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An enhanced grey wolf optimizer boosted machine learning prediction model for patient-flow prediction.
Comput Biol Med
September 2023
Zhejiang Engineering Research Center of Intelligent Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China. Electronic address:
Large and medium-sized general hospitals have adopted artificial intelligence big data systems to optimize the management of medical resources to improve the quality of hospital outpatient services and decrease patient wait times in recent years as a result of the development of medical information technology and the rise of big medical data. However, owing to the impact of several elements, including the physical environment, patient, and physician behaviours, the real optimum treatment effect does not meet expectations. In order to promote orderly patient access, this work provides a patient-flow prediction model that takes into account shifting dynamics and objective rules of patient-flow to handle this issue and forecast patients' medical requirements.
View Article and Find Full Text PDFStarling-Behavior-Inspired Flocking Control of Fixed-Wing Unmanned Aerial Vehicle Swarm in Complex Environments with Dynamic Obstacles.
Biomimetics (Basel)
November 2022
Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China.
For the sake of accomplishing the rapidity, safety and consistency of obstacle avoidance for a large-scale unmanned aerial vehicle (UAV) swarm in a dynamic and unknown 3D environment, this paper proposes a flocking control algorithm that mimics the behavior of starlings. By analyzing the orderly and rapid obstacle avoidance behavior of a starling flock, a motion model inspired by a flock of starlings is built, which contains three kinds of motion patterns, including the collective pattern, evasion pattern and local-following pattern. Then, the behavior patterns of the flock of starlings are mapped on a fixed-wing UAV swarm to improve the ability of obstacle avoidance.
View Article and Find Full Text PDFOrderly as a swarm of bees.
Nat Rev Chem
June 2020
Department of Geological Sciences and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden.
Three-dimensional trajectories and network analyses of group behaviour within chimney swift flocks during approaches to the roost.
Proc Biol Sci
February 2017
Biology Department, University of North Carolina at Chapel Hill, NC 27510, USA.
Chimney swifts () are highly manoeuvrable birds notable for roosting overnight in chimneys, in groups of hundreds or thousands of birds, before and during their autumn migration. At dusk, birds gather in large numbers from surrounding areas near a roost site. The whole flock then employs an orderly, but dynamic, circling approach pattern before rapidly entering a small aperture We recorded the three-dimensional trajectories of ≈1 800 individual birds during a 30 min period encompassing flock formation, circling, and landing, and used these trajectories to test several hypotheses relating to flock or group behaviour.
View Article and Find Full Text PDFSelf-organization in bacterial swarming: lessons from myxobacteria.
Phys Biol
October 2011
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
When colonizing surfaces, many bacteria are able to self-organize into an actively expanding biofilm, in which millions of cells move smoothly and orderly at high densities. This phenomenon is known as bacterial swarming. Despite the apparent resemblance to patterns seen in liquid crystals, the dynamics of bacterial swarming cannot be explained by theories derived from equilibrium statistical mechanics.
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