Time series forecasting using a hybrid ARIMA and neural network model
From MaRDI portal
Publication:65788
DOI10.1016/s0925-2312(01)00702-0zbMath1006.68828MaRDI QIDQ65788
G.Peter Zhang, Guoqiang Peter Zhang
Publication date: January 2003
Published in: Neurocomputing (Search for Journal in Brave)
Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies and applications (68U99)
Related Items (72)
On the construction of a nonlinear recursive predictor ⋮ Partitioning and interpolation based hybrid ARIMA-ANN model for time series forecasting ⋮ Temperature prediction based on a space–time regression-kriging model ⋮ China's energy consumption forecasting by GMDH based auto-regressive model ⋮ Series hybridization of parallel (SHOP) models for time series forecasting ⋮ Hybridization of intelligent techniques and ARIMA models for time series prediction ⋮ On the Automatic Identification of Unobserved Components Models ⋮ Applying Diebold–Mariano Test for Performance Evaluation Between Individual and Hybrid Time-Series Models for Modeling Bivariate Time-Series Data and Forecasting the Unemployment Rate in the USA ⋮ Long-term prediction of the metals' prices using non-Gaussian time-inhomogeneous stochastic process ⋮ Evaluation performance of time series methods in demand forecasting: Box-Jenkins vs artificial neural network (Case study: Automotive Parts industry) ⋮ Hybrid regression model for near real-time urban water demand forecasting ⋮ A novel hybrid ARIMA and regression tree model for the interval-valued time series ⋮ Predicting citywide crowd flows using deep spatio-temporal residual networks ⋮ A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates ⋮ Soft computing hybrids for FOREX rate prediction: a comprehensive review ⋮ Forecasting time series movement direction with hybrid methodology ⋮ Weighted sequential hybrid approaches for time series forecasting ⋮ State space modeling of Gegenbauer processes with long memory ⋮ Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks ⋮ Stocks recommendation from large datasets using important company and economic indicators ⋮ A comparison of GSTAR-SUR models and a hybrid GSTAR-SUR/neural network model on residuals of precipitation forecasting ⋮ A comparative study of series arima/mlp hybrid models for stock price forecasting ⋮ Track irregularity time series analysis and trend forecasting ⋮ Modeling and forecasting interval time series with threshold models ⋮ Combining seasonal ARIMA models with computational intelligence techniques for time series forecasting ⋮ Epicasting: an ensemble wavelet neural network for forecasting epidemics ⋮ Learning model predictive control with long short‐term memory networks ⋮ Grain Price Forecasting Using a Hybrid Stochastic Method ⋮ Time series modeling and forecasting by mathematical programming ⋮ Forecasting stock prices using hybrid non-stationary time series model with ERNN ⋮ A quantum artificial neural network for stock closing price prediction ⋮ Different approaches to forecast interval time series: a comparison in finance ⋮ System identification using autoregressive Bayesian neural networks with nonparametric noise models ⋮ Generalized exponential autoregressive models for nonlinear time series: stationarity, estimation and applications ⋮ A Statistical Recurrent Stochastic Volatility Model for Stock Markets ⋮ Forecasting of symmetric \(\alpha\)-stable autoregressive models by time series approach supported by artificial neural networks ⋮ Appraisal of excess Kurtosis through outlier-modified GARCH-type models ⋮ A Hybrid ARIMA-ANN approach for optimum estimation and forecasting of gasoline consumption ⋮ Short-Term Solar Irradiance Forecasting Using Neural Network and Genetic Algorithm ⋮ A novel auto-regressive fractionally integrated moving average–least-squares support vector machine model for electricity spot prices prediction ⋮ Autoregressive prediction with rolling mechanism for time series forecasting with small sample size ⋮ Experimental Analysis of the Accessibility of Drawings with Few Segments ⋮ Multivariate time series prediction using a hybridization of VARMA models and Bayesian networks ⋮ Employee turnover forecasting for human resource management based on time series analysis ⋮ Minimal variability Owa operator combining ANFIS and fuzzy c-means for forecasting BSE index ⋮ A New Hybrid Model Based on Triple Exponential Smoothing and Fuzzy Time Series for Forecasting Seasonal Time Series ⋮ Time series forecasting with a nonlinear model and the scatter search meta-heuristic ⋮ A data-driven forecasting approach for newly launched seasonal products by leveraging machine-learning approaches ⋮ Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review ⋮ Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models ⋮ Optimal forecasting of option prices using particle filters and neural networks ⋮ A weighted LS-SVM based learning system for time series forecasting ⋮ A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series prediction ⋮ hybridts ⋮ Forecasting \(\text{SO}_{2}\) pollution incidents by means of Elman artificial neural networks and ARIMA models ⋮ ARIMAANN ⋮ Adaptive neural network model for time-series forecasting ⋮ Stock market prediction and portfolio selection models: a survey ⋮ Exploiting the interpretability and forecasting ability of the RBF-AR model for nonlinear time series ⋮ A novel intelligent option price forecasting and trading system by multiple kernel adaptive filters ⋮ Analysis of infectious disease transmission and prediction through SEIQR epidemic model ⋮ A novel hybrid decomposition-ensemble model based on VMD and HGWO for container throughput forecasting ⋮ Exchange rate forecasting using ensemble modeling for better policy implications ⋮ Forecasting nonlinear time series with a hybrid methodology ⋮ Temporal pattern attention for multivariate time series forecasting ⋮ Development of hybrid models for forecasting time-series data using nonlinear SVR enhanced by PSO ⋮ Time series seasonal analysis based on fuzzy transforms ⋮ Comparison of ARIMA, neural networks and hybrid models in time series: tourist arrival forecasting ⋮ Forecasting Study of Shanghai’s and Shenzhen’s Stock Markets Using a Hybrid Forecast Method ⋮ Artificial Neural Network with Histogram Data Time Series Forecasting: A Least Squares Approach Based on Wasserstein Distance ⋮ Forecasting financial time series with Boltzmann entropy through neural networks ⋮ Time Series Forecasting Using Range Regression Automata
This page was built for publication: Time series forecasting using a hybrid ARIMA and neural network model