AHP VIKOR framework for selecting wind turbine materials with a focus on corrosion and efficiency.

Autor: Raju SK; School of Computing, SASTRA Deemed University, Thanjavur, 613401, India. sekar1971kr@gmail.com., Natesan S; School of Computing, SASTRA Deemed University, Thanjavur, 613401, India., Alharbi AH; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia., Kannan S; K. Ramakrishnan College of Engineering (Autonomous), Samayapuram, 621 112, India., Khafaga DS; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia., Periyasamy M; Cyber security and MCA, Paavai Engineering College (Autonomous), Namakkal, 637 018, India., Eid MM; Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura, Egypt., El-Kenawy EM; Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt.

Publikováno v: Scientific reports [Sci Rep] 2024 Oct 14; Vol. 14 (1), pp. 24071. Date of Electronic Publication: 2024 Oct 14.

Hybrid attention-based deep neural networks for short-term wind power forecasting using meteorological data in desert regions.

Autor: Belletreche M; Department of Matter Sciences, Faculty of Matter Sciences, Mathematics, and Computer Science, Ahmed Draia University of Adrar, Adrar, 01000, Algeria., Bailek N; Laboratory of Mathematics Modeling and Applications, Department of Mathematics and Computer Science, Faculty of Matter Sciences, Mathematics, and Computer Science, Ahmed Draia University of Adrar, Adrar, 01000, Algeria. bailek.nadjem@univ-adrar.edu.dz.; Energies and Materials Research Laboratory, Faculty of Sciences and Technology, University of Tamanghasset, Tamanghasset, 10034, Algeria. bailek.nadjem@univ-adrar.edu.dz., Abotaleb M; Department of System Programming, South Ural State University, Chelyabinsk, 454080, Russia., Bouchouicha K; Centre de Développement des Energies Renouvelables, CDER, BP 62 Route de l'Observatoire, Bouzaréah, Algiers, 16340, Algeria., Zerouali B; Laboratory of Architecture, Cities and Environment, Department of Hydraulic, Faculty of Civil Engineering and Architecture, Hassiba Benbouali University of Chlef, B.P. 78C, Ouled Fares, Chlef, 02180, Algeria., Guermoui M; Centre de Développement des Energies Renouvelables, Unité de Recherche Appliquée en Energies Renouvelables, URAER, CDER, Ghardaïa, 47133, Algeria., Kuriqi A; CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. RoviscoPais 1, Lisbon, 1049-001, Portugal., Alharbi AH; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia., Khafaga DS; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia. dskhafga@pnu.edu.sa., El-Shimy M; Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo, 11566, Egypt., El-Kenawy EM; Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt.

Publikováno v: Scientific reports [Sci Rep] 2024 Sep 19; Vol. 14 (1), pp. 21842. Date of Electronic Publication: 2024 Sep 19.

Integrating machine and deep learning technologies in green buildings for enhanced energy efficiency and environmental sustainability.

Autor: Mahmood S; School of Finance and Economics, Jiangsu University, Zhenjiang, China. shahidnajam786@live.com., Sun H; School of Finance and Economics, Jiangsu University, Zhenjiang, China.; School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China., El-Kenawy EM; Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt.; MEU Research Unit, Middle East University, Amman, Jordan., Iqbal A; School of International Studies, Zhengzhou University, Zhengzhou, China., Alharbi AH; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, 11671, Riyadh, Saudi Arabia., Khafaga DS; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, 11671, Riyadh, Saudi Arabia.

Publikováno v: Scientific reports [Sci Rep] 2024 Sep 02; Vol. 14 (1), pp. 20331. Date of Electronic Publication: 2024 Sep 02.

An improved deep reinforcement learning routing technique for collision-free VANET.

Autor: Upadhyay P; Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Gwalior, Gwalior, Madhya-Pradesh, India., Marriboina V; Deptartment of Computer Science and Engineering, SVKM's NMIMS MPSTME Shirpur, Shirpur, India., Goyal SJ; Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Gwalior, Gwalior, Madhya-Pradesh, India., Kumar S; School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India. drskumar.cs@gmail.com., El-Kenawy EM; Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt. skenawy@ieee.org., Ibrahim A; Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt., Alhussan AA; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, PO Box 84428, Riyadh, 11671, Saudi Arabia., Khafaga DS; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, PO Box 84428, Riyadh, 11671, Saudi Arabia.

Publikováno v: Scientific reports [Sci Rep] 2023 Dec 08; Vol. 13 (1), pp. 21796. Date of Electronic Publication: 2023 Dec 08.

Brain Tumor Detection and Classification Using Deep Learning and Sine-Cosine Fitness Grey Wolf Optimization.

Autor: ZainEldin H; Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt., Gamel SA; Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt., El-Kenawy EM; Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt., Alharbi AH; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia., Khafaga DS; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia., Ibrahim A; Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt., Talaat FM; Machine Learning & Information Retrieval Department, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33511, Egypt.

Publikováno v: Bioengineering (Basel, Switzerland) [Bioengineering (Basel)] 2022 Dec 22; Vol. 10 (1). Date of Electronic Publication: 2022 Dec 22.