Zobrazeno 1 - 10
of 825
pro vyhledávání: '"Recurrent neural networks (RNNs)"'
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-25 (2024)
Abstract Discovering new chemical compounds with specific properties can provide advantages for fields that rely on materials for their development, although this task comes at a high cost in terms of complexity and resources. Since the beginning of
Externí odkaz:
https://doaj.org/article/46c4a59873a9454683ba3f8faff4113e
Publikováno v:
PeerJ Computer Science, Vol 10, p e2338 (2024)
Medical data analysis is an expanding area of study that holds the promise of transforming the healthcare landscape. The use of available data by researchers gives guidelines to improve health practitioners’ decision-making capacity, thus enhancing
Externí odkaz:
https://doaj.org/article/6bc12ac911fb451488837674038a9d92
Publikováno v:
Case Studies in Thermal Engineering, Vol 64, Iss , Pp 105516- (2024)
This paper investigates the use of Artificial Intelligence (AI), notably Recurrent Neural Networks (RNNs), to analyze heat transfer in moving radiative porous triangular systems with heat generation (HTMPTHG). AI-based RNN models are employed to simu
Externí odkaz:
https://doaj.org/article/7b3760d20ad748fea4faa2cf56d48ecd
Autor:
A.E. Abdelkareem
Publikováno v:
Diyala Journal of Engineering Sciences, Vol 17, Iss 3 (2024)
This research delves into the evaluation of Deep learning signal constellation identification (DL-SCI) algorithms in underwater acoustic communications using Orthogonal Frequency Division Multiplexing (OFDM). It distinctly examines at how effective t
Externí odkaz:
https://doaj.org/article/46118b42e0654f08a33fc85fef2ce801
Autor:
Chen, Tiansheng 1, Kang, Yanjie 1, Yan, Pengbo, Yuan, Yuan ⁎, Feng, Haoyang, Wang, Junhao, Zhai, Houzhong, Zha, Yuting, Zhou, Yuan, Tian, Gengyuan, Wang, Yangle
Publikováno v:
In Energy 30 December 2024 313
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5071-5081 (2024)
Abstract To solve a distributed optimal resource allocation problem, a collective neurodynamic approach based on recurrent neural networks (RNNs) is proposed in this paper. Multiple RNNs cooperatively solve a global constrained optimization problem i
Externí odkaz:
https://doaj.org/article/9f1905bcc72246c1ae9a6d96aba5efa7
Autor:
Nevena Rankovic, Dragica Rankovic
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 19, Iss 1, Pp 381-395 (2024)
Meeting customer requirements in software project management, even for large digital enterprises, proves challenging due to unpredictable human factors. It involves meticulous planning and environmental factor analysis, ultimately benefiting both com
Externí odkaz:
https://doaj.org/article/e1dc63456fb54e5c99c2ec079bd900a0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7608-7620 (2024)
Precipitation nowcasting is a critical aspect of meteorological services, which helps people make reasonable arrangements. Nowadays the methods based on recurrent neural networks are widely employed as the primary solution for precipitation nowcastin
Externí odkaz:
https://doaj.org/article/047384ce94b947bfaf93761713890445
Publikováno v:
Sensors, Vol 24, Iss 11, p 3495 (2024)
Research on transformers in remote sensing (RS), which started to increase after 2021, is facing the problem of a relative lack of review. To understand the trends of transformers in RS, we undertook a quantitative analysis of the major research on t
Externí odkaz:
https://doaj.org/article/c55fe1acb64b49bf85fd09b552fb27e0
Publikováno v:
IEEE Access, Vol 11, Pp 33148-33159 (2023)
Recurrent Neural Networks (RNNs) and their variants have been demonstrated tremendous successes in modeling sequential data such as audio processing, video processing, time series analysis, and text mining. Inspired by these facts, we propose human a
Externí odkaz:
https://doaj.org/article/7d06b84ef9734e368abcc746ff48f9d2