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Autoregressive Moving Average Recurrent Neural Networks Applied to the Modelling of Colombian Exchange Rate
(International Journal of Artificial Intelligence, 2018)
Modeling and prediction of time series has required in recent times a lot of attention, due to the necessity to have to make with accurate tools a right decision and to surpass theoretical, conceptual and practical limitations ...
Earthquake Magnitude and Frequency Forecasting in Northeastern Algeria using Time Series Analysis
This study uses two different time series forecasting approaches (parametric and non-parametric) to assess a frequency and magnitude forecasting of earthquakes above Mw 4.0 in Northeastern Algeria. The Autoregressive ...
Predicting hourly ozone concentrations using wavelets and ARIMA models
(2019)
In recent years, air pollution has been a major concern for its implications on human health. Specifically, ozone (O-3) pollution is causing common respiratory diseases. In this paper, we illustrate the process of modeling ...
Development of new hybrid model of discrete wavelet decomposition and autoregressive integrated moving average (ARIMA) models in application to one month forecast the casualties cases of COVID-19
Everywhere around the globe, the hot topic of discussion today is the ongoing and fast-spreading coronavirus disease (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARSCOV-2). Earlier ...
Análise do comportamento futuro do preço de compra do cimento Portland CP IV
(Universidade Federal de Santa MariaBrasilUFSMCentro de Tecnologia, 2016-11-25)
The main purpose of this research is to predict the Portland CP IV cement purchase price for a supply materials store, by means of autoregressive integrated moving average (ARIMA) forecasting models and forecast combinations ...
Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents
(2014)
Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. Thestrategy of forecasting ...
Forecast of sea surface temperature off the Peruvian coast using an autoregressive integrated moving average modelPrevisión de la temperatura superfi cial del mar frente a la costa peruana mediante un modelo autorregresivo integrado de media móvil
(Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Biológicas, 2007)
Using the Statistical Machine Learning Models ARIMA and SARIMA to Measure the Impact of Covid-19 on Official Provincial Sales of Cigarettes in Spain
From a public health perspective, tobacco use is addictive by nature and triggers several cancers, cardiovascular and respiratory diseases, reproductive disorders, and many other adverse health effects leading to many ...