Suppr超能文献

Fully Scalable Fuzzy Neural Network for Data Processing.

作者信息

Apiecionek Łukasz

机构信息

Faculty of Computer Science, Kazimierz Wielki University in Bydgoszcz, Jana Karola Chodkiewicza 30, 85-064 Bydgoszcz, Poland.

出版信息

Sensors (Basel). 2024 Aug 10;24(16):5169. doi: 10.3390/s24165169.

Abstract

The primary objective of the research presented in this article is to introduce an artificial neural network that demands less computational power than a conventional deep neural network. The development of this ANN was achieved through the application of Ordered Fuzzy Numbers (OFNs). In the context of Industry 4.0, there are numerous applications where this solution could be utilized for data processing. It allows the deployment of Artificial Intelligence at the network edge on small devices, eliminating the need to transfer large amounts of data to a cloud server for analysis. Such networks will be easier to implement in small-scale solutions, like those for the Internet of Things, in the future. This paper presents test results where a real system was monitored, and anomalies were detected and predicted.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6223/11359782/6a68e07a6844/sensors-24-05169-g001.jpg

相似文献

1
Fully Scalable Fuzzy Neural Network for Data Processing.
Sensors (Basel). 2024 Aug 10;24(16):5169. doi: 10.3390/s24165169.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验