Abstract
The original branch-bound backtrack (BBB) algorithm applied to fuzzy decision trees is corrected and improved. It is shown useful for both the probabilistic (prob) and the max-min models for decision making. The improved technique is not only powerful as far as recognition in imprecise environments, but also very useful as far as the optimality of the solution.
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