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Tytuł:
Forecasting the sales of console games for the Italian market
Autorzy:
Rossetti, Renato
Powiązania:
https://bibliotekanauki.pl/articles/425197.pdf
Data publikacji:
2019
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
exponential smoothing
SARIMA
forecast
videogames
Opis:
In videogames industry, time series analysis can be very useful in determining the general evolution and behaviour of the market dynamics. These methods are applicable to any time series forecasting problem, regardless of the application sector. This article discusses time series approaches to forecast the sales of console games for the Italian market. In particular two univariate techniques were evaluated, exponential smoothing and the SARIMA technique. The aim is to exploit the capabilities of these statistical methods in order to have a comparison of the results and to choose the most accurate model through an ex-post evaluation. Using monthly time-series data from November 2005 to September 2017, the selection of the most suitable model was indicated by the smallest value of the measures of accuracy (MAPE, sMAPE, RMSE) for the out-of-sample observations regarding the period October 2017-September 2018. The implementation of the models was done using Forecast PRO and Gretl. The time series involved is related to the sales regarding the first party manufacturers of consoles and handhelds (Microsoft, Sony and Nintendo).
Źródło:
Econometrics. Ekonometria. Advances in Applied Data Analytics; 2019, 23, 3; 76-96
1507-3866
Pojawia się w:
Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Predictive modeling and analysis of changes migrations in Poland
Autorzy:
Monika Nawrocka, Monika Nawrocka
Powiązania:
https://bibliotekanauki.pl/articles/1179772.pdf
Data publikacji:
2017
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
dynamics migration
exponential smoothing
forecasting
Opis:
The development of the research in economy has shown that conducting mathematical modeling and statistics is an effective instrument for diagnosing the progress phenomenon of socio-economic. It provides the information about the dynamics of result changeability in different periods of time. Additionally statistical analysis allows determining the prediction for periods of future and past years. Migrations is characterized by the quality of being measurable because it includes quantitative data. In recent years, demonstrate high dynamics. Conducting the analyses and calculations based on methods and statistical instruments will result in the opportunity to compare, group, analysis variables, specify trends and designate the diagnoses of achieved sports results with the implementation of the optimum vector of variables of independent variable of migrations. An analysis of the dynamics migration variability was carried out on the basis of data from the website of the main statistical office, in this article. Used the statistical methods and the testing of interdependencies. Additionally, the models of time series have been used for the sake of the analysis. The most significant aim of the analysis of the dynamics is the designation of predictions. The use of the model of time series has the task of the specification of the change of the phenomenon level in time.
Źródło:
World Scientific News; 2017, 72; 467-481
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Exponential smoothing and resampling techniques in time series prediction
Autorzy:
Neves, Maria
Cordeiro, Clara
Powiązania:
https://bibliotekanauki.pl/articles/729996.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
time series
bootstrap
exponential smoothing
forecasting
accuracy measures
Opis:
Time series analysis deals with records that are collected over time. The objectives of time series analysis depend on the applications, but one of the main goals is to predict future values of the series. These values depend, usually in a stochastic manner, on the observations available at present. Such dependence has to be considered when predicting the future from its past, taking into account trend, seasonality and other features of the data. Some of the most successful forecasting methods are based on the concept of exponential smoothing. There are a variety of methods that fall into the exponential smoothing family, each having the property that forecasts are weighted combinations of past observations. But time series analysis needs proper statistical modeling. The model that better describes the behavior of the series in study can be crucial in obtaining 'good' forecasts. Departures from the true underlying distribution can adversely affect those forecasts. Resampling techniques have been considered in many situations to overcome that difficulty. For time series, several authors have proposed bootstrap methodologies. Here we will present an automatic procedure built in R language that first selects the best exponential smoothing model (among a set of possibilities) for fitting the data, followed by a bootstrap approach for obtaining forecasts. A real data set has been used to illustrate the performance of the proposed procedure.
