A modular hybrid simulation framework for complex manufacturing system design [PDF]
, 2019 For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal ...
Erkoyuncu, J. A. +3 more
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Arrival times by Recurrent Neural Network for induced seismic events from a permanent network
Frontiers in Big Data, 2023 We have developed a Recurrent Neural Network (RNN)-based phase picker for data obtained from a local seismic monitoring array specifically designated for induced seismicity analysis. The proposed algorithm was rigorously tested using real-world data from
Petr Kolar +3 more
doaj +1 more source
Applied Sciences, 2023 The necessity for undertaking this research is driven by the prevailing challenges encountered in logistic centers. This study addresses a logistic order-picking issue involving unidirectional conveyors and buffers, which are assigned to racks and ...
Kateryna Czerniachowska +2 more
doaj +1 more source
A Microseismic Phase Picking and Polarity Determination Model Based on the Earthquake Transformer
Applied SciencesPhase arrival times and polarities provide essential kinematic constraints for and dynamic insights into seismic sources, respectively. This information serves as fundamental data in seismological study.
Ling Peng, Lei Li, Xiaobao Zeng
doaj +1 more source
PSSegNet: Segmenting the P- and S-Phases in Microseismic Signals through Deep Learning
Mathematics, 2023 Microseismic P- and S-phase segmentation is an influential step that limits the accuracy of event location, parameter inversion, and mechanism analysis.
Zhengxiang He +5 more
doaj +1 more source
Pioneers of Influence Propagation in Social Networks [PDF]
, 2013 With the growing importance of corporate viral marketing campaigns on online social networks, the interest in studies of influence propagation through networks is higher than ever.
Blaszczyszyn, Bartlomiej +2 more
core +4 more sources
First Arrival Picking of Seismic Data Based on Trace Envelope
IEEE Access, 2019 We introduce a new method for first arrival traveltime picking based on the maximum difference between adjacent points of the envelope (MDPE) of a seismic trace.
Abdullah A. Al-Mashhor +3 more
doaj +1 more source
Consistent phase picking for regional tomography models: application to the greater Alpine region [PDF]
, 2017 The resolution and reliability of tomographic velocity models strongly depends on quality and consistency of available traveltime data. Arrival times routinely picked by network analysts on a day-to-day basis often yield a high level of noise due to ...
Aldersons, F. +3 more
core
Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning
Nature Communications, 2023 Distributed Acoustic Sensing (DAS) is an emerging technology for earthquake monitoring and subsurface imaging. However, its distinct characteristics, such as unknown ground coupling and high noise level, pose challenges to signal processing.
Weiqiang Zhu +5 more
doaj +1 more source
LEQNet: Light Earthquake Deep Neural Network for Earthquake Detection and Phase Picking
Frontiers in Earth Science, 2022 Developing seismic signal detection and phase picking is an essential step for an on-site early earthquake warning system. A few deep learning approaches have been developed to improve the accuracy of seismic signal detection and phase picking.
Jongseong Lim +8 more
doaj +1 more source