Multilayer feedforward networks are universal approximators
Neural Networks
Time series forecasting using neural networks
APL '94 Proceedings of the international conference on APL : the language and its applications: the language and its applications
Neural network models for time series forecasts
Management Science
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Expert Systems with Applications: An International Journal
Suitability of different neural networks in daily flow forecasting
Applied Soft Computing
A neural network ensemble method with jittered training data for time series forecasting
Information Sciences: an International Journal
Locally recurrent neural networks for wind speed prediction using spatial correlation
Information Sciences: an International Journal
Towards the evaluation of time series protection methods
Information Sciences: an International Journal
Approximation capabilities of multilayer fuzzy neural networks on the set of fuzzy-valued functions
Information Sciences: an International Journal
Distortion-free predictive streaming time-series matching
Information Sciences: an International Journal
Integrating induction and deduction for noisy data mining
Information Sciences: an International Journal
A locally linear RBF network-based state-dependent AR model for nonlinear time series modeling
Information Sciences: an International Journal
Information Sciences: an International Journal
New model for system behavior prediction based on belief rule based systems
Information Sciences: an International Journal
A class of hybrid morphological perceptrons with application in time series forecasting
Knowledge-Based Systems
On the use of cross-validation for time series predictor evaluation
Information Sciences: an International Journal
Sparsely connected neural network-based time series forecasting
Information Sciences: an International Journal
Discovering influencers for marketing in the blogosphere
Information Sciences: an International Journal
Revenue forecasting using a least-squares support vector regression model in a fuzzy environment
Information Sciences: an International Journal
A Morphological-Rank-Linear evolutionary method for stock market prediction
Information Sciences: an International Journal
Recentness biased learning for time series forecasting
Information Sciences: an International Journal
Motion modeling and neural networks based yaw control of a biomimetic robotic fish
Information Sciences: an International Journal
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In this study, an artificial neural network (ANN) structure is proposed for seasonal time series forecasting. The proposed structure considers the seasonal period in time series in order to determine the number of input and output neurons. The model was tested for four real-world time series. The results found by the proposed ANN were compared with the results of traditional statistical models and other ANN architectures. This comparison shows that the proposed model comes with lower prediction error than other methods. It is shown that the proposed model is especially convenient when the seasonality in time series is strong; however, if the seasonality is weak, different network structures may be more suitable.