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In order to avoid the computational complexity, the expert rule base and the parameters of membership functions (MF) are optimized by turns.
If we assume that the previously mentioned off-line expert rule extraction phase has not been (or partially) accomplished an exploration of the space of possible configurations is needed.
For all combinations of n and p+q, the expert rule outperformed the aggregated rule, and their average accuracies were 0.83 and 0.75.
Thus, for equal accuracies, an expert rule would be less costly (in terms of time), especially as groups grow larger [22].
Of note, these TCE correspond exactly to those used in [30], in order to maintain a fair comparison with other tested methods, such as expert rule bases.
If (4) was satisfied, the aggregated rule would be used in the second decision, and otherwise the expert rule would be used, and so on for the subsequent decisions.
Similar(40)
The guideline requires the use of two complementary approaches, an expert rule-based method and a statistical algorithm.
The objective of this paper is to present an open and modular expert rule-based system in order to automatically select cutting parameters in milling operations.
In the 1970s computer scientists specializing in artificial intelligence created expert, "rule-based" systems, programs that attempted to simulate the reasoning process of a human expert in making decisions related to highly structured problems.
Denning's work was focused on explicit expert rules, which were pervasive throughout the first generation of IDSs.
The approach uses expert rules to choose parts, part order, and part disassembly directions, based upon physical constraints.
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