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Research on GDP Forecast Analysis Combining BP Neural Network and ARIMA Model
8 references·0 citing·39 second hop
Research on GDP Forecast Analysis Combining BP Neural Network and ARIMA Model (2021)Research on GDP Forecast Analysis Combini…A network traffic forecasting method based on SA optimized ARIMA–BP neural network (2021)A network traffic forecasting…Stock price forecasting based on LLE-BP neural network model (2020)Stock price forecasting based…A comparative study on the prediction of the BP artificial neural network model and the ARIMA model in the incidence of AIDS (2020)A comparative study on the pr…Forecasting Horticultural Products Price Using ARIMA Model and Neural Network Based on a Large-Scale Data Set Collected by Web Crawler (2019)Forecasting Horticultural Pro…Exploration of stock index change prediction model based on the combination of principal component analysis and artificial neural network (2019)Exploration of stock index ch…Comparison of Forecasting India’s Energy Demand Using an MGM, ARIMA Model, MGM-ARIMA Model, and BP Neural Network Model (2018)Comparison of Forecasting Ind…Application and analysis of forecasting stock price index based on combination of ARIMA model and BP neural network (2018)Application and analysis of f…Prediction of stock prices based on LM-BP neural network and the estimation of overfitting point by RDCI (2017)Prediction of stock prices ba…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control. (1978)Urban population density estimation based on spatio‐temporal trajectories (2020)ARIMA forecasting of primary energy demand by fuel in Turkey (2006)A global review of energy consumption, CO 2 emissions and policy in the residential sector (with an overview of the top ten CO 2 emitting countries) (2014)Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model (2016)Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model (2019)Using artificial neural network models in stock market index prediction (2011)Recurrent neural network and a hybrid model for prediction of stock returns (2014)Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock market (2016)Stock Price Prediction Using Machine Learning Techniques (2019)Discovery and Prediction of Stock Index Pattern via Three-Stage Architecture of TICC, TPA-LSTM and Multivariate LSTM-FCNs (2020)A Black Swan event-based hybrid model for Indian stock markets’ trends prediction (2022)A high-order fuzzy time series forecasting model for internet stock trading (2013)A hybrid fuzzy time series model based on granular computing for stock price forecasting (2014)Intraday stock price forecasting based on variational mode decomposition (2015)Assess deep learning models for Egyptian exchange prediction using nonlinear artificial neural networks (2020)A Hybrid Approach for Predicting Corporate Financial Risk: Integrating SMOTE-ENN and NGBoost (2023)Digital Money Options for the BRICS (2023)Generalized autoregressive conditional heteroskedasticity (1986)Forecasting with artificial neural networks: (1998)Applications of deep learning into supply chain management: a systematic literature review and a framework for future research (2022)Forecasting Agricultural Commodity Prices Using Dual Input Attention LSTM (2022)Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India (2022)Stock price forecast using Bayesian network (2012)Support vector regression with chaos-based firefly algorithm for stock market price forecasting (2012)A stock time series forecasting approach incorporating candlestick patterns and sequence similarity (2022)Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices (2023)Stock Market Trend Prediction Using Deep Learning Approach (2024)Industrial and business forecasting methods : a practical guide to exponential smoothing and curve fitting (1982)Computational and Mathematical Methods in Medicine (2011)A new linear & nonlinear artificial neural network model for time series forecasting (2012)A Combined Model of SARIMA and Prophet Models in Forecasting AIDS Incidence in Henan Province, China (2022)The research of ARIMA, GM(1,1), and LSTM models for prediction of TB cases in China (2022)Application of ARIMA, and hybrid ARIMA Models in predicting and forecasting tuberculosis incidences among children in Homa Bay and Turkana Counties, Kenya (2023)Time-series forecasting of seasonal items sales using machine learning – A comparative analysis (2022)Forecasting Network Traffic: A Survey and Tutorial With Open-Source Comparative Evaluation (2023)Digital economy and risk response: How the digital economy affects urban resilience (2024)
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References

  • 2021A network traffic forecasting method based on SA optimized ARIMA–BP neural network223 cited
  • 2019Forecasting Horticultural Products Price Using ARIMA Model and Neural Network Based on a Large-Scale Data Set Collected by Web Crawler133 cited
  • 2020Stock price forecasting based on LLE-BP neural network model67 cited
  • 2020A comparative study on the prediction of the BP artificial neural network model and the ARIMA model in the incidence of AIDS66 cited
  • 2017Prediction of stock prices based on LM-BP neural network and the estimation of overfitting point by RDCI65 cited
  • 2018Application and analysis of forecasting stock price index based on combination of ARIMA model and BP neural network63 cited
  • 2019Exploration of stock index change prediction model based on the combination of principal component analysis and artificial neural network59 cited
  • 2018Comparison of Forecasting India’s Energy Demand Using an MGM, ARIMA Model, MGM-ARIMA Model, and BP Neural Network Model39 cited

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