验教学多元评价体系――以《水电站》课程虚拟仿真实验为例", 中国教育信息化, no. 06 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112580258B (en) | 2024-05-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| McCown | Locating agricultural decision support systems in the troubled past and socio-technical complexity of ‘models for management’ | |
| Reddy et al. | Knowledge based engineering: notion, approaches and future trends | |
| CN112052608A (en) | Integrated method for war deduction simulation and efficiency evaluation | |
| Sturges et al. | Computational model for conceptual design based on extended function logic | |
| Xie et al. | Knowledge map and forecast of digital twin in the construction industry: State-of-the-art review using scientometric analysis | |
| Rouse et al. | Interactive visualizations for decision support: Application of Rasmussen's abstraction-aggregation hierarchy | |
| Bruckner | Ml-o-scope: a diagnostic visualization system for deep machine learning pipelines | |
| CN113449878B (en) | Data distributed incremental learning method, system, equipment and storage medium | |
| CN112580258A (en) | Engine design simulation artificial intelligence analysis method and device based on data driving | |
| Jeong et al. | Integration of queuing network and IDEF3 for business process analysis | |
| Uzochukwu et al. | Development and implementation of product sustainment simulator utilizing fuzzy cognitive map (FCM) | |
| Rook et al. | The knowledge acquisition activity matrix: A systems engineering conceptual framework | |
| Guo et al. | Human resource behaviour simulation in business processes | |
| Nakamura et al. | Sequential pattern mining method for analysis of programming learning history based on the learning process | |
| Gitelman et al. | Visual analysis for conceptual design of complex systems | |
| Hughes et al. | Taxonomy for requirements analysis | |
| CN106104513A (en) | Based on cognitive knowledge processing system and method | |
| Deng et al. | CAD Challenges App: An Informatics Framework for Parametric Modeling Practice and Research Data Collection in Computer-Aided Design | |
| Ceccon | AI: Inferring Unseen Pieces to Solve the Heritage Puzzle | |
| Tkáčik | Pattern Mining in Command Histories from Cybersecurity Training | |
| Wu et al. | A hierarchical object-oriented functional modeling framework for co-design of mechatronic products | |
| Biemer et al. | Systems engineering: Basic concepts and life cycle | |
| Richardson | A software environment for visualizing high-dimensional data using contextual self-organizing maps linked with immersive virtual reality | |
| Cichocki et al. | Heating system design support | |
| Li et al. | SoS Architecture Alternatives Tradespace Modeling and Computable Experimentation: A Framework with System Engineering Thinking |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |