Zobrazeno 1 - 10
of 3 171
pro vyhledávání: '"Restricted Boltzmann Machine"'
Publikováno v:
Journal of Intelligent Systems, Vol 33, Iss 1, Pp 6821-30 (2024)
A traceability and analysis method for measurement laboratory testing data based on the intelligent Internet of Things (IoT) and deep belief network (DBN) is proposed to address the issue of low accuracy in identifying anomalies in measurement testin
Externí odkaz:
https://doaj.org/article/b2a8183e0b4746a7aaeba8a4f7b0893c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract While the globe continues to struggle to recover from the devastation brought on by the COVID-19 virus's extensive distribution, the recent worrying rise in human monkeypox outbreaks in several nations raises the possibility of a novel world
Externí odkaz:
https://doaj.org/article/bbe812895fd04297af0433ba1a508bde
Publikováno v:
IET Radar, Sonar & Navigation, Vol 18, Iss 6, Pp 876-890 (2024)
Abstract Model‐based acoustic localisation estimates the locations of underwater objects by comparing sensor measurements with model predictions. To obtain high quality predictions, propagation models need to be run for a large set of environmental
Externí odkaz:
https://doaj.org/article/1880320e43c047fcabe076a7f3a0739d
Autor:
Ranganathaswamy Madihalli Kenchappa, Rakesh Kumar Yadav, Alka Singh Noida, Arvind Kumar Pandey
Publikováno v:
Proceedings on Engineering Sciences, Vol 6, Iss 1, Pp 241-250 (2024)
Industrial automation systems (IASs) are utilized in vital facilities to sustain society's fundamental services. As a consequence, protecting them against terrorist operations, natural catastrophes and cyber-threats is essential. The research on tech
Externí odkaz:
https://doaj.org/article/29a8cb9be364445791fcaa89d61bf740
Autor:
S Thumilvannan, R Balamanigandan
Publikováno v:
PeerJ Computer Science, Vol 10, p e2196 (2024)
Stroke prediction has become one of the significant research areas due to the increasing fatality rate. Hence, this article proposes a novel Adaptive Weight Bi-Directional Long Short-Term Memory (AWBi-LSTM) classifier model for stroke risk level pred
Externí odkaz:
https://doaj.org/article/dfae5d5416354c95b01959433901e967
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionEvent-related potentials (ERPs), such as P300, are widely utilized for non-invasive monitoring of brain activity in brain-computer interfaces (BCIs) via electroencephalogram (EEG). However, the non-stationary nature of EEG signals and dif
Externí odkaz:
https://doaj.org/article/a40bbc2b65874a92a1bd19406d6a39ea
Autor:
Amal H. Alharbi, Doaa Sami Khafaga, El-Sayed M. El-kenawy, Marwa M. Eid, Abdelhameed Ibrahim, Laith Abualigah, Nima Khodadadi, Abdelaziz A. Abdelhamid
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
As the number of individuals who drive electric vehicles increases, it is becoming increasingly important to ensure that charging infrastructure is both dependable and conveniently accessible. Methodology: In this paper, a recommendation system is pr
Externí odkaz:
https://doaj.org/article/3e292574ddf84b8c8b30947ea95182ce
Publikováno v:
IEEE Access, Vol 12, Pp 91263-91271 (2024)
The precise prediction of energy consumption is crucial for businesses, companies, and households especially when it comes to planning energy purchases. An underestimated or overestimated forecast value may result in the use of energy inefficiently.
Externí odkaz:
https://doaj.org/article/fc69e66ed8294618b5e8041d101c549c
Autor:
Liu Hongyun
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 8, Iss 2, Pp 2599-2606 (2023)
In this paper, the emotions of dancers are identified in combination with the integrated deep-learning model. Firstly, four initial value features with important emotional states are extracted from the time, frequency, and time-frequency domains, res
Externí odkaz:
https://doaj.org/article/22bec3517c234b2ca8aedb072451a4bf
Autor:
Koji Watanabe, Katsumi Inoue
Publikováno v:
Human-Centric Intelligent Systems, Vol 3, Iss 3, Pp 296-311 (2023)
Abstract Understanding the dynamics of a system is crucial in various scientific and engineering domains. Machine learning techniques have been employed to learn state transition rules from observed time-series data. However, these data often contain
Externí odkaz:
https://doaj.org/article/2858d73ce2d34dcfbef20de806d830d6