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Wyszukujesz frazę "Box-Jenkins" wg kryterium: Temat


Wyświetlanie 1-5 z 5
Tytuł:
The energy consumption forecasting in Mongolia based on Box-Jenkins method (Arima model)
Autorzy:
Zolboo, Gansukh
Adiya, Bor
Bilguun, Enkhbayar
Powiązania:
https://bibliotekanauki.pl/articles/101770.pdf
Data publikacji:
2019
Wydawca:
Instytut Polityki Energetycznej im. Ignacego Łukasiewicza
Tematy:
energy forecasting
energy consumption
ARIMA model
Box-Jenkins method
Opis:
The primary products of the power industry are electric energy and thermal energy. Thus, forecasting electric energy consumption is significant for short and long term energy planning. ARIMA model has adopted to forecast energy consumption because of its precise prediction for energy consumption. Our result has shown that annual average electric energy consumption will be 10,628 million kWh per year during 2019-2030 which approximately 3.3 percent growth per annum. At the moment, there is not a practice solution for the storage of electricity in Mongolia. Therefore, energy supply and demand have to be balanced in real-time for operational stability. Without an accurate forecast, the end-users may experience brownouts or even blackouts or the industry could be faced with sudden accidents due to the energy demand. For this reason, energy consumption forecasting is essential to power system stability and reliability.
Źródło:
Energy Policy Studies; 2019, 1 (3); 70-77
2545-0859
Pojawia się w:
Energy Policy Studies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Predicting the overall equipment efficiency of core drill rigs in mining using ANN and improving it using MCDM
Autorzy:
Balakrishnan, Kirubakaran
Mani, Ilangkumaran
Durairaj, Sankaran
Powiązania:
https://bibliotekanauki.pl/articles/27312784.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
artificial neural network
response surface methodology
core drill
overall equipment efficiency
Box-Jenkins
Opis:
In this manuscript, an attempt has been made to predict and improve the overall equipment effectiveness of core drill rigs. A combined Box– Jenkins and artificial neural network model was used to develop a three parameter model (drill pushing pressure, drill penetration rate & average pillar drill pit cycle time) for predicting effectiveness. the overall equipment efficiency of core drill rigs. The values of mean average percentage error, root mean square error, normalized root mean square error, men bias error, normalized mean biased error and coefficient of determination values were found to be 9.462%, 17.378%, 0.194, 0.96%, 0.0014 and 0.923. Empirical relationships were developed between the input and output parameters and its effectiveness were evaluated using analysis of variance. For attaining 74.9% effectiveness, the optimized values of pushing pressure, penetration rate and average pillar drill pit cycle time were predicted to be 101.7 bar, 0.94 m/min and 272 min, which was validated. Interactions, perturbations and sensitivity analysis were conducted.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 3; art. no. 169581
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance Comparison of Four New ARIMA-ANN Prediction Models on Internet Traffic Data
Autorzy:
Babu, C. N.
Reddy, B. E.
Powiązania:
https://bibliotekanauki.pl/articles/308269.pdf
Data publikacji:
2015
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
ANN
ANN training
ARIMA
Box-Jenkins methodology
hybrid ARIMA-ANN model
Internet traffic forecasting
Opis:
Prediction of Internet traffic time series data (TSD) is a challenging research problem, owing to the complicated nature of TSD. In literature, many hybrids of auto-regressive integrated moving average (ARIMA) and artificial neural networks (ANN) models are devised for the TSD prediction. These hybrid models consider such TSD as a combination of linear and non-linear components, apply combination of ARIMA and ANN in some manner, to obtain the predictions. Out of the many available hybrid ARIMA-ANN models, this paper investigates as to which of them suits better for Internet traffic data. This suitability of hybrid ARIMA-ANN models is studied for both one-step ahead and multistep ahead prediction cases. For the purpose of the study, Internet traffic data is sampled at every 30 and 60 minutes. Model performances are evaluated using the mean absolute error and mean square error measurement. For one-step ahead prediction, with a forecast horizon of 10 points and for three-step prediction, with a forecast horizon of 12 points, the moving average filter based hybrid ARIMA-ANN model gave better forecast accuracy than the other compared models.
Źródło:
Journal of Telecommunications and Information Technology; 2015, 1; 67-75
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Water quality management in a treatment plant using the Box-Jenkins method
Autorzy:
Redondo-Peñuela, E. A.
Rondón-Quintana, H. A.
Zafra-Mejía, C. A.
Powiązania:
https://bibliotekanauki.pl/articles/230328.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
model Box-Jenkinsa
oczyszczalnia
szereg czasowy
jakość wody
Box-Jenkins model
treatment plant
time series
water quality
Opis:
Drinking water systems are critical to society. They protect residents from waterborne illnesses and encourage economic success of businesses by providing consistent water supplies to industries and supporting a healthy work force. This paper shows a study on water quality management in a treatment plant (TP) using the Box-Jenkins method. A comparative analysis was carried out between concentrations of water quality parameters, and Colombian legislation and guidelines established by the World Health Organization. We also studied the rainfall influence in relation to variations in water quality supplied by the TP. A correlation analysis between water quality parameters was carried out to identify management parameters during the TP operation. Results showed the usefulness of the Box-Jenkins method for analyzing the TP operation from a weekly timescale (mediumterm), and not from a daily timescale (short-term). This was probably due to significant daily variations in the management parameters of water quality in the TP. The application of a weekly moving average transformation to the daily time series of water quality parameter concentrations significantly decreased the mean absolute percentage error in the forecasts of Box-Jenkins models developed. Box-Jenkins analysis suggested an influence of the water quality parameter concentrations observed in the TP during previous weeks (between 2-3 weeks). This study was probably constituted as a medium-term planning tool in relation to atypical events or contingencies observed during the TP operation. Finally, the findings in this study will be useful for companies or designers of drinking water treatment systems to take operational decisions within the public health framework.
Źródło:
Archives of Civil Engineering; 2020, 66, 3; 125-137
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Best Time Series In-sample Model for Forecasting Nigeria Exchange Rate
Autorzy:
Gaddafi, Adamu Babali
Akpensuen, Shiaondo Henry
Shitu, Abdulrazaq Ahmed
Malle, Ahmad Atiku
Adamu, Muhammed
Bukar, Muhammad Goni
Powiązania:
https://bibliotekanauki.pl/articles/1031300.pdf
Data publikacji:
2021
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
ARIMA
Autoregressive Integrated Moving Average Model
Autoregressive Moving Average Model
Autoregressive models
Box-Jenkins Methodology
CBN
Exchange rate
Model
Moving Average Models
Nigeria
Opis:
In this work we considered data on official Nigeria exchange rates (Naira to British Pound sterling) from January 2003 to December 2019. Four competing models ARIMA (1, 1, 1), ARIMA (2, 1, 1), ARIMA (1, 1, 0) and ARIMA (1, 1, 2) were identified for the exchange rates series. Diagnostic analysis revealed that all the competing models adequately represent the exchange rate series. However, on the basis of out-of-sample model selection and evaluation ARIMA (1, 1, 1) was selected as the optimal model with minimum information criteria for the exchange rate series. A 24 months forecast indicates that the Naira will continue to depreciate. The policy implication of our study is that the Central Bank of Nigeria (CBN), should devalue the Naira in order to not only re-establish exchange rate stability but also encourage local manufacturing and encourage foreign capital inflows.
Źródło:
World Scientific News; 2021, 151; 45-63
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
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