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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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Yifan Fang, Shanshan Jiang, Shengxuan Fang, Zhenxi Gong, Min Xia and Xiaodong Zhang
Load decomposition technology is an important aspect of power intelligence. At present, there are mainly machine learning methods based on artificial features and deep learning methods for load decomposition. The method based on artificial features has a...
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Shuai Lu, Haibo Chen and Yilong Teng
Traffic flow prediction is a crucial research area in traffic management. Accurately predicting traffic flow in each area of the city over the long term can enable city managers to make informed decisions regarding the allocation of urban transportation ...
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Mohammad Naser Lessani, Jiqiu Deng and Zhiyong Guo
Multiple geographical feature label placement (MGFLP) is an NP-hard problem that can negatively influence label position accuracy and the computational time of the algorithm. The complexity of such a problem is compounded as the number of features for la...
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Xiaoxiao Meng, Qianggang Wang, Niancheng Zhou, Shuyan Xiao and Yuan Chi
AC microgrid mainly comprise inverter-interfaced distributed generators (IIDGs), which are nonlinear complex systems with multiple time scales, including frequency control, time delay measurements, and electromagnetic transients. The droop control-based ...
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Zhenxin Li, Yong Han, Zhenyu Xu, Zhihao Zhang, Zhixian Sun and Ge Chen
Traffic forecasting has always been an important part of intelligent transportation systems. At present, spatiotemporal graph neural networks are widely used to capture spatiotemporal dependencies. However, most spatiotemporal graph neural networks use a...
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Vijayakumar Varadarajan, Dweepna Garg and Ketan Kotecha
Deep learning is a relatively new branch of machine learning in which computers are taught to recognize patterns in massive volumes of data. It primarily describes learning at various levels of representation, which aids in understanding data that includ...
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Sakshi Pandey and Amit Banerjee
Counting the number of speakers in an audio sample can lead to innovative applications, such as a real-time ranking system. Researchers have studied advanced machine learning approaches for solving the speaker count problem. However, these solutions are ...
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Juan Carlos Rodríguez-Murillo and Montserrat Filella
Wavelet transform, wavelet spectra, and coherence are popular tools for studying fluctuations in time series in the form of a bidimensional time and scale representation. We discuss two aspects of wavelet analysis?namely the significance and stochastic/d...
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Saad A. Alowayyed,Maxime Vassaux,Ben Czaja,Peter V. Coveney,Alfons G. Hoekstra
Pág. 20 - 43
New applications that can exploit emerging exascale computing resources efficiently, while providing meaningful scientific results, are eagerly anticipated. Multi-scale models, especially multi-scale applications, will assuredly run at the exascale. We h...
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Lilun Zhang, Dezhi Wang, Changchun Bao, Yongxian Wang and Kele Xu
Whale vocal calls contain valuable information and abundant characteristics that are important for classification of whale sub-populations and related biological research. In this study, an effective data-driven approach based on pre-trained Convolutiona...
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Georges Da Costa,Thomas Fahringer,Juan Antonio Rico Gallego,Ivan Grasso,Atanas Hristov,Helen D. Karatza,Alexey Lastovetsky,Fabrizio Marozzo,Dana Petcu,Georgios L. Stavrinides,Domenico Talia,Paolo Trunfio,Hrachya Astsatryan
Pág. 6 - 27
Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equiped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such Exascale systems will provide hardware ...
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Peizhen Zhang, Xiaofeng Yin, Bin Wang and Ziyi Feng
The construction of wind farm pilings, submarine pipelines, and underwater submarines involves multiple cylinders. However, there is currently a lack of economic research on predicting the mechanism and characteristics of mutual coupling of acoustic scat...
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Edmund Robbins, Thu Thu Hlaing, Jonathan Webb and Nezamoddin N. Kachouie
Glaciers are important indictors of climate change as changes in glaciers physical features such as their area is in response to measurable evidence of fluctuating climate factors such as temperature, precipitation, and CO2. Although a general retreat of...
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Christos Kastrisios, Noel Dyer, Tamer Nada, Stilianos Contarinis and Jose Cordero
Electronic Navigational Chart (ENC) data are essential for safe maritime navigation and have multiple other uses in a wide range of enterprises. Charts are relied upon to be as accurate and as up-to-date as possible by the vessels moving vast amounts of ...
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Yi Wang and Changfeng Jing
Benefiting from the rapid development of geospatial big data-related technologies, intelligent transportation systems (ITS) have become a part of people?s daily life. Traffic volume forecasting is one of the indispensable tasks in ITS. The spatiotemporal...
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Pi-Yun Chen, Xuan-Hao Zhang, Jian-Xing Wu, Ching-Chou Pai, Jin-Chyr Hsu, Chia-Hung Lin and Neng-Sheng Pai
Mammography is a first-line imaging examination approach used for early breast tumor screening. Computational techniques based on deep-learning methods, such as convolutional neural network (CNN), are routinely used as classifiers for rapid automatic bre...
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Hafiz Suliman Munawar, Fahim Ullah, Amirhossein Heravi, Muhammad Jamaluddin Thaheem and Ahsen Maqsoom
Manual inspection of infrastructure damages such as building cracks is difficult due to the objectivity and reliability of assessment and high demands of time and costs. This can be automated using unmanned aerial vehicles (UAVs) for aerial imagery of da...
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Ruijia Cao and Jianping Yuan
The cavitation states among centrifugal pumps can be mirrored by corresponding vibration features. To select the vibration feature target scientifically and objectively for monitor the cavitation states in real time, the analysis method of grey slope cor...
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Luis E. Rodríguez-Pupo, Carlos Granell and Sven Casteleyn
In large-scale context-aware applications, a central design concern is capturing, managing and acting upon location and context data. The ability to understand the collected data and define meaningful contextual events, based on one or more incoming (con...
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