Źródło:
Discussiones Mathematicae Probability and Statistics; 2010, 30, 1; 87-101
1509-9423
Pojawia się w:
Discussiones Mathematicae Probability and Statistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Unit load devices (ULD) demand forecasting in the air cargo for optimal cost management
Autorzy:
Mikram, Mounia
Rhanoui, Maryem
Yousf, Siham
Briwa, Houda
Powiązania:
https://bibliotekanauki.pl/articles/1837377.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
air transport
ULD
machine learning
ARIMA
exponential smoothing
Opis:
In recent decades, the airline industry has become very competitive. With the advent of large aircraft in service, unit load devices (ULD) have become an essential ele‐ ment for efficient air transport. They can load a large amount of baggage, cargo or mail using only one unit. Since this results in fewer units to load, saving time and efforts of ground crews and helping to avoid delayed flig‐ hts. However, a deficient loading of the units causes ope‐ rating irregularities, costing the company and contribu‐ ting to the dissatisfaction of the customers. In contrast, an excess load of containers is at the expense of cargo. In this paper we propose an approach to predict the de‐ mand for baggage in order to optimize the management of its ULD flow. Specifically, we build prediction models: ARIMA following the BOX‐JENKINS approach and expo‐ nential smoothing methods, in order to obtain more accu‐ rate forecasts. The approach is tested using the operatio‐ nal data of flight processing and the results are compared with four benchmark method (SES, DES, Holt‐Winters and Naive prediction) using different performance indicators: MAE, MSE, MAPE , WAPE, RMSE, SMPE. The results obtai‐ ned with the exponential smoothing methods surpass the benchmarks by providing more accurate forecasts.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 3; 71-80
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Towards a target employment rate within age and gender groups
Autorzy:
Jaworski, Stanisław
Zielińska-Kolasińska, Zofia
Powiązania:
https://bibliotekanauki.pl/articles/1917017.pdf
Data publikacji:
2021-12-08
Wydawca:
Główny Urząd Statystyczny
Tematy:
employment rate
exponential smoothing
forecasting
state space approach
Opis:
Quarterly employment rates in European countries are analysed in terms of the likelihood of achieving a specific employment rate within age and gender groups in a five-year horizon. The German employment rate serves as a benchmark for this research. The likelihood is estimated by a Monte-Carlo simulation based on the class of exponential smoothing models. The research presents a pessimistic prognosis of employment rates in European countries with respect to young and partly to older workers.
Źródło:
Statistics in Transition new series; 2021, 22, 4; 213-225
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment
Autorzy:
Lenart, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/2076445.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
HICP
seasonal volatility
exponential smoothing
nowcasting
predictive distribution
logscore
Opis:
The aim of this paper is to examine the problem of existing seasonal volatility in total and disaggregated HICP for Baltic Region countries (Denmark, Estonia, Latvia, Finland, Germany, Lithuania, Poland and Sweden). Using nonparametric tests, we found that in the case of m-o-m prices, including fruit, vegetables, and total HICP, the homogeneity of variance during seasons is rejected. Based on these findings, we propose an exponential smoothing model with periodic variance of error terms that capture the repetitive seasonal variation (in conditional or unconditional second moments). In a pseudo-real data experiment, the short-term forecasts (nowcasting) for the considered components of inflation were determined using different specifications of considered models. The forecasting performance of the models was measured using one of the scoring rules for probabilistic forecasts called logarithmic score. We found instead that while the periodic phenomenon in variance was statistically significant, the models with a periodic phenomenon in variance of error terms do not significantly improve forecasting performance in disaggregated cases and in the case of total HICP. The simpler models with constant variance of error term have comparative forecasting (nowcasting) performance over the alternative model
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2017, 1; 29-67
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Exponential smoothing for multi-product lot-sizing with heijunka and varying demand
Autorzy:
Korytkowski, P.
Grimaud, F.
Dolgui, A.
Powiązania:
https://bibliotekanauki.pl/articles/406946.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
job shop
multiproduct
varying demand
lot-sizing
heijunka
exponential smoothing
Opis:
Here we discuss a multi-product lot-sizing problem for a job shop controlled with a heijunka box. Demand is considered as a random variable with constant variation which must be absorbed somehow by the manufacturing system, either by increased inventory or by flexibility in the production. When a heijunka concept (production leveling) is used, fluctuations in customer orders are not transferred directly to the manufacturing system allowing for a smoother production and better production capacity utilization. The problem rather is to determine a tradeoff between the variability in the production line capacity requirement and the inventory level.
Źródło:
Management and Production Engineering Review; 2014, 5, 2; 20-26
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of the predictive properties of Browns model in the extended domain of the internal parameter
Analiz prognoznykh svojjstv modeli Brauna v rasshirennojj oblasti vnutrennego parametra
Autorzy:
Romanenkov, Y.
