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Konstantinos P. Fourkiotis and Athanasios Tsadiras
In today?s evolving global world, the pharmaceutical sector faces an emerging challenge, which is the rapid surge of the global population and the consequent growth in drug production demands. Recognizing this, our study explores the urgent need to stren...
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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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Supraja Malladi and Qiqi Lu
The COVID-19 pandemic has had a catastrophic effect on the healthcare system including organ transplants worldwide. The number of living donor transplants performed in the US was affected more significantly by the pandemic with a 22.6% decrease in counts...
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Juncheng Mi and Guoqin Huang
Direct-drive electro-hydraulic servo valves are widely used in the aerospace industry, in the military, and in remote sensing control, but there is little research and discussion on their performance degradation and service life prediction. Based on prev...
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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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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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Miaomiao Yu, Hongyong Yuan, Kaiyuan Li and Lizheng Deng
To separate the noise and important signal features of the indoor carbon dioxide (CO2) concentration signal, we proposed a noise cancellation method, based on time-varying, filtering-based empirical mode decomposition (TVF-EMD) with Bayesian optimization...
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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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Pieter Cawood and Terence Van Zyl
The techniques of hybridisation and ensemble learning are popular model fusion techniques for improving the predictive power of forecasting methods. With limited research that instigates combining these two promising approaches, this paper focuses on the...
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Thabang Mathonsi and Terence L. van Zyl
Hybrid methods have been shown to outperform pure statistical and pure deep learning methods at forecasting tasks and quantifying the associated uncertainty with those forecasts (prediction intervals). One example is Exponential Smoothing Recurrent Neura...
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