Zobrazeno 1 - 10
of 1 459
pro vyhledávání: '"Neural network algorithm"'
Autor:
Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi
Publikováno v:
Discover Chemical Engineering, Vol 4, Iss 1, Pp 1-16 (2024)
Abstract Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overal
Externí odkaz:
https://doaj.org/article/fe87c58b3172411b8921c3639a14df10
Publikováno v:
Zhipu Xuebao, Vol 45, Iss 6, Pp 897-906 (2024)
Flos Carthami (FC) has a good therapeutic effect on chronic alcoholic liver injury (CALI) in clinical practice, but the treatment mechanism is not very clear. Therefore, elucidating the molecular mechanism of action of FC in treating CALI is of great
Externí odkaz:
https://doaj.org/article/cd0b43e54c274de595eef0de5fa499a8
Publikováno v:
Yuanzineng kexue jishu, Vol 7, Iss 58, Pp 1432-1439 (2024)
During the operation of pressurized water reactor (PWR), the fuel assemblies would inevitably occur the phenomenon of bowing, due to the factors such as axial irradiation growth, high speed impact of coolant during operation and so on. This phenomeno
Externí odkaz:
https://doaj.org/article/77d072367a51424e833874db260a95a3
Autor:
Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Ashraf Azmi, Zainuddin Abd Manan, Jeng Shiun Lim, Hong An Er, Siti Nor Azreen Ahmad Termizi
Publikováno v:
Digital Chemical Engineering, Vol 13, Iss , Pp 100181- (2024)
Optimization on an industrial scale is a complex task that involves fine-tuning the performance of large-scale systems and applications to make them more efficient and effective. This process can be challenging due to the increasing volume of work, g
Externí odkaz:
https://doaj.org/article/dd5307cd527a40cf8723186bbed36edb
Autor:
Jiayin Zhang
Publikováno v:
Systems and Soft Computing, Vol 6, Iss , Pp 200158- (2024)
Painting color matching technology is widely used in the production and printing process of products. Traditional painting and color matching have been unable to meet market demands. Based on this, a large-scale corpus under the existing semantic int
Externí odkaz:
https://doaj.org/article/ab80f57ed9004844a3902a10651a3b49
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 55, Iss 2, Pp 223-230 (2024)
Purposes The intelligent filling of goaf is an important direction of green, safe, intelligent, and efficient mining of coal resources, and the key lies in intelligent decision-making and control of gangue-filling process in underground goaf. Methods
Externí odkaz:
https://doaj.org/article/3423b8b19b5c47b3a74a18630656b9b8
Autor:
Muhammad Naeem Aslam, Muhammad Waheed Aslam, Muhammad Sarmad Arshad, Zeeshan Afzal, Murad Khan Hassani, Ahmed M. Zidan, Ali Akgül
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-22 (2024)
Abstract In this article, examine the performance of a physics informed neural networks (PINN) intelligent approach for predicting the solution of non-linear Lorenz differential equations. The main focus resides in the realm of leveraging unsupervise
Externí odkaz:
https://doaj.org/article/a17dadfa3792446ea1e4d3c27704afef
Publikováno v:
Chengshi guidao jiaotong yanjiu, Vol 27, Iss 3, Pp 230-233 (2024)
[Objective] Worker′s unsafe behavior is the fundamental factor in urban rail transit construction accidents. As the traditional management mode is insufficient in restraining the workers from the unsafe behavior, it is necessary to eliminate the hi
Externí odkaz:
https://doaj.org/article/e859e3980e02468ebeddca67a1c7f798
Autor:
Yingdong Cao, Yun Wang
Publikováno v:
IEEE Access, Vol 12, Pp 125557-125570 (2024)
Currently, there are numerous challenges in the nursing and healing of children’s chronic lower limb wounds (CLLW), such as prolonged healing times, difficulties in pain management, high risk of infection, and insufficient parental caregiving knowl
Externí odkaz:
https://doaj.org/article/102a0b795d014628b1c781aeec72119e
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14543-14555 (2024)
Accurate medium- and long-term hydrological forecasting is crucial for sustainable water management, infrastructure planning, and ecosystem conservation. This study integrates visual geometry group convolution neural network algorithm (VGGNet)-driven
Externí odkaz:
https://doaj.org/article/ed1c72cc31534274aa692779601d350c