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Juliana Castaneda, Mattia Neroni, Majsa Ammouriova, Javier Panadero and Angel A. Juan
Many real-life combinatorial optimization problems are subject to a high degree of dynamism, while, simultaneously, a certain level of synchronization among agents and events is required. Thus, for instance, in ride-sharing operations, the arrival of veh...
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T. M. Mishchenko
Pág. 67 - 76
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Yaping Hao and Qiang Gao
In the stock market, predicting the trend of price series is one of the most widely investigated and challenging problems for investors and researchers. There are multiple time scale features in financial time series due to different durations of impact ...
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Yuanfeng Lian, Yueyao Geng and Tian Tian
Due to the complexity of the oil and gas station system, the operational data, with various temporal dependencies and inter-metric dependencies, has the characteristics of diverse patterns, variable working conditions and imbalance, which brings great ch...
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Christoph Laroque, Madlene Leißau, Pedro Copado, Christin Schumacher, Javier Panadero and Angel A. Juan
Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneo...
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Vladimir Zyryanov, Victor Kocherga, Ivan Topilin
Pág. 746 - 750
The paper reports the results of studies of changes in parameters of two-component model of the kinetic theory of transport flows. The paper states a ratio between cars stopping at the same time in the network, specific travel time and specific standing ...
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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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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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Jianfeng Wang, Gaowei Jia, Zheng Guo and Zhongxi Hou
Heterogeneous multi-UAV systems offer distinct advantages through their complementary and coordinated use of their diverse capabilities. However, this complexity poses significant challenges in task planning, particularly in considering temporal constrai...
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Aida Boudhaouia and Patrice Wira
This article presents a real-time data analysis platform to forecast water consumption with Machine-Learning (ML) techniques. The strategy fully relies on a web-oriented architecture to ensure better management and optimized monitoring of water consumpti...
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Andreas Rauh and Julia Kersten
Continuous-time linear systems with uncertain parameters are widely used for modeling real-life processes. The uncertain parameters, contained in the system and input matrices, can be constant or time-varying. In the latter case, they may represent state...
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Jenny Leonard
The strategic, transformational nature of many information systems projects is now widely understood. Large-scale implementations of systems are known to require significant management of organisational change in order to be successful. Moreover, project...
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Jose Luis Guerrero Cusumano
Pág. 45 - 60
Text analysis is a useful tool to determine what a company and its customers want in order to improve processes and methodologies of analysis. Searches in databases may have a time series component that determines the importance and sequences of multivar...
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Guoying Wang, Jiafeng Ai, Lufeng Mo, Xiaomei Yi, Peng Wu, Xiaoping Wu and Linjun Kong
Anomaly detection has an important impact on the development of unmanned aerial vehicles, and effective anomaly detection is fundamental to their utilization. Traditional anomaly detection discriminates anomalies for single-dimensional factors of sensing...
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Xuebin Xu, Chen Chen, Kan Meng, Longbin Lu, Xiaorui Cheng and Haichao Fan
Sleep, as the basis for regular body functioning, can affect human health. Poor sleep conditions can lead to various physical ailments, such as poor immunity, memory loss, slow cognitive development, and cardiovascular diseases. Along the increasing stre...
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Jacques Hermes, Marcus Rosenblatt, Christian Tönsing and Jens Timmer
Describing viral outbreaks, such as the COVID-19 pandemic, often involves employing compartmental models composed of ordinary differential equation (ODE) systems. Estimating the parameter values for these ODE models is crucial and relies on accessible da...
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Victoria Kamenchuk, Boris Rumiantsev, Sofya Dzhatdoeva, Elchin Sadykhov and Azret Kochkarov
Urban vertical farming is an innovative solution to address the increasing demand for food in densely populated cities. With advanced technology and precise monitoring, closed urban vertical farms can optimize growing conditions for plants, resulting in ...
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Tingting Wang, Zhuolin Li, Xiulin Geng, Baogang Jin and Lingyu Xu
The accurate prediction of sea surface temperature (SST) is the basis for our understanding of local and global climate characteristics. At present, the existing sea temperature prediction methods fail to take full advantage of the potential spatial depe...
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Anna Bakurova, Olesia Yuskiv, Dima Shyrokorad, Anton Riabenko, Elina Tereschenko
Pág. 14 - 22
The subject of the research is the methods of constructing and training neural networks as a nonlinear modeling apparatus for solving the problem of predicting the energy consumption of metallurgical enterprises. The purpose of this work is to develop a ...
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Jiandong Bai, Jiawei Zhu, Yujiao Song, Ling Zhao, Zhixiang Hou, Ronghua Du and Haifeng Li
Accurate real-time traffic forecasting is a core technological problem against the implementation of the intelligent transportation system. However, it remains challenging considering the complex spatial and temporal dependencies among traffic flows. In ...
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