| Autor: |
Chen Li, Min Xu, Siming He, Zhiyu Mao, Tong Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Intelligent Systems with Applications, Vol 23, Iss , Pp 200392- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2667-3053 |
| DOI: |
10.1016/j.iswa.2024.200392 |
| Popis: |
This paper introduces a novel approach utilizing normalized flow networks (NFNs) for dynamic personal risk (PR) analysis, specifically focusing on the assessment of two-way data rates at network nodes. NFNs, a sophisticated paradigm in data processing and modeling derived from machine learning principles, serve as the foundational framework for our analysis. Leveraging NFNs, we develop a generalized method that integrates information transmission techniques into PR dynamics, enabling a comprehensive examination of communication efficacy within network structures. Our study entails the formulation of dynamic models tailored to capture the evolving nature of PR interactions, facilitating the evaluation of data rates exchanged between network nodes. Through extensive simulations and empirical validation, we demonstrate the effectiveness of our approach in elucidating the intricate dynamics of PR campaigns and quantifying the impact on the network performance. The findings underscore the significance of leveraging NFNs for dynamic PR analysis, offering valuable insights into optimizing communication strategies and enhancing network efficiency in diverse domains. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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