Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real‐Time Application

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Forecasting with Periodic Autoregressive Time Series Models

This chapter is concerned with forecasting univariate seasonal time series data using periodic autoregressive models We show how one should account for unit roots and deterministic terms when generating out of sample forecasts We illus trate the models for various quarterly UK consumption series This is the rst version July of a chapter that is to be prepared for potential inclusion in the Comp...

متن کامل

Forecasting with time-varying vector autoregressive models

The purpose of this paper is to propose a time-varying vector autoregressive model (TV-VAR) for forecasting multivariate time series. The model is casted into a state-space form that allows flexible description and analysis. The volatility covariance matrix of the time series is modelled via inverted Wishart and singular multivariate beta distributions allowing a fully conjugate Bayesian infere...

متن کامل

Seasonal Autoregressive Models for Estimating the Probability of Frost in Rafsanjan

This work develops a statistical model to assess the frost risk in Rafsanjan, one of the largest pistachio production regions in the world. These models can be used to estimate the probability that a frost happens in a given time-period during the year; a frost happens after 10 warm days in the growing season. These probability estimates then can be used for: (1) assessing the agroclimate risk ...

متن کامل

Forecasting with prediction intervals for periodic autoregressive moving average models

Periodic autoregressive moving average (PARMA) models are indicated for time series whose mean, variance and covariance function vary with the season. In this study, we develop and implement forecasting procedures for PARMA models. Forecasts are developed using the innovations algorithm, along with an idea of Ansley. A formula for the asymptotic error variance is provided, so that Gaussian pred...

متن کامل

seasonal forecasting of agriculture gross domestic production in iran: application of periodic autoregressive model

agriculture as one of the major economic sectors of iran, has an important role in gross domestic production by providing about 14% of gdp. this study attempts to forecast the value of the agriculture gdp using periodic autoregressive model (par), as the new seasonal time series techniques. to address this aim, the quarterly data were collected from march 1988 to july 1989. the collected data w...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Water Resources Research

سال: 2018

ISSN: 0043-1397,1944-7973

DOI: 10.1002/2017wr022007