Data Simulation System with Automated Logic Generation
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Solution Overview
Problem
Existing data simulation systems require significant experience and knowledge to design simulation processes and logic, making it difficult to effectively store and reuse design experience, resulting in high manpower and time costs.
Innovation Solution
A data simulation system and method that includes an execution engine with a type matcher, executor, and analyzer, which automatically generates and adjusts simulation logic groups based on simulation commands, types, and data source information, ensuring accurate simulation results and efficient logic generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If design personnel manually design simulation processes and logic based on experience and knowledge, then the simulation can be performed, but significant manpower and time costs are consumed and experience cannot be effectively stored and reused
Solution Approach 1:
The patent creates a digital copy of design experience and knowledge by automatically generating simulation logic groups from historical data and preset templates. This copied knowledge is stored in the system and can be reused for future simulations, eliminating the need for manual redesign and reducing both manpower and time costs while maintaining simulation quality.
Solution Approach 2:
The system enables self-service by automatically generating simulation logic groups without requiring design personnel to manually input their experience and knowledge each time. The automated generation process serves itself by learning from historical data and preset templates, continuously improving simulation establishment efficiency while reducing human intervention.
2Loss of information
If design personnel manually establish simulation processes, then the simulation logic can be created, but the process cannot be clearly displayed through data changes making it difficult to store and reuse experience
Solution Approach 1:
The patent segments the complex simulation logic into structured logic groups that can be independently analyzed, stored, and reused. By dividing the simulation process into discrete, organized components, the system makes the logic transparent and searchable, enabling effective storage and retrieval of design experience without being overwhelmed by overall system complexity.
Solution Approach 2:
The patent introduces an intermediary layer between manual design and system storage by automatically generating structured simulation logic groups that bridge the gap. This intermediary process converts implicit design experience into explicit, storable formats, making knowledge transferable and reusable while managing the complexity of simulation logic through systematic organization.
3Productivity
If automated simulation logic generation is implemented, then productivity is improved, but the accuracy and matching degree of simulation results must be maintained
Solution Approach 1:
The patent implements feedback mechanisms where simulation results are automatically evaluated against preset criteria and historical data. The system uses this feedback to refine and adjust simulation logic groups, ensuring that automated generation maintains high accuracy. The feedback loop continuously improves both productivity and precision by learning from previous simulations and adjusting parameters accordingly.
Solution Approach 2:
The patent utilizes parameter changes to balance productivity and accuracy by dynamically adjusting simulation parameters based on the complexity of the task, available data quality, and performance requirements. The system can modify parameters such as simulation depth, data sampling rates, and logic complexity to optimize both generation speed and result accuracy for different scenarios.
Data Source
AI summary
The disclosure provides a data simulation system and a data simulation method. The data simulation system includes an execution engine and a database. The execution engine includes a type matcher, an executor, and an analyzer. The type matcher receives a simulation command and generates a simulation logic group according to a simulation type in the simulation command. The executor executes simulation processing on data according to the simulation logic group to generate a simulation result. The analyzer determines a matching degree between the simulation result and a preset result according to the simulation type. When the matching degree is less than a threshold value, the analyzer adjusts the simulation logic group and commands the executor to execute the simulation processing repeatedly. When the matching degree is greater than the threshold value, the analyzer stores the simulation logic group.