Powiązania:
https://bibliotekanauki.pl/articles/77408.pdf
Data publikacji:
2015
Wydawca:
Komisja Motoryzacji i Energetyki Rolnictwa
Tematy:
predictive value
Brown's method
adaptive model
exponential smoothing
parametric synthesis
robustness
Źródło:
Motrol. Motoryzacja i Energetyka Rolnictwa; 2015, 17, 8
1730-8658
Pojawia się w:
Motrol. Motoryzacja i Energetyka Rolnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new hybrid approach based on probability distribution and an improved machine learning for multivariate risk assessment
Autorzy:
Azzedine, Abdelhakim
Nouri, Fatma Zohra
Bouhouche, Salah
Powiązania:
https://bibliotekanauki.pl/articles/31341643.pdf
Data publikacji:
2024
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
blast furnace
exponential smoothing
risk
safety
data driven techniques
probability distribution
Opis:
A highly complex dynamic non-linear reactor is the blast furnace iron manufacturing system. It has possible dangers, including carbon monoxide, wide variety of chemical reactions, fire, high pressure and explosion, noise, split and fall, hot metal sparks, hit etc. To ensure a secure working, organizations must take the required measures to manage the risks and their effects. The approach for risk assessment discussed in this research attempts to increase blast furnace safety performance and reduce workers injuries. This approach uses probability distribution and an improved machine learning techniques such as radial basis function artificial neural networks (RBANN). The novelty here is to calculate a multivariate risk using a proposed method, namely exponential smoothing combined with radial basis function artificial neural networks (ES-RBANN). To identify their limits, the results of a research comparing conventional and novel techniques are confirmed using real data collected from the steel production operations ArcelorMittal-Annaba, Algeria.
Źródło:
Diagnostyka; 2024, 25, 1; art. no. 2024113
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of exponential smoothing method to forecasting daily water consumption in rural areas
Zastosowanie metody wygładzania wykładniczego do prognozowania dobowego zużycia wody w obszarach wiejskich
Autorzy:
Cieżak, Wojciech
Kutyłowska, Małgorzata
Powiązania:
https://bibliotekanauki.pl/articles/27312154.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
prognozowanie
sieć przewodów
wygładzanie wykładnicze
zużycie wody
forecasting
exponential smoothing
pipe network
water consumption
Opis:
The size and distribution of water demand within a given structural unit is the basis for the proper operation and planning of the expansion and modernization of the water supply system’s elements. In rural areas, particularly in municipalities adjacent to urban-industrial agglomerations, a change in the use of tap water has been increasingly observed. The water consumption for animal breeding or agricultural use, typical of these areas, has been decreasing and even disappearing. Water has been increasingly used for domestic purposes in single- and multi-family housing as well as for other purposes such as watering lawns and filling residential swimming pools. Taking this into account, this paper presents observations regarding daily water consumption in a municipality adjacent to Wrocław together with an analysis of the possibility of using the exponential smoothing method for the short-term forecasting of daily water consumption. The analyses presented in this paper were carried out using STATISTICA 13 software.
Wzrost zapotrzebowania na wodę w gminach przyległych do dużych aglomeracji, a co za tym idzie wzrost produkcji wody, zmuszają przedsiębiorstwa wodociągowe do szukania nowych rozwiązań dotyczących między innymi optymalnego sterowania takimi procesami jak: ujmowanie i rozdział dyspozycyjnych zasobów wodnych, dystrybucja oraz oczyszczanie wody i ścieków. Aby zapewnić skuteczne sterowanie tymi procesami wymagany jest między innymi skalibrowany model hydrauliczny sieci dystrybucji i model prognostyczny poboru wody. Do bieżącego i krótkoterminowego prognozowania poboru wody wykorzystywane są modele stochastyczne, wprowadzane w postaci zalgorytmizowanej do struktury zarządzania procesem sterowania. Najczęściej stosowane są scałkowane modele autoregresji i średniej ruchomej ARIMA oraz metody wygładzania wykładniczego szeregów czasowych. Modele klasy ARIMA odwzorowują właściwości statyczne i dynamiczne szeregów stacjonarnych i pewnych klas szeregów niestacjonarnych, interpretowanych jako wynik przejścia białego szumu przez dyskretny filtr liniowy skończenie wymiarowy. Charakteryzują się one różnymi właściwościami przy jednolitym zapisie formalnym oraz identycznych metodach estymacji parametrów dla różnych typów i podklas modeli. Metody prognozowania oparte na algorytmach wygładzania wykładniczego są łatwe do praktycznego zastosowania i nie wymagają założenia o stacjonarności analizowanego szeregu czasowego. W niniejszej pracy przedstawiono obserwacje dotyczące dobowego zużycia wody w jednej z gmin przyległej do Wrocławia wraz z analizą możliwości zastosowania metody wygładzania wykładniczego do krótkoterminowego prognozowania dobowego poboru wody.
Źródło:
Archives of Civil Engineering; 2023, 69, 3; 445--456
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-10 z 25

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