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Aggregation operators with moving averages
(Springer, 2019)
A moving average is an average that aggregates a subset of variables from the set and moves across the sample. It is widely used in time-series forecasting. This paper studies the use of moving averages in some representative ...
Coherence and uniqueness theorems for averaging processes in statistical mechanics
(Kluwer Academic PublDordrechtHolanda, 2003)
OWA operators in the calculation of the average green-house gases emissions
(IOS, 2020)
This study proposes, through weighted averages and ordered weighted averaging operators, a new aggregation system for the investigation of average gases emissions. We present the ordered weighted averaging operators gases ...
Aggregation systems for sales forecasting
(Elsevier, 2015)
Sales forecasting consists of calculating the expected sales of a specific product or company. An important issue
when dealing with sales forecasting is the calculation of the average sales, usually using the arithmetic ...
Nonlinear Dynamic Average Model of a DC-DC Converter
(Institute Of Electrical And Electronics Engineers, 2014-08)
A nonlinear dynamical average model of a dc-dc converter is presented. The converter under study has a particular feature. In this converter, classical average analysis cannot be applied because the ripple cannot be neglected ...
Probabilistic OWA distances applied to asset management
(Springer, 2018-08)
Average distances are widely used in many fields for calculating the distances between two sets of elements. This paper presents several new average distances by using the ordered weighted average, the probability and the ...
Bounds for Estimators of Ergodic Averages
(Hikari, 2013-01)
We consider different ergodic averages and estimate the measure of the set of points in which the averages apart from a given value. The cases considered are empirical measures of cylinders in symbolic spaces and averages ...
String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
(Iop Publishing Ltd, 2014-05-01)
We study the maximum likelihood model in emission tomography and propose a new family of algorithms for its solution, called string-averaging expectation maximization (SAEM). In the string-averaging algorithmic regime, the ...