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José Francisco Lima, Fernanda Catarina Pereira, Arminda Manuela Gonçalves and Marco Costa
Linear models, seasonal autoregressive integrated moving average (SARIMA) models, and state-space models have been widely adopted to model and forecast economic data. While modeling using linear models and SARIMA models is well established in the literat...
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Federico Ricci, Luca Petrucci, Francesco Mariani and Carlo Nazareno Grimaldi
To carry out increasingly sophisticated checks, which comply with international regulations and stringent constraints, on-board computational systems are called upon to manipulate a growing number of variables, provided by an ever-increasing number of re...
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Yuan-Jen Chang, He-Kai Hsu, Tzu-Hsuan Hsu, Tsung-Ti Chen and Po-Wen Hwang
With the development of next-generation airplanes, the complexity of equipment has increased rapidly, and traditional maintenance solutions have become cost-intensive and time-consuming. Therefore, the main objective of this study is to adopt predictive ...
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Kadria Ezzine, Joseph Di Martino and Mondher Frikha
We present an any-to-one voice conversion (VC) system, using an autoregressive model and LPCNet vocoder, aimed at enhancing the converted speech in terms of naturalness, intelligibility, and speaker similarity. As the name implies, non-parallel any-to-on...
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Abas Omar Mohamed
The study investigated the empirical role of past values of Somalia?s GDP growth rates in its future realizations. Using the Box?Jenkins modeling method, the study utilized 250 in-sample quarterly time series data to forecast out-of-the-sample Somali GDP...
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Enna Hirata and Takuma Matsuda
With the increasing availability of large datasets and improvements in prediction algorithms, machine-learning-based techniques, particularly deep learning algorithms, are becoming increasingly popular. However, deep-learning algorithms have not been wid...
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Ulrich Gunter
The present study employs daily data made available by the STR SHARE Center covering the period from 1 January 2010 to 31 January 2020 for six Viennese hotel classes and their total. The forecast variable of interest is hotel room demand. As forecast mod...
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Monica Defend, Aleksey Min, Lorenzo Portelli, Franz Ramsauer, Francesco Sandrini and Rudi Zagst
This article considers the estimation of Approximate Dynamic Factor Models with homoscedastic, cross-sectionally correlated errors for incomplete panel data. In contrast to existing estimation approaches, the presented estimation method comprises two exp...
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Maria Grazia De Giorgi, Luciano Strafella and Antonio Ficarella
One of the most important parts of a turboshaft engine, which has a direct impact on the performance of the engine and, as a result, on the performance of the propulsion system, is the engine fuel control system. The traditional engine control system is ...
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Magda Monteiro and Marco Costa
The monitoring and prediction of water quality parameters are important tasks in the management of water resources. In this work, the performances of time series statistical models were evaluated to predict and forecast the dissolved oxygen (DO) concentr...
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