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Исследование применения S-Ð¾Ð±Ñ€Ð°Ð·Ð½Ñ‹Ñ ÐºÑ€Ð¸Ð²Ñ‹Ñ Ð² моделировании ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸Ñ‡ÐµÑÐºÐ¸Ñ Ð¿Ñ€Ð¾Ñ†ÐµÑÑÐ¾Ð²

магистерская диссертация

Исследование применения S-Ð¾Ð±Ñ€Ð°Ð·Ð½Ñ‹Ñ ÐºÑ€Ð¸Ð²Ñ‹Ñ Ð² моделировании ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸Ñ‡ÐµÑÐºÐ¸Ñ Ð¿Ñ€Ð¾Ñ†ÐµÑÑÐ¾Ð²

Abstract

В работе были рассмотрены существующие в настоящее время логистические кривые, записаны их уравнения, выявлены области их применения. Проведен анализ возможностей прогнозирования динамики экономических процессов на основе использования логистических кривых. Изучены основы построения имитационных моделей в программе AnyLogic, рассмотрены примеры параметризации S-образных кривых на реальных примерах, в том числе на примере динамики сложности майнинга криптовалют. Проанализирована динамика экономической эффективности вложений на примере криптовалюты биткоин, рассчитана рентабельность майнинга биткоина. Рассмотрены принципы отражения проводок операций с криптовалютами в бухгалтерском учете.

Keywords

логистическая динамика, прогнозирование, экономическая эффективность, Математическое моделирование, криптовалюты

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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