| 000 | 03099nla2a2200469 4500 | ||
|---|---|---|---|
| 001 | 657535 | ||
| 005 | 20231030041514.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\24065 | ||
| 035 | _aRU\TPU\network\24064 | ||
| 090 | _a657535 | ||
| 100 | _a20180213a2017 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aFR | ||
| 105 | _ay z 100zy | ||
| 135 | _adrgn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aFuzzy Neural Network Technology Support Decision-Making _fNguyen Anh Tu, A. M. Korikov, Nguyen Anh Tuan |
|
| 203 |
_aText _celectronic |
||
| 300 | _aTitle screen | ||
| 320 | _a[References: p. 131 (11 tit.)] | ||
| 330 | _aThe application of fuzzy neural network models using fuzzy neuron activation functions to solve the problems of clustering the intensity of Markov chains, whose distribution belongs to the exponential family, has been investigated and discussed in this study. The research is carried out with the help of the computer simulation tools of MATLAB software. Markov chains are presented with a ten successive elementary data sets, each of which is characterized by the intensity of arrival of events. Using fuzzy neural networks, the dichotomy problem is solved: the clusterization of the intensity of ten Poisson streams. The simulation results have validated the applicability of fuzzy neural network clustering of Markov chain intensity. | ||
| 461 | 1 |
_0(RuTPU)RU\TPU\network\18167 _tAdvances in Computer Science Research |
|
| 463 | 0 |
_0(RuTPU)RU\TPU\network\24029 _tVol. 72 : Information technologies in Science, Management, Social sphere and Medicine (ITSMSSM 2017) _oIV International Scientific Conference, 5-8 December 2017, Tomsk, Russia _o[proceedings] _fNational Research Tomsk Polytechnic University (TPU) ; eds. O. G. Berestneva [et al.] _v[P. 128-131] _d2017 |
|
| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _afuzzy activation functions | |
| 610 | 1 | _afuzzy neural networks | |
| 610 | 1 | _aMarkovian arrival processes | |
| 610 | 1 | _aintensity clustering | |
| 610 | 1 | _aнечеткие функции | |
| 610 | 1 | _aнечеткие нейронные сети | |
| 610 | 1 | _aмарковские процессы | |
| 610 | 1 | _aкластеризация | |
| 610 | 1 | _aпринятие решений | |
| 700 | 0 | _aNguyen Anh Tu | |
| 701 | 1 |
_aKorikov _bA. M. _cradiophysicist, specialist in the field of informatics and computer technology _cProfessor of Tomsk Polytechnic University, doctor of technical sciences _f1942- _gAnatoly Mikhailovich _2stltpush _3(RuTPU)RU\TPU\pers\35166 |
|
| 701 | 0 | _aNguyen Anh Tuan | |
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа информационных технологий и робототехники _bОтделение автоматизации и робототехники _h7952 _2stltpush _3(RuTPU)RU\TPU\col\23553 |
| 801 | 2 |
_aRU _b63413507 _c20180213 _gRCR |
|
| 856 | 4 | _uhttp://dx.doi.org/10.2991/itsmssm-17.2017.27 | |
| 942 | _cCF | ||