Zobrazeno 1 - 10
of 297
pro vyhledávání: '"Graph Networks"'
Autor:
Yongqing ZHOU, Dawei HAO, Yuchen FAN, Xintong WEN, Chang WEI, Xin LIU, Wenzhen ZHANG, Heyang WANG
Publikováno v:
Meitan xuebao, Vol 49, Iss 10, Pp 4127-4137 (2024)
Due to the introduction of large-scale renewable energy to the electric grid, the coal-fired units are running more under load cycling conditions and this has dramatically increased the difficulty of boiler in the control of NOx emissions. The real-t
Externí odkaz:
https://doaj.org/article/de4de299066a402fbf7a1591b26aa293
Publikováno v:
AKCE International Journal of Graphs and Combinatorics, Vol 21, Iss 3, Pp 225-231 (2024)
Irregular convex triangular networks consist of the interior of a 6-sided convex polygon drawn on the infinite triangular network. Formal description of these applicable networks is provided. In the main result it is proved that the metric dimension
Externí odkaz:
https://doaj.org/article/f00596b152944e99abca782b4a6d449d
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103301- (2024)
Plant diseases are increasingly becoming a serious threat to food security as well as sustainable agriculture sets. Traditional methods for detecting crop diseases, especially in Finger Millet, are cumbersome with chances of error. Therefore, automat
Externí odkaz:
https://doaj.org/article/c9563c9f5de349c2a388f156b6cf3986
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Compared with the time-consuming and labor-intensive for biological validation in vitro or in vivo, the computational models can provide high-quality and purposeful candidates in an instant. Existing computational models face limi
Externí odkaz:
https://doaj.org/article/f628e944211d4862b1343e635b2e39a5
Autor:
Tiwari, Shailendra a, ⁎, Gehlot, Anita a, Singh, Rajesh a, Twala, Bhekisipho b, Priyadarshi, Neeraj c
Publikováno v:
In Results in Engineering December 2024 24
Autor:
Qionghao Huang, Jili Chen
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-26 (2024)
Abstract Educational big data significantly impacts education, and Massive Open Online Courses (MOOCs), a crucial learning approach, have evolved to be more intelligent with these technologies. Deep neural networks have significantly advanced the cru
Externí odkaz:
https://doaj.org/article/fb289fffb2a34d9d8c1c80c1f9506b18
Autor:
Qionghao Huang, Yan Zeng
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 3, Pp 3557-3575 (2024)
Abstract Academic performance is a crucial issue in the field of Online learning analytics. While deep learning-based models have made significant progress in the era of big data, many of these methods need help to capture the complex relationships p
Externí odkaz:
https://doaj.org/article/7c9217e3605e43fe805a0d71be9d984a
Publikováno v:
IEEE Access, Vol 12, Pp 157630-157656 (2024)
In the fast-changing video surveillance area, there exists a critical need for new ways in which the huge and complex data availed from CCTV systems can be correctly analyzed. Most already-existing methods of person detection and video analysis are n
Externí odkaz:
https://doaj.org/article/d0dd9adc9e9b472692a83c5ae5579302
Publikováno v:
IEEE Access, Vol 12, Pp 140611-140627 (2024)
The prediction of traffic flow has emerged as a pivotal element within the domain of intelligent transport systems, garnering considerable interest and attention from various quarters. SpatioTemporal Graph Neural Networks (STGNNS) have been extensive
Externí odkaz:
https://doaj.org/article/82d4ad5d8e024f12bb1505cdc1178baa
Publikováno v:
Knowledge, Vol 3, Iss 3, Pp 293-306 (2023)
Deep learning is widely used in many real-life applications. Despite their remarkable performance accuracies, deep learning networks are often poorly calibrated, which could be harmful in risk-sensitive scenarios. Uncertainty quantification offers a
Externí odkaz:
https://doaj.org/article/ea6e3b3cac01457ea0e27c24f46222ef