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035 _a(RuTPU)RU\TPU\network\24062
035 _aRU\TPU\network\24060
090 _a657532
100 _a20180213a2017 k y0engy50 ba
101 0 _aeng
102 _aFR
105 _ay z 100zy
135 _adrcn ---uucaa
181 0 _ai
182 0 _ab
200 1 _aSDE Simulation in One Click: Fiction or Reality?
_fA. Barysheva, A. Markov
203 _aText
_celectronic
300 _aTitle screen
320 _a[References: p. 437 (18 tit.)]
330 _aStochastic differential equations (further referred to as SDEs) and the models based on SDE are widely used to describe stochastic processes in virtually any area of human activity, such as biology or finance. Unlike an analytical approach to solving SDE, the simulation methods allow to significantly increase the range of practical problems, which examples are given in the paper. Capture III describes the result of the comparative analysis of existing programming tools for SDE simulation, their advantages and shortcomings. It was shown that none of the existing tools completely meet the requirements formulated in Chapter III for the tool's functionality used for building a simulation model.
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. 434-437]
_d2017
610 1 _aэлектронный ресурс
610 1 _aтруды учёных ТПУ
610 1 _astochastic differential equations
610 1 _adiscretization scheme
610 1 _aMonte-Carlo simulation
610 1 _aстохастические дифференциальные уравнения
610 1 _aмоделирование
610 1 _aдискретизация
610 1 _aметод Монте-Карло
700 1 _aBarysheva
_bA.
_cAlexandra
701 1 _aMarkov
_bA.
_gAlexander
712 0 2 _aNational Research Tomsk Polytechnic University (TPU)
_2stltpush
_3(RuTPU)RU\TPU\col\18773
801 2 _aRU
_b63413507
_c20180213
_gRCR
856 4 _uhttp://dx.doi.org/10.2991/itsmssm-17.2017.91
942 _cCF