34   Artículos

 
en línea
Cihan Ates, Dogan Bicat, Radoslav Yankov, Joel Arweiler, Rainer Koch and Hans-Jörg Bauer    
In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digital tw... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Nur Hamid, Willy Dharmawan and Hidetaka Nambo    
Unmanned surface vehicles (USVs) are experiencing significant development across various fields due to extensive research, enabling these devices to offer substantial benefits. One kind of research that has been developed to produce better USVs is path p... ver más
Revista: Applied System Innovation    Formato: Electrónico

 
en línea
Yong Yu, Shudong Chen, Rong Du, Da Tong, Hao Xu and Shuai Chen    
Temporal knowledge graphs play an increasingly prominent role in scenarios such as social networks, finance, and smart cities. As such, research on temporal knowledge graphs continues to deepen. In particular, research on temporal knowledge graph reasoni... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Xiaoyu Han, Chenyu Li, Zifan Wang and Guohua Liu    
Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML). Although search methods based on reinforcement learning and evolutionary ... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Valeria Mercuri, Martina Saletta and Claudio Ferretti    
As the prevalence and sophistication of cyber threats continue to increase, the development of robust vulnerability detection techniques becomes paramount in ensuring the security of computer systems. Neural models have demonstrated significant potential... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Tatiana Lazovskaya, Dmitriy Tarkhov, Maria Chistyakova, Egor Razumov, Anna Sergeeva and Tatiana Shemyakina    
The article presents the development of new physics-informed evolutionary neural network learning algorithms. These algorithms aim to address the challenges of ill-posed problems by constructing a population close to the Pareto front. The study focuses o... ver más
Revista: Computation    Formato: Electrónico

 
en línea
Thomas Carolus and Konrad Bamberger    
This study targets determining impellers of impeller-only axial fans with an optimal hub-to-tip ratio for the highest achievable total-to-static efficiency. Differently from other studies, a holistic approach is chosen. Firstly, the complete class of the... ver más

 
en línea
Zhenwei Yang, Hang Lv, Xinyi Wang, Hengrui Yan and Zhaofeng Xu    
In recent years, inrush water has hampered the regular mining of coal mines, and the proper identification of the source of inrush water is critical to the prevention and management of water hazards in mines. This paper extracts the standard water chemis... ver más
Revista: Water    Formato: Electrónico

 
en línea
Dennis Delali Kwesi Wayo, Sonny Irawan, Alfrendo Satyanaga and Jong Kim    
Data-driven models with some evolutionary optimization algorithms, such as particle swarm optimization (PSO) and ant colony optimization (ACO) for hydraulic fracturing of shale reservoirs, have in recent times been validated as one of the best-performing... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Wentao Li, Wenbo Li, Yunqin He and Guozhu Liang    
The reverse design of solid propellant grain for a performance-matching goal, one of the most challenging directions of the solid rocket motor designing work, is limited by the traditional semi-empirical parameter-driven optimization methods based on som... ver más
Revista: Aerospace    Formato: Electrónico

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