Results 11 to 20 of about 33,755,974 (386)
Journal of The Royal Society Interface, 2017 Complex systems theory is concerned with identifying and characterizing common design elements that are observed across diverse natural, technological and social complex systems. Systems biology, a more holistic approach to study molecules and cells in biology, has advanced rapidly in the past two decades.
Avi Ma’ayan
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The physics of higher-order interactions in complex systems [PDF]
Nature Physics, 2021 Complex networks have become the main paradigm for modelling the dynamics of interacting systems. However, networks are intrinsically limited to describing pairwise interactions, whereas real-world systems are often characterized by higher-order ...
F. Battiston +13 more
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A complex systems approach to aging biology
Nature Aging, 2022 Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging.
A. Cohen +11 more
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The why, how, and when of representations for complex systems [PDF]
SIAM Review, 2020 Complex systems thinking is applied to a wide variety of domains, from neuroscience to computer science and economics. The wide variety of implementations has resulted in two key challenges: the progenation of many domain-specific strategies that are ...
Leo Torres +3 more
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EPJ Data Science, 2021 Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter.
Thayer Alshaabi +6 more
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Evasion of tipping in complex systems through spatial pattern formation
Science, 2021 Description Resilience to tipping points in ecosystems Spatial pattern formation has been proposed as an early warning signal for dangerous tipping points and imminent critical transitions in complex systems, including ecosystems. Rietkerk et al.
M. Rietkerk +5 more
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Attention Mechanisms and Their Applications to Complex Systems
Entropy, 2021 Deep learning models and graphics processing units have completely transformed the field of machine learning. Recurrent neural networks and long short-term memories have been successfully used to model and predict complex systems.
Adrián Hernández, J. Amigó
semanticscholar +1 more source
Complexity, 2022 The U.S. stock market is one of the largest and most complex marketplaces in the global financial system. Over the past several decades, this market has evolved at multiple structural and temporal scales.
Colin M. Van Oort +4 more
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Kernel-based online learning for real-time voltage control in distribution networks
IET Smart Grid, 2020 This paper presents a new data-driven voltage control approach for distribution networks based on kernel methods. Voltage control becomes more and more challenging due to the increased penetration of Distributed Generation (DG), bidirectional power flow ...
Lisette Cupelli +4 more
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Modeling Complex Systems: A Case Study of Compartmental Models in Epidemiology
Complexity, 2022 Compartmental epidemic models have been widely used for predicting the course of epidemics, from estimating the basic reproduction number to guiding intervention policies.
Alexander F. Siegenfeld +2 more
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