Analysis Procedure Selection Using Target and Environment Attributes
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Solution Overview
Problem
Existing data analysis systems require specialized knowledge to select appropriate analysis procedures, as they do not account for varying attributes of analysis targets and their environments, leading to inefficiencies in selecting procedures that balance accuracy, speed, and robustness.
Innovation Solution
A learning processing device that outputs indices for selecting analysis procedures based on attributes of the analysis target, including characteristics and environmental factors, allowing for the selection of procedures that meet preset conditions for data analysis properties such as speed, accuracy, and robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple analysis procedures are executed in parallel to find the most accurate one, then analysis accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing evaluation values for multiple analysis procedures in a database before actual analysis is needed. When analysis is required, the system retrieves pre-stored evaluation results and selects procedures based on these pre-computed metrics, avoiding the need to execute all procedures in parallel at runtime.
Solution Approach 2:
Instead of evaluating all possible analysis procedures exhaustively, the system uses partial evaluation by selecting and executing only those procedures whose evaluation values meet predetermined criteria. The selection is based on partial information (evaluation values) rather than complete execution of all procedures, reducing processing time while maintaining accuracy.
2Adaptability or versatility
If analysis procedures are selected based on comprehensive evaluation of multiple attributes, then suitability for specific purposes is improved, but the complexity of selection increases
Solution Approach 1:
The system introduces an intermediary mechanism - a database storing pre-calculated evaluation values that act as a mediator between analysis procedures and selection criteria. This intermediary structure simplifies the selection process by providing ready-made evaluation metrics, eliminating the need for complex real-time evaluation logic.
Solution Approach 2:
The system changes parameters by using predetermined evaluation values stored in a database rather than calculating all attributes in real-time. The selection process operates on transformed parameters (pre-computed evaluation metrics) rather than raw attribute data, reducing computational complexity while maintaining comprehensive evaluation capability.
3Measurement precision
If specialized knowledge is required to select appropriate analysis procedures, then analysis accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system implements self-service by automatically selecting analysis procedures based on predetermined evaluation values and selection criteria without requiring user expertise. The system autonomously retrieves evaluation data, applies selection logic, and chooses appropriate procedures, freeing users from the need to possess specialized knowledge about analysis procedure selection.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing evaluation values for all analysis procedures before user interaction. This pre-computation eliminates the need for users to perform complex evaluations or possess specialized knowledge, as the system has already prepared the selection criteria in advance.
Data Source
AI summary
An index outputter (120) of a learning processor (100) outputs an index for selection of an analysis procedure based on attributes of an analysis target. The attributes to be inputted include features of the analysis target itself and features of the environment surrounding the analysis target. The analysis procedure selector (170) selects an analysis procedure among analysis procedures as an analysis procedure for which diagnosis target data to be outputted by the analysis target is to be analyzed. The selected analysis procedure is a procedure in which an evaluation value of a property of data analysis satisfies a preset condition in connection with the index.