Data Analyzing Apparatus Dynamic Parameter Adjustment
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Solution Overview
Problem
Conventional data analyzing apparatuses face challenges in using an optimum combination of analytical parameters and input data formats, leading to decreased accuracy when input data trends change, and struggle to simultaneously address these issues.
Innovation Solution
A data analyzing apparatus that generates and evaluates format variations and analytical parameter combinations, dynamically switching between different analytical methods to maintain accuracy by reactivating and updating the most accurate knowledge models based on changing data trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a clear-cut solution is used to select from semi-infinite variations of processed data and analytical methods, then device complexity is reduced, but manufacturing precision (accuracy of analytical results) deteriorates
Solution Approach 1:
The system dynamically adjusts analytical parameters and data formats based on changing input data trends. Instead of using a fixed clear-cut solution, the apparatus continuously adapts the combination of analytical parameters and input data formats to maintain high accuracy when data trends change, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The invention changes parameters (analytical parameters and data formats) based on the characteristics of input data. By automatically adjusting these parameters according to data trends, the system achieves high accuracy without requiring manual selection from semi-infinite variations, thus reducing complexity while maintaining precision.
2Ease of operation
If the same parameter is used for extracting knowledge models continuously, then ease of operation is improved, but reliability (accuracy maintenance) deteriorates when input data trend changes
Solution Approach 1:
The system monitors input data trends and provides feedback to automatically adjust analytical parameters. When a change in data trend is detected, the feedback mechanism triggers parameter adjustment to maintain accuracy, thus preserving reliability while keeping the operation simple through automation.
Solution Approach 2:
The apparatus performs self-adjustment of analytical parameters based on detected data trends. The system serves itself by automatically recognizing when parameter changes are needed and implementing them without external intervention, maintaining both ease of operation and reliability.
3Manufacturing precision
If multiple format variations and analytical parameter combinations are evaluated, then manufacturing precision (accuracy) is improved, but device complexity and loss of time increase
Solution Approach 1:
The system pre-evaluates and stores the accuracy of different analytical parameter combinations and data format variations before actual analysis. By preparing these evaluations in advance, the apparatus can quickly select the optimal combination during runtime without performing complex real-time evaluations, thus maintaining high accuracy while reducing operational complexity.
Solution Approach 2:
Instead of evaluating all possible semi-infinite combinations, the system evaluates a sufficient subset of format variations and parameter combinations that covers the necessary range for accurate analysis. This partial evaluation approach achieves the required accuracy without the excessive complexity of exhaustive evaluation.
4Manufacturing precision
If multiple format variations and analytical parameter combinations are evaluated, then manufacturing precision (accuracy) is improved, but loss of time (processing time) increases
Solution Approach 1:
The system performs accuracy evaluations of different format variations and parameter combinations in advance and stores the results. During actual analysis, it simply retrieves the pre-evaluated optimal combination based on current data characteristics, achieving high accuracy without the time cost of real-time exhaustive evaluation.
Solution Approach 2:
The apparatus evaluates only the necessary subset of format variations and parameter combinations that are most likely to yield accurate results for the given data type. This selective partial evaluation maintains high accuracy while significantly reducing the time loss compared to evaluating all possible combinations.
Data Source
AI summary
A data analyzing apparatus of an embodiment generates a format variation, analytical algorithm name, and analytical parameter not stored in a first storage device, and executes analysis. The data analyzing apparatus determines whether the application accuracy is lower than the knowledge model accuracy. If the determination result is “not lower”, the data analyzing apparatus reactivates a format variation generating device and an analytical parameter generating device. If the determination result is “lower”, the data analyzing apparatus reads out a format variation and knowledge model name associated with the highest priority order in the first storage device, and executes analysis.