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Prediction model for suicide based on back propagation neural network and multilayer perceptron
Frontiers in Neuroinformatics, 2022 IntroductionThe aim was to explore the neural network prediction model for suicide based on back propagation (BP) and multilayer perceptron, in order to establish the popular, non-invasive, brief and more precise prediction model of suicide.Materials and
Juncheng Lyu +4 more
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Multilayer Networks in a Nutshell [PDF]
Annual Review of Condensed Matter Physics, 2019 Complex systems are characterized by many interacting units that give rise to emergent behavior. A particularly advantageous way to study these systems is through the analysis of the networks that encode the interactions among the system constituents.
Alberto Aleta, Yamir Moreno
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Frontiers in Research Metrics and Analytics, 2023 Classifying scientific publications according to Field-of-Science taxonomies is of crucial importance, powering a wealth of relevant applications including Search Engines, Tools for Scientific Literature, Recommendation Systems, and Science Monitoring ...
Sotiris Kotitsas +4 more
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Isomorphisms in Multilayer Networks [PDF]
IEEE Transactions on Network Science and Engineering, 2018 We extend the concept of graph isomorphisms to multilayer networks with any number of "aspects" (i.e., types of layering). In developing this generalization, we identify multiple types of isomorphisms. For example, in multilayer networks with a single aspect, permuting vertex labels, layer labels, and both vertex labels and layer labels each yield ...
Porter, Mason, A., Kivela, Mikko
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An Eigenmodel for Dynamic Multilayer Networks
J. Mach. Learn. Res., 2021 Dynamic multilayer networks frequently represent the structure of multiple co-evolving relations; however, statistical models are not well-developed for this prevalent network type. Here, we propose a new latent space model for dynamic multilayer networks.
Joshua Daniel Loyal, Yuguo Chen
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Frontiers in Genetics, 2021 The effects of genes on physiological and biochemical processes are interrelated and interdependent; it is common for genes to express pleiotropic control of complex traits.
Huiying Gong +6 more
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Deep Neural Networks and An Application in Health Sciences
Van Tıp Dergisi, 2021 INTRODUCTION: Because there is more than one hidden layer between the input and output layers in the neural network algorithm, it is called "Deep Neural Networks". In the study, the Deep Neural Networks algorithm; different input (number of layers, epoch,
Sadi Elasan
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Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Multilayer networks allow for modeling complex relationships, where individuals are embedded in multiple social networks at the same time. Given the ubiquity of such relationships, these networks have been increasingly gaining attention in the literature.
Marcin Waniek +2 more
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Multilayer Network Risk Factor Pricing Model
Complexity, 2020 This paper proposes a multilayer network risk factor pricing model to depict the impact of interactions between stocks on excess stock returns by constructing the network risk factor based on the stock multilayer network and introducing it to the ...
Yu Liu, Conglin Hu, Lei Wang, Kun Yang
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Multilayer Satellite Network Dynamic Access Technology
天地一体化信息网络, 2022 Using the characteristics of satellites in diff erent orbits to build a more effi cient multilayer satellite network has become a hotspot in satellite network research in recent years.Traditional satellite network access methods have been unable to meet ...
Yunhan LI +4 more
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