Results 141 to 150 of about 13,877 (197)
Implementation of Stacking Based ARIMA Model for Prediction of Covid-19 Cases in India
, 2020 Swaraj A +5 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.
exaly +3 more sources
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 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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ARIMA Modelling and Forecasting
2020The Auto-Regressive Integrated Moving Average (ARIMA) model is the general class of models for modelling and forecasting a time series. It consists of the AR, MA and ARMA models. In this chapter, we will discuss each of these models in turn before summarising the steps for ARIMA modelling. We conclude this chapter with a numerical example.
Timina Liu, Shuangzhe Liu, Lei Shi
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A fuzzy seasonal ARIMA model for forecasting
Fuzzy Sets and Systems, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fang-Mei Tseng, Gwo-Hshiung Tzeng
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ON PREDICTION WITH FRACTIONALLY DIFFERENCED ARIMA MODELS
Journal of Time Series Analysis, 1988Abstract. This paper considers some extended results associated with the predictors of long‐memory time series models. These direct methods of obtaining predictors of fractionally differenced autoregressive integrated moving‐average (ARIMA) processes have advantages from the theoretical point of view.
Peiris, M. S, Perera, B. J. C
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Predictive Model of Births and Deaths with ARIMA
2020The paper show the application of the ARIMA (Autoregressive integrated moving average) prediction model is made, which consists of the use of statistical data (in this case, birth and deaths in Colombia) to formulate a system in which an approximation of future data is obtained, this thanks to the help of a statistical software that allows us to ...
Diana Janeth Lancheros Cuesta +3 more
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International Journal of Forecasting, 1990
Abstract A number of empirical studies published in the forecasting literature in the 1970's and 1980's have come to the conclusion that univariate ARIMA time series modeling (Box-Jenkins) is not a more accurate univariate time series forecasting method than some simpler and older alternatives, including various exponential smoothing methods.
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Abstract A number of empirical studies published in the forecasting literature in the 1970's and 1980's have come to the conclusion that univariate ARIMA time series modeling (Box-Jenkins) is not a more accurate univariate time series forecasting method than some simpler and older alternatives, including various exponential smoothing methods.
openaire +1 more source