Results 51 to 60 of about 38,897 (297)

Intelligent Layout Method of Ship Pipelines Based on an Improved Grey Wolf Optimization Algorithm

Journal of Marine Science and Engineering
Ship piping arrangement is a nondeterministic polynomial problem. Based on the advantages of the grey wolf optimization (GWO) algorithm, which is simple, easy to implement, and has few adjustment parameters and fast convergence speed, the study adopts ...
Yongjin Lu, Kai Li, Rui Lin, Yunlong Wang, Hairong Han   +4 more
doaj   +1 more source

Stochastic Nanoscale Biophysical Cues as a Basis for the Induction of Glioblastoma‐Like Transcriptional Programs in Astrocytes

Advanced Science, EarlyView.
Stochastic nanoscale physical cues induce glioblastoma (GBM)‐associated transcriptional traits in naïve astrocytes leading to spontaneous formation of spheroids. Cells within spheroids express activated‐MMP2 and a differential gene expression pattern involving P53 and NOTCH3, providing evidence for a role for changes in brain topography, as observed in
Laurent Starck, Tobias Butelmann, Sabrina Hogan, Melika Sarem, Bernd Heimrich, Ritwick Sawarkar, Marie‐Françoise Ritz, Gregor Hutter, V. Prasad Shastri   +8 more
wiley   +1 more source

CMGWO: Grey wolf optimizer for fusion cell-like P systems

Heliyon
The grey wolf optimizer is a widely used parametric optimization algorithm. It is affected by the structure and rank of grey wolves and is prone to falling into the local optimum.
Yourui Huang, Quanzeng Liu, Hongping Song, Tao Han, Tingting Li   +4 more
doaj   +1 more source

In-Wheel Motor Control System for Four-Wheel Drive Electric Vehicle Based on CR-GWO-PID Control

Sensors, 2023
In order to improve the driving performance of four-wheel drive electric vehicles and realize precise control of their speed, a Chaotic Random Grey Wolf Optimization-based PID in-wheel motor control algorithm is proposed in this paper.
Xiaoguang Xu, Miao Wang, Ping Xiao, Jiale Ding, Xiaoyu Zhang   +4 more
doaj   +1 more source

Improved multi-strategy adaptive Grey Wolf Optimization for practical engineering applications and high-dimensional problem solving

Artificial Intelligence Review
The Grey Wolf Optimization (GWO) is a highly effective meta-heuristic algorithm leveraging swarm intelligence to tackle real-world optimization problems.
Mingyang Yu, Jing Xu, Weiyun Liang, Yu Qiu, Sixu Bao, Lin Tang   +5 more
semanticscholar   +1 more source

A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long‐Read Data

Advanced Science, EarlyView.
SpecImmune introduces a unified computational framework optimized for long‐read sequencing to resolve over 400 highly polymorphic immune genes. This scalable approach achieves high‐resolution typing, enabling the discovery of cross‐family co‐evolutionary networks and population‐specific diversity.
Shuai Wang, Xuedong Wang, Mengyao Wang, Qian Zhou, Lusheng Wang, Shuai Cheng Li   +5 more
wiley   +1 more source

Optimised Internet of Thing framework based hybrid meta‐heuristic algorithms for E‐healthcare monitoring

IET Networks, EarlyView., 2022
Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi, Shymaa Mohammed Jameel, Firas Husham Almukhtar, Musaddak Maher Abdul Zahra, Refed Adnan Jaleel   +4 more
wiley   +1 more source

Path Planning of UAV Based on Improved Adaptive Grey Wolf Optimization Algorithm

IEEE Access, 2021
Aiming at the three-dimensional path planning of unmanned aerial vehicle (UAV) in the complex environment of material delivery in earthquake-stricken areas, this paper proposes an improved adaptive grey wolf optimization algorithm (AGWO) based on the ...
Wei Zhang, Sai Zhang, Fengyan Wu, Yagang Wang   +3 more
semanticscholar   +1 more source

Individualized Atrophy‐Based Prediction of Dementia Progression in Familial Frontotemporal Lobar Degeneration With Bayesian Linear Mixed‐Effects Modeling

Annals of Neurology, EarlyView.
Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD.
Shubir Dutt, Dana Leichter, Yann Cobigo, Amy Wolf, John Kornak, Annie Clark, Lucy L. Russell, Arabella Bouzigues, David M. Cash, Martina Bocchetta, Molly Olzinski, Brian Appleby, Ece Bayram, Barbara Borroni, Andrea Bozoki, Chris R. Butler, David Clark, Rhian S. Convery, R. Ryan Darby, Alexandre de Mendonça, Bradford Dickerson, Kimiko Domoto‐Reilly, Simon Ducharme, Eve Ferry‐Bolder, Elizabeth Finger, Phoebe H. Foster, Douglas R. Galasko, Daniela Galimberti, Alexander Gerhard, Nupur Ghoshal, Caroline Graff, Neill Graff‐Radford, Ian M. Grant, Chadwick M. Hales, Lawrence S. Honig, Ging‐Yuek Hsiung, Edward D. Huey, David Irwin, Lize C. Jiskoot, Walter Kremers, Justin Y. Kwan, Robert Laforce, Isabelle Le Ber, Gabriel C. Léger, Johannes Levin, Irene Litvan, Ian R. Mackenzie, Mario Masellis, Mario F. Mendez, Fermin Moreno, Chiadi Onyike, Markus Otto, Belen Pascual, Peter Pressman, Rosa Rademakers, Eliana Marisa Ramos, Aaron Ritter, Erik D. Roberson, James B. Rowe, Raquel Sanchez‐Valle, Isabel Santana, Harro Seelaar, Allison Snyder, Sandro Sorbi, Matthis Synofzik, Maria Carmela Tartaglia, Pietro Tiraboschi, John C. van Swieten, Marijne Vandebergh, Rik Vandenberghe, Hilary W. Heuer, Bruce L. Miller, William W. Seeley, Maria Luisa Gorno‐Tempini, Joel H. Kramer, Leah Forsberg, Kejal Kantarci, Bradley F. Boeve, Adam L. Boxer, Jonathan D. Rohrer, Howard J. Rosen, Adam M. Staffaroni, FTD Prevention Initiative (FPI) investigators   +82 more
wiley   +1 more source

Joint power control and user grouping mechanism for efficient uplink non‐orthogonal multiple access‐based 5G communication: Utilising the Lèvy‐flight firefly algorithm

IET Networks, EarlyView., 2023
We utilise a metaheuristic optimisation method, inspired by nature, called the Lévy‐flight firefly algorithm (LFA), to tackle the power regulation and user grouping in the NOMA systems. Abstract The non‐orthogonal multiple access strategies have shown promise to boost fifth generation and sixth generation wireless networks' spectral efficiency and ...
Zaid Albataineh, Khaled F. Hayajneh, Haythem Bany Salameh, Raed Al Athamneh, Yaser Jararweh   +4 more
wiley   +1 more source