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  2. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    The Long Short-Term Memory (LSTM) cell can process data sequentially and keep its hidden state through time. Long short-term memory ( LSTM ) [ 1 ] is a type of recurrent neural network (RNN) aimed at mitigating the vanishing gradient problem [ 2 ] commonly encountered by traditional RNNs.

  3. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    The original model uses an iterative three-stage modeling approach: Model identification and model selection: making sure that the variables are stationary, identifying seasonality in the dependent series (seasonally differencing it if necessary), and using plots of the autocorrelation (ACF) and partial autocorrelation (PACF) functions of the dependent time series to decide which (if any ...

  4. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series. [1] The building block of RNNs is the recurrent unit. This unit maintains a hidden state, essentially a form of memory, which is updated at ...

  5. Autoregressive integrated moving average - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_integrated...

    Ruby: the "statsample-timeseries" gem is used for time series analysis, including ARIMA models and Kalman Filtering. JavaScript: the "arima" package includes models for time series analysis and forecasting (ARIMA, SARIMA, SARIMAX, AutoARIMA) C: the "ctsa" package includes ARIMA, SARIMA, SARIMAX, AutoARIMA and multiple methods for time series ...

  6. Echo state network - Wikipedia

    en.wikipedia.org/wiki/Echo_state_network

    In early studies, ESNs were shown to perform well on time series prediction tasks from synthetic datasets. [ 1 ] [ 17 ] Today, many of the problems that made RNNs slow and error-prone have been addressed with the advent of autodifferentiation (deep learning) libraries, as well as more stable architectures such as long short-term memory and ...

  7. Autoregressive moving-average model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_moving...

    Python has the statsmodelsS package which includes many models and functions for time series analysis, including ARMA. Formerly part of the scikit-learn library, it is now stand-alone and integrates well with Pandas. PyFlux has a Python-based implementation of ARIMAX models, including Bayesian ARIMAX models.

  8. Doctors Say This Nighttime Behavior Can Be A Sign Of Dementia

    www.aol.com/lifestyle/doctors-nighttime-behavior...

    Sundowning also tends to happen consistently around the same time of day, Elhelou says. “It often includes cognitive effects such as significant disorientation or impaired judgement,” she says.

  9. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Forecasting on time series is usually done using automated statistical software packages and programming languages, such as Julia, Python, R, SAS, SPSS and many others. Forecasting on large scale data can be done with Apache Spark using the Spark-TS library, a third-party package.