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Cited by 100 publications
(32 citation statements)
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“…Other health areas such as antibiotic resistance outbreaks [48] and influenza outbreaks [49,50] utilized multivariate regression models. Different algorithms such as deep neural network [51,52], long short-term memory model (LSTM) [53] and gated recurrent unit (GRU)-based model [54] have been successfully applied in various forecasts. The methods rely on specific-less estimation error and running time on data sets with characteristics of multivariate, sequential and time-series data.…”
Section: Related Workmentioning
confidence: 99%
“…Other health areas such as antibiotic resistance outbreaks [48] and influenza outbreaks [49,50] utilized multivariate regression models. Different algorithms such as deep neural network [51,52], long short-term memory model (LSTM) [53] and gated recurrent unit (GRU)-based model [54] have been successfully applied in various forecasts. The methods rely on specific-less estimation error and running time on data sets with characteristics of multivariate, sequential and time-series data.…”
Section: Related Workmentioning
confidence: 99%
“…Other health areas such as antibiotic resistance outbreaks [41] and influenza outbreaks [42,43] are also used multivariate regression models. Different algorithms such as deep neural network [44,45], long short-term memory model (LSTM) [46], and gated recurrent Unit(GRU)-based model [47] are successfully applied in various forecasting. The methods rely on specific less estimation error and running time on artificial network suitable data sets with characteristics of multivariate, sequential and time-series.…”
Section: (C) Multivariate Regression In Aimentioning
confidence: 99%
“…Wen et al 6 proposed a real-time active power fluctuation identification method by considering the high permeability of renewable energy in the power system and flexible changes of power load. They introduced a long-term memory and recurrent neural network algorithms that could accurately and rapidly identify the power fluctuation state from frequency signals measured in real-time, and better maintain system frequency.…”
Section: Related Workmentioning
confidence: 99%