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Zichao He, Chunna Zhao and Yaqun Huang
Multivariate time series forecasting has long been a subject of great concern. For example, there are many valuable applications in forecasting electricity consumption, solar power generation, traffic congestion, finance, and so on. Accurately forecastin...
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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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Nika Nizharadze, Arash Farokhi Soofi and Saeed Manshadi
Predicting the price gap between the day-ahead Market (DAM) and the real-time Market (RTM) plays a vital role in the convergence bidding mechanism of Independent System Operators (ISOs) in wholesale electricity markets. This paper presents a model to pre...
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Rafaela C. Cruz, Pedro Reis Costa, Susana Vinga, Ludwig Krippahl and Marta B. Lopes
Harmful algal blooms (HABs) are among the most severe ecological marine problems worldwide. Under favorable climate and oceanographic conditions, toxin-producing microalgae species may proliferate, reach increasingly high cell concentrations in seawater,...
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Fatma Yaprakdal and Merve Varol Arisoy
In the smart grid paradigm, precise electrical load forecasting (ELF) offers significant advantages for enhancing grid reliability and informing energy planning decisions. Specifically, mid-term ELF is a key priority for power system planning and operati...
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Patrizio Vanella, Christina Benita Wilke and Doris Söhnlein
Demographic change is leading to the aging of German society. As long as the baby boom cohorts are still of working age, the working population will also age?and decline as soon as this baby boom generation gradually reaches retirement age. At the same t...
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Soumyashree Kar, Jason R. McKenna, Glenn Anglada, Vishwamithra Sunkara, Robert Coniglione, Steve Stanic and Landry Bernard
While study of ocean dynamics usually involves modeling deep ocean variables, monitoring and accurate forecasting of nearshore environments is also critical. However, sensor observations often contain artifacts like long stretches of missing data and noi...
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Mayra Salcedo-Gonzalez, Julio Suarez-Paez, Manuel Esteve and Carlos Enrique Palau
This article presents the development of a geo-visualization tool, which provides police officers or any other type of law enforcement officer with the ability to conduct the spatiotemporal predictive geo-visualization of criminal activities in short and...
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Charalampos M. Liapis and Sotiris Kotsiantis
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Given th...
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Eric Hitimana, Gaurav Bajpai, Richard Musabe, Louis Sibomana and Jayavel Kayalvizhi
Many countries worldwide face challenges in controlling building incidence prevention measures for fire disasters. The most critical issues are the localization, identification, detection of the room occupant. Internet of Things (IoT) along with machine ...
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An accurate cost estimate not only plays a key role in project feasibility studies but also in achieving a final successful outcome. Conventionally, estimating cost typically relies on the experience of professionals and cost data from previous projects....
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Afees A. Salisu, Kazeem O. Isah, Alberto Assandri
Pág. 255 - 283
This study examines probable dynamic spillover transmissions between the Nigerian stock and money markets using the multivariate volatility framework that simultaneously accounts for both returns and shock spillovers. Based on relevant pre-tests, the VAR...
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Konstantinos I. Papageorgiou, Katarzyna Poczeta, Elpiniki Papageorgiou, Vassilis C. Gerogiannis and George Stamoulis
This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim of time series forecasting is to ...
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Martina Zelenáková, Vinayakam Jothiprakash, Sasi Arjun, Daniela Káposztásová and Helena Hlavatá
Evaporation and precipitation are often considered the most important processes in the water cycle. Recent studies have turned to chaotic analysis and short-term prediction for analyzing and forecasting the time series of such phenomena. However, even wi...
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Kelly Grassi, Émilie Poisson-Caillault, André Bigand and Alain Lefebvre
In the framework of ecological or environmental assessments and management, detection, characterization and forecasting of the dynamics of environmental states are of paramount importance. These states should reflect general patterns of change, recurrent...
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Aymane Ahajjam, Jaakko Putkonen, Emmanuel Chukwuemeka, Robert Chance and Timothy J. Pasch
Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weathe...
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Mana Gharun, Mohammad Azmi and Mark A. Adams
Forested catchments in southeast Australia play an important role in supplying water to major cities. Over the past decades, vegetation cover in this area has been affected by major bushfires that in return influence water yield. This study tests methods...
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Nikolaos Stasinos, Anestis Kousis, Vangelis Sarlis, Aristeidis Mystakidis, Dimitris Rousidis, Paraskevas Koukaras, Ioannis Kotsiopoulos and Christos Tjortjis
The impact of COVID-19 and the pressure it exerts on health systems worldwide motivated this study, which focuses on the case of Greece. We aim to assist decision makers as well as health professionals, by estimating the short to medium term needs in Int...
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Sichen Li, Mélissa Zacharias, Jochem Snuverink, Jaime Coello de Portugal, Fernando Perez-Cruz, Davide Reggiani and Andreas Adelmann
The beam interruptions (interlocks) of particle accelerators, despite being necessary safety measures, lead to abrupt operational changes and a substantial loss of beam time. A novel time series classification approach is applied to decrease beam time lo...
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Mohammad Barooni and Deniz Velioglu Sogut
The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an...
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