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Application of a New Hybrid Model with Seasonal Auto-Regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-Regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China
5 references·3 citing·27 second hop
Application of a New Hybrid Model with Seasonal Auto-Regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-Regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China (2014)Application of a New Hybrid Model with Se…Forecasting nonlinear time series with a hybrid methodology (2009)Forecasting nonlinear time se…A hybrid SARIMA and support vector machines in forecasting the production values of the machinery industry in Taiwan (2006)A hybrid SARIMA and support v…Time series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Backpropagation and recurrent neural networks in financial analysis of multiple stock market returns (1996)Backpropagation and recurrent…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Application of a hybrid model in predicting the incidence of tuberculosis in a Chinese population (2019)Application of a hybrid model…A Review of Epidemic Forecasting Using Artificial Neural Networks (2019)A Review of Epidemic Forecast…Nonlinear combination method of forecasters applied to PM time series (2017)Nonlinear combination method …The Combination of Forecasts (1969)Time Series Analysis: Forecasting and Control (1977)A neural network ensemble method with jittered training data for time series forecasting (2007)Forecasting the demand of the aviation industry using hybrid time series SARIMA-SVR approach (2018)An intelligent hybridization of ARIMA with machine learning models for time series forecasting (2019)Time Series Analysis: Forecasting and Control (1977)A new linear & nonlinear artificial neural network model for time series forecasting (2012)PREDICTING HOUSING SALES IN TURKEY USING ARIMA, LSTM AND HYBRID MODELS (2019)A Review of Time-Series Forecasting Algorithms for Industrial Manufacturing Systems (2024)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Forecasting with artificial neural networks: (1998)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)The financial analysts journal (1960)Time series forecasting using neural networks vs. Box- Jenkins methodology (1991)Stock performance modeling using neural networks: A comparative study with regression models (1994)A Rolling Grey Model Optimized by Particle Swarm Optimization in Economic Prediction (2014)Enhancing stock market prediction with extended coupled hidden Markov model over multi-sourced data (2018)A comparative study on the prediction of the BP artificial neural network model and the ARIMA model in the incidence of AIDS (2020)Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China (2016)An Advanced Data-Driven Hybrid Model of SARIMA-NNNAR for Tuberculosis Incidence Time Series Forecasting in Qinghai Province, China (2020)The M3-Competition: results, conclusions and implications (2000)Another look at measures of forecast accuracy (2006)Principles of forecasting : a handbook for researchers and practitioners (2001)25 years of time series forecasting (2006)The politics of attention: how government prioritizes problems (2006)
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References

  • 1978Time Series Analysis: Forecasting and Control.5,299 cited
  • 2003Time series forecasting using a hybrid ARIMA and neural network model4,469 cited
  • 2006A hybrid SARIMA and support vector machines in forecasting the production values of the machinery industry in Taiwan208 cited
  • 2009Forecasting nonlinear time series with a hybrid methodology155 cited
  • 1996Backpropagation and recurrent neural networks in financial analysis of multiple stock market returns92 cited

Cited by

  • 2019A Review of Epidemic Forecasting Using Artificial Neural Networks59 cited
  • 2019Application of a hybrid model in predicting the incidence of tuberculosis in a Chinese population53 cited
  • 2017Nonlinear combination method of forecasters applied to PM time series48 cited

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