This study develops a sedimentation process model that simulate the effects of inflow water quality, treatment flow rate and outflow water quality. The model uses transfer function ARIMA (Auto-Regressive Moving Average) for reflecting the dynamic characteristics of the system The sedimentation model for outflow water turbidity are separated into low and high turbidity by input variables, turbid...

Due to notable depletion of fuel, non-conventional energy aids the present grid for Power management across the country. Wind energy indeed has major contribution next to solar. Prediction of wind power is essential to integrate wind farms into the grid. Due to intermittency and variability of wind power, forecasting of wind behavior becomes intricate. Wind speed forecasting tools can resolve t...

This paper applies the Hodrck-Prescott (HP) filter to forecast short-term residential real estate prices under cyclical movements. We separate the trend component from the cyclical component. We show that each regional residential market reacts not only to previous price movements, but also that these regional markets react to previous shocks under Auto Regressive Integrated Moving Average (ARI...

This paper intends to propose an integrated method which combines selforganizing map (SOM) network with genetic algorithm (GA) and particle swarm optimization (PSO)-based (ISGP) algorithm to train the radial basis function (RBF) network for function approximation. The experimental results for three benchmark problems indicated that such integration can have better performance. In addition, usin...

Citation: Nakamura N, Kinoshita T and Fukuyama H (2017) Response Analysis and Auto-Regressive Exogenous Modeling of a SteelReinforced Concrete High-Rise Building during the 2011 Off the Pacific Coast of Tohoku Earthquake. Front. Built Environ. 3:74. doi: 10.3389/fbuil.2017.00074 response analysis and autoregressive exogenous Modeling of a steel-reinforced concrete high-rise Building during the ...

The objective of the study was to describe seasonality of hospitalizations for heart failure in tropical climate as it has been described in cold climates. Seasonal Auto-regressive Integrated Moving-Average model was applied to time-series data of heart failure hospitalizations between 1996 and 2004 in Niteroi (Southeastern Brazil), collected from the Brazilian National Health Service Database....

in this study, the situation of iran, u.s and turkey's pistachio export is investigated. to this purpose, revealed comparative advantage (rca) index is calculated based on agricultural and total economy export, separately, then forecasted by using auto- regressive integrated moving average (arima) approached, for 2008-2013. the results show that considering both commodity baskets, turkey a...

In statistics, signal processing, and mathematical finance; a time series is a sequence of data points that measured at uniform time intervals. The prediction of time series is a very complicated process. In this paper, an improved Adaptive Neuro Fuzzy Inference System (ANFIS) is taken for predicting Mackey-Glass which is one of the chaotic time series. In the modeling of linear and stationary ...

The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT) along with the Auto Regressive Moving Average (ARMA) is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE). A simulation study has been conducted by comparing the forecasting results using...

In this paper, we propose a time series based method for analyzing and predicting personal medical data. First, we introduce an auto-regressive integrated moving average model which is good for all time series processes. Second, we describe how to identify a personalized time series model based on the patient’s history information, followed by estimating the parameters in the model. Furthermore...