logo
calendar15 Dekabr 2019
view35
Main language:Russian

Increase of identification quality on the basis of genetic adjustment of models parameters for description non-stationary objects.

Field of Science:
pdf

5df612475397c.pdf

PDF

Kimyoviy texnologiya. Nazorat va boshqaruv

Kimyoviy texnologiya. Nazorat va boshqaruv

Publish Articlesee more

ARTICLE ANNOTATION

quote
Paper formulated the problem of increasing the quality of identification for casual time series (CTS), representing non-stationary objects in multicontour control systems on the basis of effective search of global and local extremums when parameters of target optimization function are rational. The new approach is offered to optimization of search by consideration statistical and dynamic characteristics of CTS as specimen of population generation, and by reflection of coordinate points set in space of evolution toward optimal values of target function. The modified genetic algorithm (GA) is developed on the basis of overlapping, generalization of opportunities and use of properties of genetic operators for evolutionary modeling. Procedures are entered for statistical selection of search points population, exception "unsuccessful" descendants, change of specimen generations on the basis of elimination and replacement unpromising specimen. Efficiency of the program complex to CTS identification is investigated on the basis of mechanisms to adjustment of parameters by recurrent dependences, traditional and modified GA.

AUTHORS

A.Axmatov

Samarqand davlat universiteti

N.Isroilov

Samarqand davlat universiteti

Tags

# оператор# идентификация# identification# генетический алгоритм# genetic algorithm# operator# нестационарный объект# настройка параметров# non-stationary object# adjustment of parameters# тадрижий моделлаштириш# ностационар объект# генетик алгоритм# параметрларни созлаш# эволюционное моделирование# evolutionary modeling# излаш диапазони# ечим эҳтимоли# мурожаат сони# мақсад функцияси# глобал ва локал экстремумлар# диапазон поиска# вероятность решения# число обращений# целевая функция# глобальный и локальный экстремум# range of search# probability of solution# number of appeals# target function# global and local extremes

OTHER ARTICLES IN THIS JOURNAL

Rate Article

0
0 ratings
5
4
3
2
1

Article Identifiers

ROI:

https://eroi.uz/11.0008/A1219-0016

DOI:

Not Available

References

1. Barsegyan A.A., Kupriyanov M.S., Stepanenko V.V., Holod I.I. Tehnologiya analiza danny'h: Data Mining, Visual Mining, Text Mining, OLAP. 2-e izd. Uch. posobie. Spb.: BHV - Peterburg, 2007. - 384 s. 2. Kennedy J., Eberhart R.C. Particle swarm optimization // In Proceedings of IEEE International Conference on Neural Networks, 1995. P. 1942-1948. 3. Eberhart R.C., Kennedy J. A new optimizer using particle swarm theory // Proceedings of the Sixth International Symposium on Micro Machine and Human Science MHS’95, 1995. P. 39-43. 4. Rutkovskaya D., Pilin'skiy M., Rutkovskiy L. Neyronny'e seti, geneticheskie algoritmy' i nechetkie sistemy'. M.: Goryachaya liniya - Telekom, 2004. - 452 s. 5. Mahotilo K.V., Petrashev S.N., Sergeev S.A. Geneticheskie algoritmy', iskusstvenny'e neyronny'e seti i problemy' virtual'noy real'nosti. Har'kov: Osnova, 1997. - 112 s. 6. Jumanov I.I., Bekmurodov Z.T. Identifikaciya sluchayny'h vremenny'h ryadov na osnove neyro-nechetkoy seti dlya povy'sheniya dostovernosti prognoza// HI Mejdunarodnaya Aziatskaya shkola «Problemy' optimizacii slojny'h sistem», Issy'k-Kul'skaya oblast', s. Bulan-Sogotu - 2015 - s. 258-264. 7. Djumanov O.I. Sistema intellektual'nogo analiza i obrabotki danny'h na osnove geneticheskih algoritmov kontrolya dostovernosti izobrajeniy neprery'vny'h ob`ektov // H Mejdunarodnaya Aziatskaya shkola «Problemy' optimizacii slojny'h sistem», Issy'k-Kul'skaya oblast', s. Bulan-Sogotu - 2014 - s. 249-254. 8. Djumanov O.I. Metody' analiza sluchayny'h vremenny'h processov v sistemah upravleniya nestacionarny'mi processami // Respublikanskaya nauchnaya konferenciya «Perspektivy' razvitiya informacionny'h tehnologiy i telekommunikacionny'h sistem», 13-14 mart 2014 g., TUIT, chast' 1. - Tashkent, 2014. - s. 332-334. 9. Djumanov O.I. Optimizaciya obucheniya neyrosetevy'h sistem obrabotki danny'h na osnove dinamicheskih harakteristik// «Problemy' informatiki i e`nergetiki», Izd. «Fan» AN RUz. - Tashkent, 2011. - №3. - s. 63-70.