| Номер документа в системі: | 340023 |
| Автор: | Zhengbing Hu, Bodyanskiy Y. V., Tyshchenko O.K., Samitova V. O. |
| Назва документа: | Fuzzy data clustering in the rank scale based on a double neo-fuzzy neuron = Нечітка кластеризація даних у ранговій шкалі на основі подвійного нео-фаззі нейрону |
| УДК | 004.032.26 |
| Мова документу | Англійська |
| Аннотація | Context. A task of data classification under conditions of clusters' overlapping is considered in this article. Besides that, it's assumed that information to be processed is given in the rank scale.
Objective. It's proposed to use a double neo-fuzzy neuron for classification which is a modification of a traditional neo-fuzzy neuron with specially designed asymmetrical membership functions and improved approximating properties.
Method. The double neo-fuzzy neuron (just like the traditional one) is designated for processing data given the scale of natural numbers. However, the situation may become complicated greatly if source data is not given in the numerical scale but in the ordinal one which is a quite common case for a wide variety of practical tasks.
Results. A gradient minimization procedure with a variable learning step parameter was used for learning the double neo-fuzzy neuron. The proposed approach to fuzzy classification for data given in the ordinal scale based on the double neo-fuzz |
| Кількість сторінок | Р. 74-82. |