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Christy Pérez-Albornoz, Ángel Hernández-Gómez, Victor Ramirez and Damien Guilbert
Installation of new wind farms in areas such as the north coast of the Yucatan peninsula is of vital importance to face the local energy demand. For the proper functioning of these facilities it is important to perform wind data analysis, the data having...
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Evangelos Spiliotis, Fotios Petropoulos and Vassilios Assimakopoulos
Forecasters have been using various criteria to select the most appropriate model from a pool of candidate models. This includes measurements on the in-sample accuracy of the models, information criteria, and cross-validation, among others. Although the ...
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Kadir Dönmez, Emre Aydogan, Cem Çetek and Erdem Emin Maras
This study aims to determine the impact of the International Civil Aviation Organization?s (ICAO) taxiway system development stages on runway capacity and delays in a single-runway airport that serves mixed operations by using a combined approach integra...
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Liuqi An, Lan Chen and Xiaoran Hao
With the increasing complexity of building structures and interior materials, the danger of indoor fires has become more severe. It is effective to improve the accuracy and timeliness of fire-sensing devices in order to reduce the harm caused by fires. T...
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Bramasto Wiryawan Yudanto, Budi Hartanto
Pág. 188 - 199
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Hatice Erkekoglu,Aweng Peter Majok Garang,Adire Simon Deng
Pág. 206 - 216
While various linear and nonlinear forecasting models exist, multivariate methods like VAR, Exponential smoothing, and Box-Jenkins? ARIMA methodology constitute the widely used methods in time series. This paper employs series of Turkish private co...
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Óscar Trull, J. Carlos García-Díaz and Alicia Troncoso
Electricity management and production depend heavily on demand forecasts made. Any mismatch between the energy demanded with respect to that produced supposes enormous losses for the consumer. Transmission System Operators use time series-based tools to ...
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Nazzareno Diodato, Lelys Bravo De Guenni, Mariangel Garcia and Gianni Bellocchi
Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longe...
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William Obeng-Amponsah,Sun Zehou,Elias Augustine Dey
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Nazzareno Diodato and Gianni Bellocchi
The coasts of the Italian peninsula have been recently affected by frequent damaging hydrological events driven by intense rainfall and deluges. The internal climatic mechanisms driving rainfall variability that generate these hydrological events in the ...
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Indah Suryani,Romi Satria Wahono
Pág. 67 - 75
Emas menjadi salah satu logam mulia yang paling banyak diminati baik untuk investasi maupun untuk dijadikan perhiasan. Memprediksi harga emas telah menjadi signifikan dan sangat penting bagi investor karena emas merupakan alat yang penting untuk perlindu...
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Handanhal V. Ravinder
This paper examines exponential smoothing constants that minimize summary error measures associated with a large number of forecasts. These forecasts were made on numerous time series generated through simulation on a spreadsheet. The series varied in le...
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O. N. Gnennyi
Pág. 316 - 321
The problems of short-, medium- and long-term forecasting price dynamics are considered. The improvement of short-term forecasting techniques based on exponential smoothing is proposed. A modified autoregressive model of the first-order differences for t...
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Preslav Mihaylov Dimitrov
Pág. 208 - 221
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Eren Bas, Erol Egrioglu and Ufuk Yolcu
Exponential smoothing methods are one of the classical time series forecasting methods. It is well known that exponential smoothing methods are powerful forecasting methods. In these methods, exponential smoothing parameters are fixed on time, and they s...
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Samar A. Shilbayeh, Abdullah Abonamah and Ahmad A. Masri
Prediction models of coronavirus disease utilizing machine learning algorithms range from forecasting future suspect cases, predicting mortality rates, to building a pattern for country-specific pandemic end date. To predict the future suspect infection ...
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Vadim Kramar and Vasiliy Alchakov
The models for forecasting time series with seasonal variability can be used to build automatic real-time control systems. For example, predicting the water flowing in a wastewater treatment plant can be used to calculate the optimal electricity consumpt...
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Yuruixian Zhang, Wei Chong Choo, Jen Sim Ho and Cheong Kin Wan
Tourism forecasting has garnered considerable interest. However, integrating tourism forecasting with volatility is significantly less typical. This study investigates the performance of both the single models and their combinations for forecasting the v...
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Lu Han, Chongchong Yu, Cuiling Liu, Yong Qin and Shijie Cui
The proposed model of this paper is for the fault diagnosis of rolling bearings in rail train.
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Eduar Jamis Mejía Vásquez,Salome Gonzales Chávez
Pág. 181 - 191
El objetivo de este trabajo es predecir el consumo de energía eléctrica residencial de la Región Cajamarca mediante modelos Holt-Winters. Este procedimiento de modelización predictiva es útil para la predicción a corto y mediano plazo de ventas de energí...
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