Optimal construction of the pattern matrix for probabilistic neural networks in technical diagnostics based on expert estimations
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Дата
2021
Автори
Науковий керівник
Назва журналу
Номер ISSN
Назва тому
Видавець
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Анотація
In the field of technical diagnostics, many tasks are solved by using automated classification. For this,
such classifiers like probabilistic neural networks fit best owing to their simplicity. To obtain a probabilistic
neural network pattern matrix for technical diagnostics, expert estimations or measurements are commonly
involved. The pattern matrix can be deduced straightforwardly by just averaging over those estimations.
However, averages are not always the best way to process expert estimations. The goal is to suggest a
method of optimally deducing the pattern matrix for technical diagnostics based on expert estimations. The
main criterion of the optimality is maximization of the performance, in which the subcriterion of
maximization of the operation speed is included. First of all, the maximal width of the pattern matrix is
determined. The width does not exceed the number of experts. Then, for every state of an object, the expert
estimations are clustered. The clustering can be done by using the k-means method or similar. The centroids
of these clusters successively form the pattern matrix. The optimal number of clusters determines the
probabilistic neural network optimality by its performance maximization. In general, most results of the error
rate percentage of probabilistic neural networks appear to be near-exponentially decreasing as the number of
clustered expert estimations is increased. Therefore, if the optimal number of clusters defines a too “wide”
pattern matrix whose operation speed is intolerably slow, the performance maximization implies a tradeoff
between the error rate percentage minimum and maximally tolerable slowness in the probabilistic neural
network operation speed. The optimal number of clusters is found at an asymptotically minimal error rate
percentage, or at an acceptable error rate percentage which corresponds to maximally tolerable slowness in
operation speed. The optimality is practically referred to the simultaneous acceptability of error rate and
operation speed.
Опис
Ключові слова
technical diagnostics, probabilistic neural network, pattern matrix, expert estimations, clustering, performance maximization
Бібліографічний опис
Romanuke, V. Optimal construction of the pattern matrix for probabilistic neural networks in technical diagnostics based on expert estimations / Romanuke Vadim // Information, Computing and Intelligent systems. – 2021. – No. 2. – Pp. 19–25. – Bibliogr.: 13 ref.