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Energies, 2023 Forecasting peak electrical energy consumption is important because it allows utilities to properly plan for the production and distribution of electrical energy. This reduces operating costs and avoids power outages. In addition, it can help reduce environmental impact by allowing for more efficient power generation and reducing the need for ...
Birregah Babiga, Babiga Birregah
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ARIMA and Wavelet-ARIMA Models for the Signal Produced by Ultrasound in Diesel
2021 25th International Conference on System Theory, Control and Computing (ICSTCC), 2021This article presents new results on modeling the signals collected in an experiment related to the propagation of ultrasound in liquids. An experimental set-up designed for this purpose was utilized for capturing the signals produced in the cavitation field by ultrasound when the studied liquid was diesel.
Alina Barbulescu +1 more
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ARIMA Processes With ARIMA Parameters
Journal of Business & Economic Statistics, 1993This article introduces a general class of nonlinear and nonstationary time series models whose basic scheme is an autoregressive integrated moving average (ARIMA). The main feature is that the parameters are assumed to behave like a vector ARIMAx model in which the exogenous (x) component is represented by the regressors of the observable process. For
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ARIMA model's superiority over f-ARIMA model
WCC 2000 - ICCT 2000. 2000 International Conference on Communication Technology Proceedings (Cat. No.00EX420), 2002We make it clear that the SRD model is better than the LRD model with time-scale resolution over 60 seconds. The conclusion was derived in the following way. We used the real traffic data observed at our university's router, which is the gateway to the Internet for approximately 1000 machines.
Y. Takahashi, H. Aida, T. Saito
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2017
The goal of Chapter 2 is to derive the properties of common processes and, based on these properties, to develop a general scheme for classifying processes. Stationary processes includes white noise, moving average (MA), and autoregressive (AR) processes. MA and AR models can approximate mixed ARMA models.
Richard McCleary +2 more
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The goal of Chapter 2 is to derive the properties of common processes and, based on these properties, to develop a general scheme for classifying processes. Stationary processes includes white noise, moving average (MA), and autoregressive (AR) processes. MA and AR models can approximate mixed ARMA models.
Richard McCleary +2 more
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Management Science, 2005
This paper presents a multistage supply chain model that is based on Autoregressive Integrated Moving Average (ARIMA) time-series models. Given an ARIMA model of consumer demand and the lead times at each stage, it is shown that the orders and inventories at each stage are also ARIMA, and closed-form expressions for these models are given.
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This paper presents a multistage supply chain model that is based on Autoregressive Integrated Moving Average (ARIMA) time-series models. Given an ARIMA model of consumer demand and the lead times at each stage, it is shown that the orders and inventories at each stage are also ARIMA, and closed-form expressions for these models are given.
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2015
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?? ???????????? ???????????????????????? ARIMA-???????????? ???????????????????? ?????????? ?? ???????????????????????? ?????????????? ???? ?????????????? ???????????????????? ????????????????????. ?????????????????? ???????????????????? ???????????? ?? ?????????????????????????????? ???????????????? ???????????????????? ???????? ?????????????????? ????
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ARIMAmmse: An Improved ARIMA-based
30th Annual International Computer Software and Applications Conference (COMPSAC'06), 2006Productivity is a critical performance index of process resources. As successive history productivity data tends to be auto-correlated, time series prediction method based on Auto-Regressive Integrated Moving Average (ARIMA) model was introduced into software productivity prediction by Humphrey et al. In this paper, a variant of their prediction method
Li Ruan +5 more
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