Adaptive Rule Evaluation for Time-Variant Data
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Solution Overview
Problem
Existing rule evaluation systems face performance issues when dealing with time variant input data, as the fixed order of criterion evaluation can lead to suboptimal performance.
Innovation Solution
An adaptive rule evaluation system that dynamically adjusts the order of criterion evaluation based on profiling and optimization analysis, using modules such as the evaluation processing module and the adjustment processing module to continuously assess and improve the rule processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed order of rule evaluation is used, then the system structure is simple, but the performance deteriorates when handling time variant input data
Solution Approach 1:
The patent implements dynamic rule evaluation by introducing an evaluation processing module that continuously profiles rule performance and an adjustment processing module that dynamically reorders rules based on current input data characteristics. This transforms the static fixed-order evaluation into a dynamic adaptive system that optimizes performance for time-variant input data while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The patent establishes a feedback loop where the evaluation processing module monitors rule evaluation outcomes and feeds this information to the adjustment processing module, which then modifies the rule evaluation order. This feedback mechanism enables the system to learn from past performance and automatically adapt to improve future rule evaluation efficiency without requiring complex manual configuration.
2Productivity
If rules are evaluated in a fixed sequential order, then the implementation is straightforward, but unnecessary checks are performed reducing efficiency
Solution Approach 1:
The patent applies preliminary action by having the evaluation processing module profile and analyze rule performance characteristics before the actual rule evaluation occurs. This preliminary analysis enables the adjustment processing module to pre-arrange rules in an optimal order based on expected input data characteristics, thereby avoiding unnecessary rule checks and reducing processing time during actual evaluation.
3Adaptability or versatility
If the rule evaluation order is adapted dynamically, then performance on time variant data improves, but the device complexity increases
Solution Approach 1:
The patent segments the rule evaluation system into distinct functional modules: a rule match processing module for executing rule evaluations, an evaluation processing module for profiling and analyzing performance, and an adjustment processing module for dynamically reordering rules. This segmentation enables dynamic adaptability to time-variant data while keeping each module's complexity manageable and well-defined, avoiding the need for a monolithic complex system.
Data Source
Figure 1~2
AI summary
An adaptive rule evaluation system comprises an input (12) for receiving time variant input data, a rule match processing module (14), an evaluation processing module (16), and an adjustment processing module (18). The rule match processing module (14) is configured to process the time variant input data by means of applying at least one rule on the time variant input data. The at least one rule comprises at least one criterion assigned to a characteristic of the time variant input data. The characteristic is time variant. The evaluation processing module (16) is configured to profile the rule processing. The adjustment processing module (18) is configured to determine an adjusted rule processing. Further, a method for automatically adapting a rule evaluation with respect to time variant input data is described.