In this paper, a modified estimation algorithm has been developed refers to Covariance Shaping Least Square (CSLS) estimation based on the quantum mechanical concepts and constraints. The algorithm has been applied to Auto Regressive Moving Average (ARMA models with various parameter values. The same models can be applied with Colored Noise which estimates the bias in the parameter and the vali...

The paper focuses on the stochastic forecast of the financial sustainability ofbasic pension, based on predictions for the population of China. The population was calculated iteratively by using Leslie matrix. An auto-regressive moving average model was adapted for the predictions of the fertility rates and the mortality rates. The Monte Carlo stochastic method was adapted for the projections o...

Firms use time-series forecasting methods to predict sales. However, it is still a question which method forecaster best, if only single forecast needed. This study investigates and evaluates different sales methods: multiplicative Holt-Winters (HW), additive HW, seasonal auto regressive integrated moving average (SARIMA) [a variant of (ARIMA)], long short-term memory (LSTM) recurrent neural ne...

In this article, we present a not fully connected recurrent network applied to the problem of load forecasting. Although many authors have pointed out that Recurrent Networks were able to modelize NARMAX process (Non linear Auto Regressive Moving Average with eXogeneous variables), we present a constructing scheme for the MA part. In addition we present a modification of the learning step which...

Road section data packet is very necessary for the estimation and prediction in short-time traffic condition. However, previous researches on this problem are lack of quantitative analysis. A section correlation analyzing method with traffic flow microwave data is proposed for this problem. It is based on the metric multidimensional scaling theory. With a dissimilarity matrix, scalar product ma...

This paper presents a method to simulate the growth of the facial/head model of a person from childhood to adulthood. The method works by generating continuous data of standard landmarks using auto-regressive moving average based on anthropometry of the head/face. The standard landmarks are assigned to the particular head and face, and vertices of the growing head/facial model are calculated by...

During this field survey, we measured and recorded a few quality parameters of wireless communication in a substation switchyard. A microprocessor-based measurement system was used for data collection and analysis. We investigated long-term noise variation in this specific environment. Based on our measurement and post-processing analysis we conclude that the so-called Classic/Bayesian assumpti...

In this paper a new least-squares (LS) approach is used to model the discrete-time fractional differintegrator. This approach is based on a mismatch error between the required response and the one obtained by the difference equation defining the auto-regressive, moving-average (ARMA) model. In minimizing the error power we obtain a set of suitable normal equations that allow us to obtain the AR...

This paper deals with the application of the Multi Objective Generalized Predictive Control (MOGPC) to level control in a laboratory process. The major characteristic of the considered plant is that the manual draining vane can take many positions causing changes in plant dynamics and strong disturbances in the process. The controller is based on a set of Controlled Auto Regressive Integrated M...