A Hybrid Model of Differential Evolution with Neural Network on Lag Time Selection for Agricultural Price Time Series Forecasting

2017 ◽  
pp. 155-167
Author(s):  
Chen ZhiYuan ◽  
Le Dinh Van Khoa ◽  
Lee Soon Boon
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Differential Evolution ◽  
Hybrid Model ◽  
Lag Time ◽  
Time Series Forecasting ◽  
Selection For ◽  
Agricultural Price ◽  
Time Selection

scholarly journals Hybrid Model for Time Series of Complex Structure with ARIMA Components

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1122
Author(s):  
Oksana Mandrikova ◽  
Nadezhda Fetisova ◽  
Yuriy Polozov
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Hybrid Model ◽  
Complex Structure ◽  
Arima Model ◽  
Ionospheric Parameter ◽  
Arima Models ◽  
Complicated Structure ◽  
Threshold Functions ◽  
Anomalous Component

A hybrid model for the time series of complex structure (HMTS) was proposed. It is based on the combination of function expansions in a wavelet series with ARIMA models. HMTS has regular and anomalous components. The time series components, obtained after expansion, have a simpler structure that makes it possible to identify the ARIMA model if the components are stationary. This allows us to obtain a more accurate ARIMA model for a time series of complicated structure and to extend the area for application. To identify the HMTS anomalous component, threshold functions are applied. This paper describes a technique to identify HMTS and proposes operations to detect anomalies. With the example of an ionospheric parameter time series, we show the HMTS efficiency, describe the results and their application in detecting ionospheric anomalies. The HMTS was compared with the nonlinear autoregression neural network NARX, which confirmed HMTS efficiency.

scholarly journals Recurrent Multiplicative Neuron Model Artificial Neural Network for Non-linear Time Series Forecasting

2014 ◽  
Vol 41 (2) ◽  
pp. 249-258 ◽  
Author(s):  
Erol Egrioglu ◽  
Ufuk Yolcu ◽  
Cagdas Hakan Aladag ◽  
Eren Bas
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Neuron Model ◽  
Linear Time ◽  
Time Series Forecasting ◽  
Non Linear ◽  
Artificial Neural

PSO based neural network for time series forecasting

2009 ◽  
Author(s):  
Girish K. Jha ◽  
Parimala Thulasiraman ◽  
Ruppa K. Thulasiram
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Series Forecasting

Financial Time Series Forecasting with Multi-Modality Graph Neural Network

2021 ◽  
pp. 108218
Author(s):  
Dawei Cheng ◽  
Fangzhou Yang ◽  
Sheng Xiang ◽  
Jin Liu
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Financial Time Series ◽  
Time Series Forecasting ◽  
Financial Time

An ARIMA-ANN Hybrid Model for Time Series Forecasting

2013 ◽  
Vol 30 (3) ◽  
pp. 244-259 ◽  
Author(s):  
Li Wang ◽  
Haofei Zou ◽  
Jia Su ◽  
Ling Li ◽  
Sohail Chaudhry
Keyword(s):  
Time Series ◽  
Hybrid Model ◽  
Time Series Forecasting
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