Results 211 to 220 of about 145,010 (267)

Forecasting global monthly cotton prices: the superiority of NNAR models over traditional models. [PDF]

Front Artif Intell
Limbu Sanwa R, Khadka R, Chi YN.
europepmc   +1 more source

Time-series-based forecasting of accident-related referrals to Maharaj Nakorn Chiang Mai Hospital, Northern Thailand, during each year and especially the "Seven dangerous Days" periods. [PDF]

BMC Public Health
Srikummoon P, Traisathit P, Chittawatanarat K, Chandacham K, Kittikhunakon A, Piriyahaphan T, Kawilapat S, Chotirosniramit N.   +7 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

ARIMA model's superiority over f-ARIMA model

WCC 2000 - ICCT 2000. 2000 International Conference on Communication Technology Proceedings (Cat. No.00EX420), 2002
We 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
openaire   +1 more source

ARIMA Processes With ARIMA Parameters

Journal of Business & Economic Statistics, 1993
This 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
openaire   +2 more sources

Forecasting stock index returns using ARIMA-SVM, ARIMA-ANN, and ARIMA-random forest hybrid models

International Journal of Banking, Accounting and Finance, 2014
The purpose of this paper is to develop and identify the best hybrid model to predict stock index returns. We develop three different hybrid models combining linear ARIMA and non-linear models such as support vector machines (SVM), artificial neural network (ANN) and random forest (RF) models to predict the stock index returns. The performance of ARIMA-
Manish Kumar, M. Thenmozhi
openaire   +1 more source

???????????????????????? ???????????? ARIMA ?????? ?????????????????????????? ?????????????? ?????????????????? ?????????????? ??????????????

2013
Forecast of profitable part of budget of Ukraine in 2011 is built.
openaire   +3 more sources

Traj-ARIMA

Proceedings of the Third International Workshop on Computational Transportation Science, 2010
Trajectory data play an important role in analyzing real world applications that involve movement features, e.g. natural and social phenomena such as bird migration, transportation management, urban planning and tourism analysis. Such trajectory data are a speical kind of time series with another focus on the spatial dimension besides the temporal one.
openaire   +1 more source

???????????????????? ARIMA-???????????? ???????????????????????? ???????????????????? ???????????????????????? ?? ?????????? ?? ?????????????? (???? ?????????????? ???????????????????? ????????????????????)

2015
?? ???????????? ???????????????????????? ARIMA-???????????? ???????????????????? ?????????? ?? ???????????????????????? ?????????????? ???? ?????????????? ???????????????????? ????????????????????. ?????????????????? ???????????????????? ???????????? ?? ?????????????????????????????? ???????????????? ???????????????????? ???????? ?????????????????? ????
openaire   +2 more sources

ARIMA Algebra

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, David McDowall, Bradley J. Bartos   +2 more
openaire   +1 more source