BACKGROUND Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease. METHODS The autoregressive integrated moving average (ARIMA) model and the generalized regression neural network (GRNN) model were used to fit the incidence data ...

Both theoretical and empirical findings have suggested that combining different models can be an effective way to improve the predictive performance of each individual model. It is especially occurred when the models in the ensemble are quite different. Hybrid techniques that decompose a time series into its linear and nonlinear components are one of the most important kinds of the hybrid model...

Crude oil is one of the non-renewable power sources and lifeblood contemporary industry. Every significant change in price crude (CO) will have an effect on how global economy, including COVID-19, develops. This study developed a novel hybrid prediction technique that depends local mean decomposition, Autoregressive Integrated Moving Average (ARIMA), Long Short-term Memory (LSTM) models to incr...

Abstract Long Short-Term Memory (LSTM) is one of the developments from Recurrent Neural Network (RNN) architecture. In this paper, we use LSTM architecture for modeling and forecasting Indonesian Composite Stock Price Index (IHSG) closing value data. We also compare performance method with ARIMA Radial Basis Function (RBF) method. implementation, both R Python open source software. For empirica...

The Hungarian mortality rates were analyzed by autoregressive integrated moving average models and seasonal time series models examined the data of acute childhood lymphoid leukaemia. The mortality data may be analyzed by time series methods such as autoregressive integrated moving average (ARIMA) modelling. This method is demonstrated by two examples: analysis of the mortality rates of cerebro...

The quality of purchased parts is an important factor affecting the whole quality of the products, that how to grasp the size and trend of the defective rate in the warehouse-in inspection, becomes a meaningful theme in the quality control, through studying the modeling method of time series ARIMA model, applies variance analysis to the time series modeling, and carries out the variance analysi...

The paper presents an innovative approach that integrates the arbitrage pricing theory (APT) and artificial neural networks (ANN) to support portfolio management. The integrated approach takes advantage of the synergy between APT and ANN in extracting risk factors, predicting the trend of individual risk factor, generating candidate portfolios, and choosing the optimal portfolio. It uses quadra...

Abstract: We present a method for optimizing adaptation laws that are generalizations of the LMS algorithm. Timevarying parameters of linear regression models are estimated in situations where the regressors are stationary or have slowly time-varying properties. The parameter variations are modeled as ARIMA-processes and the aim is to use such prior information to provide high performance filte...