The paper discusses the properties of Auto-Regressive Integrated Moving Average (ARIMA) models and proceeds to estimate a model for monthly evolution annual inflation rate in Moldova from January 2013 October 2021. aim is develop relying exclusively upon historical as an additional instrument forecasting purposes. estimated explains close 97 % variation over model’s estimation period used gener...

Purpose: This work aims to evaluate demand forecasting models determine if using exogenous factors and machine learning techniques helps improve performance compared univariate statistical models, allowing manufacturing companies manage better.Design/methodology/approach: We implemented a multivariate Auto-Regressive Moving Average with eXogenous input (ARMAX) model Neural Network-ARMAX (NN-ARM...

The dynamic model of the milk cooling process from 36°C to 4°C using chilled water available at 2°C has been carried out. temperature is kept constant by a refrigeration unit. being studied was Packo brand tank belonging KUD SAE Pujon (Malang - Indonesia). A fundamental heat balance method used derive model, leading first-order transfer function process. For 2 hours then, gain and time values a...

In this paper, instead of the usual Gaussian noise assumption, t-distribution noise is assumed. AMaximum Likelihood Estimator using the most recent N measurements is proposed for the Auto-Regressive-Moving-Average with eXogenous input (ARMAX) process with this assumption. The proposed estimator is robust to outliers because the ‘thick tail’ of the t-distribution reduces the effect of large erro...

It may be critical for drivers to have information about the occupancy rates of parking spaces around their destination in order reduce traffic density, a non-negligible part which caused by trips find an available space. In this study, we predict (and thus, space availability) using three different techniques: (i) auto-regressive integrated moving average model, (ii) seasonal model and (iii) n...

Model reduction methods aim to describe complex dynamic phenomena using only relevant dynamical variables, decreasing computational cost, and potentially highlighting key mechanisms. In the absence of special features such as scale separation or symmetries, time evolution these variables typically exhibits memory effects. Recent work has found a variety data-driven model be effective for repres...

in this study, the situation of iran, u.s and turkey's pistachio export is investigated. to this purpose, revealed comparative advantage (rca) index is calculated based on agricultural and total economy export, separately, then forecasted by using auto- regressive integrated moving average (arima) approached, for 2008-2013. the results show that considering both commodity baskets, turkey and ir...

Abstract: In this paper we discuss a two model multilayer neural network controller for adaptive control of blood pressure using sodium nitroprusside. A model with auto-regressive moving average, represent the dynamics of the system and a modified backpropagation training algorithm are used to design the control system to meet specified objectives of design and clinical constraints. Controller ...