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Complex network modeling of evidence theory

WebNov 1, 2024 · Abstract Dempster-Shafer evidence theory is widely used in the field of information fusion especially when confronting with uncertainties. ... Deng Y., Complex network modeling of evidence theory, IEEE Transactions on Fuzzy Systems 99 (2024) 1. Google Scholar [37] Mao S., Deng Y., Pelusi D., Alternatives selection for produced … WebJul 27, 2024 · Abstract. Complex networks can model a wide range of complex systems in nature and society, and many algorithms (network generators) capable of synthesizing networks with few and very specific ...

Conflicting evidence combination from the perspective of …

WebOct 20, 2024 · As an extension of probability theory, evidence theory is able to better handle unknown and imprecise information. Owing to its advantages, evidence theory has more flexibility and effectiveness for modeling and processing uncertain information. Uncertainty measure plays an essential role both in evidence theory and probability … WebAug 1, 2024 · A new complex evidence theory. Dempster-Shafer evidence theory is widely used in the field of information fusion since it satisfies weaker conditions than probability theory. Nevertheless, the description space of the current evidence theory is only real space, and it cannot effectively describe and process the uncertain information … can you marinate a chuck roast https://thev-meds.com

Special Issue "Complex Network Modeling: Theory and Applications"

WebJul 1, 2024 · Combining basic probability assignments (BPAs) with time series is common in real-life cases. Therefore, a new evidence fusion approach based on belief entropy and … WebOct 31, 2024 · Some typical issues of evidence theory, such as conflicting evidence, multiclass evidence clustering, and computational complexity for large-scale fusion … WebDescription. Epidemics spread through a diversity of interactions, and affect many healthy people within a short time, resulting in profound social and economic consequences. Although the research community has accumulated overwhelming evidence for the roles of complex networks in the modelling of epidemic dynamics, we are still confronted with ... brigith martin

Complex Network Modeling of Evidence Theory - IEEE …

Category:Special Issue "Complex Network Modeling: Theory and Applications"

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Complex network modeling of evidence theory

Role of Complex Networks in Modelling Epidemic Dynamics

WebMay 16, 2024 · To be specific, a mass function in the generalized Dempster–Shafer evidence theory is modeled by a complex number, called as a complex basic belief assignment, which has more powerful ability to express uncertain information. Based on that, a generalized Dempster’s combination rule is exploited. In contrast to the classical … WebApr 1, 2024 · This approach has superiority in identifying nodes that seem unimportant but are important in the complex network. Besides, it provides a quantitative model to measure the global importance of each node (GIN). ... Due to the efficiency of evidence theory in data fusion [58], [59], [60], Evidence theory [61], [62] offers a flexible way to …

Complex network modeling of evidence theory

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Web2.2 Complex network models. In complex network theory, different types of networks are used to explain the behavior of real-world complex systems. In this section, a brief … Webt. e. In the context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in networks representing real systems. The study of complex networks is a young and active area of scientific research [1] [2 ...

WebJan 14, 2024 · Complex networks are dynamic systems that change continuously with time. How to construct network evolution models is the core problem of the complex … Web-soft-computing techniques for empirical regression modeling (e.g., Artificial Neural Networks);-techniques for solving nonlinear, constrained optimization problems (e.g., Genetic Algorithms);-methods for modeling the behavior of power networks and interdependent infrastructures (e.g., complex network theory).

WebJul 13, 2024 · Network analysis is a powerful tool that provides us a fruitful framework to describe phenomena related to social, technological, and many other real-world complex systems. In this paper, we present a brief review about complex networks including fundamental quantities, examples of network models, and the essential role of network … WebIn the context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or …

WebApr 10, 2024 · The evidence theory and original definition and inference mechanism of conventional EN is firstly recommended, and the DT-DEN is further presented. …

WebOct 26, 2024 · Dempster-Shafer (D-S) evidence theory needs the weaker conditions than Bayesian probability theory by assigning the probability into power sets. Hence it has the more stronger ability to express imprecise and unknown information which can be used in many fields. In D-S evidence theory, how to measure the cross entropy between … can you marinate already cooked chickenWebMar 3, 2024 · In this paper we overcome this limitation, and develop a data-driven framework to control a complex network optimally and without any knowledge of the … can you marinade cooked beefWebSep 14, 2024 · Complex Network Modeling of Evidence Theory. Abstract: Because of the advantages of graphs in visualizing the relationship between individuals, complex networks have been widely used and greatly developed. In real-world applications of … brigith navarro lugoWebNov 1, 2024 · Inspired by the interaction among nodes in complex networks and the main ideas of the theory of system core and coritivity, this paper conducts a network structure … brigithaWebZhao and Deng, 2024 Zhao J., Deng Y., Complex network modeling of evidence theory, IEEE Transactions on Fuzzy Systems 29 (11) (2024) 3470 – 3480. Google Scholar Zhou et al., 2024 Zhou C. , Ding L. , Zhou Y. , Luo H. , Topological mapping and assessment of multiple settlement time series in deep excavation: A complex network perspective ... brigit mahoney feetWebDec 5, 2024 · In this study, we use evidence theory to solve link prediction in multiplex networks by viewing it as an uncertain information fusion problem. To predict links in the … can you marinate and freeze meatWebRigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the ... brigit luffingham