Перевод названия: ВРЕМЕННЫЕ РЯДЫ РАСПРЕДЕЛЕНИЙ ДЛЯ ПРОГНОЗИРОВАНИЯ И ОЦЕНКИ РИСКА
Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: Моделирование и анализ безопасности и риска в сложных системах; Санкт-Петербург; Санкт-Петербург
Год издания: 2020
Ключевые слова: big time series, distributional time series, aggregation, computational probabilistic analysis, forecasting, risk assessment
Аннотация: Important computational aspects of big data processing and forecasting methods for the problems of the digital economy are under consideration. New approach to the study and forecasting of big data represented by time series is discussed.Our approach is based on big data technologies, including data aggregation procedures for inputПоказать полностьюand output parameters and computational probabilistic analysis.The result of this approach is a new type of representation of big time series in the form of distributional time series. Piecewise polynomial models are used for data aggregation procedures. To solve computational problems on distributed time series, we developed arithmetic over piecewise polynomial functions. To demonstrate our approach, we examined the task of risk assessing to investment project for the organization of parking lots.
Журнал: Modeling and Analysis of Safety and Risk in Complex Systems
Номера страниц: 122-128
Издатель: Санкт-Петербургский государственный университет аэрокосмического приборостроения