Young developed a set of algorithms around this kind of fuzzy pattern recognition and cast about for markets that might be able to use it.
To meet these requirements, we develop an evolving version of fuzzy pattern tree learning, in which model adaptation is realized by anticipating possible local changes of the current model, and confirming these changes through statistical hypothesis testing.
We propose a weighting function for compatibility grade of patterns that improves the performance of fuzzy classification system without degrading the interpretability of fuzzy rules.
This task is formulated as a combinatorial optimization problem with three objectives: to maximize the number of correctly classified training patterns, to minimize the number of fuzzy rules, and to minimize the total number of antecedent conditions.
Six major differential expression patterns were identified by use of Fuzzy C-means clustering [ 49] (Fig. 2).
Dr Vsevolod Makeev, State Research Centre of Genetics and Selection of Industrial Microorganisms, GosNIIgenetika, Moscow (nominated by Dr Mikhail Gelfand Thee authors compare four methods for identification of fuzzy periodical patterns in nucleotide sequences in the context of extracting the 10-periodic nucleosome positioning signal.
In order to handle on-line recognition problems of some complex industrial process, a new modeling method with a self-learning function is proposed by using the theories of fuzzy sets and pattern recognition.
Some elements of the pattern are fuzzy -- as cracked and begrimed with age as any old painting.
And when imagining an elephant, or seeing an elephant, moving from left to right on the screen, the pattern of brain scanning shows a fuzzy image of an elephant.
The Post notes that the finding fits a general pattern of Americans being a bit fuzzy on where their food comes from.
When there is no pattern in the fuzzy sub-space defined by A q, we do not generate any fuzzy rules with A q in the antecedent part.
