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...

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 ...

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...

Abstract—The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the correspondi...

We develop a new class of Continuous-time Auto-Regressive Fractionally Integrated Moving-Average (CARFIMA) models which are useful for modelling regularly-spaced and irregularly-spaced discrete-time long-memory data. We derive the autocovariance function of a stationary CARFIMA model, and study maximum likelihood estimation of a regression model with CARFIMA errors, based on discrete-time data ...

A definition of reliability appropriate for systems containing significant software that includes trustworthiness and is independent of requirements will be stated and argued for. The systems addressed will encompass the entire product development process as well as both product and its documentation. Cost incurred as a result of faults will be shown to be appropriate as a performance measureme...

and Applied Analysis 3 is the order of regular differences and φ(B) and θ(B) are, respectively, defined as follows φ (B) = 1 − φ 1 B − φ 2 B 2 − ⋅ ⋅ ⋅ − φ p B p θ (B) = 1 − θ 1 B − θ 2 B 2 − ⋅ ⋅ ⋅ − θ q B q . (5) Random errors, ε t , are assumed to be independently and identically distributed with a mean of zero and a constant variance of σ, and the roots of φ(x) = 0 and θ(x) = 0 all lie outsid...

Cognitive radio requires real time monitoring of the spectrum to determine the frequency of transmission. Spectrum analysers tend to employ a slow frequency sweep and hence such measurements can only be used for modelling of the spectrum, which can provide vital information for frequency planning and management. Occupancy measurements every hour over a seven-day period were performed in the UK ...

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain efficient estimates of...

A key application of long memory time series models concerns innation. Long memory implies that shocks have a long-lasting eeect. It may however be that empirical evidence for long memory is caused by neglecting one or more level shifts. Since such level shifts are not unlikely for innation, where the shifts may be caused by sudden oil price shocks, we examine whether evidence for long memory (...