نتایج جستجو برای: روش arima

تعداد نتایج: 372572  

2007
S. MOHAN N. ARUMUGAM N. Arumugam

Abstract Evapotranspiration (ET) is an important process in the hydrological cycle and needs to be accurately quantified for proper irrigation scheduling and optimal water resources systems operation. The time variant characteristics of ET necessitate the need for forecasting ET. In this paper, two techniques, namely a seasonal ARIMA model and Winter's exponential smoothing model, have been inv...

Journal: :World journal of gastroenterology 2004
Peng Guan De-Sheng Huang Bao-Sen Zhou

AIM To study the application of artificial neural network (ANN) in forecasting the incidence of hepatitis A, which had an autoregression phenomenon. METHODS The data of the incidence of hepatitis A in Liaoning Province from 1981 to 2001 were obtained from Liaoning Disease Control and Prevention Center. We used the autoregressive integrated moving average (ARIMA) model of time series analysis ...

2018
Jingzhou Xin Jianting Zhou Simon X. Yang Xiaoqing Li Yu Wang

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mini...

2013
Razana Alwee Siti Mariyam Hj Shamsuddin Roselina Sallehuddin

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to in...

2014
H. R. Wang C. Wang X. Lin J. Kang

Auto regressive integrated moving average (ARIMA) models have been widely used to calculate monthly time series data formed by interannual variations of monthly data or inter-monthly variation. However, the influence brought about by inter-monthly variations within each year is often ignored. An improved ARIMA model is developed in this study accounting for both the interannual and inter-monthl...

Journal: :BMC Health Services Research 2005
Arul Earnest Mark I Chen Donald Ng Leo Yee Sin

BACKGROUND The main objective of this study is to apply autoregressive integrated moving average (ARIMA) models to make real-time predictions on the number of beds occupied in Tan Tock Seng Hospital, during the recent SARS outbreak. METHODS This is a retrospective study design. Hospital admission and occupancy data for isolation beds was collected from Tan Tock Seng hospital for the period 14...

2013
Hye-Kyung Yu Na-Young Kim Sung Soon Kim Chaeshin Chu Mee-Kyung Kee

OBJECTIVES From the introduction of HIV into the Republic of Korea in 1985 through 2012, 9,410 HIV-infected Koreans have been identified. Since 2000, there has been a sharp increase in newly diagnosed HIV-infected Koreans. It is necessary to estimate the changes in HIV infection to plan budgets and to modify HIV/AIDS prevention policy. We constructed autoregressive integrated moving average (AR...

2014
Lingling Zhou Lijing Yu Ying Wang Zhouqin Lu Lihong Tian Li Tan Yun Shi Shaofa Nie Li Liu

BACKGROUNDS/OBJECTIVE Schistosomiasis is still a major public health problem in China, despite the fact that the government has implemented a series of strategies to prevent and control the spread of the parasitic disease. Advanced warning and reliable forecasting can help policymakers to adjust and implement strategies more effectively, which will lead to the control and elimination of schisto...

2011
Karin Kandananond

Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and multiple linear regression (MLR)—were utilized to formulate prediction models of t...

2014
Lida Barba Nibaldo Rodríguez Cecilia Montt

Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel m...

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