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Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
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A Composite Particle Swarm Optimization Algorithm for Hospital Equipment Management Risk Control Optimization and

Jinghui Li1, Li Zhang2, Xiangmin Gu3

  • 1Department of Hospital Office, Jiangsu Taizhou People's Hospital, Taizhou 225300, China.

Journal of Environmental and Public Health
|June 3, 2022
PubMed
Summary

A new composite particle swarm optimization algorithm enhances hospital equipment risk management. This method improves multidimensional analysis and global search accuracy, leading to better risk control and prediction.

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Area of Science:

  • Engineering
  • Computer Science
  • Healthcare Management

Background:

  • Particle swarm optimization (PSO) faces limitations in multidimensional analysis and global search capabilities.
  • Effective risk management for hospital equipment is crucial for operational efficiency and patient safety.

Purpose of the Study:

  • To address the limitations of traditional PSO by proposing a composite particle swarm optimization (CPSO) algorithm.
  • To enhance the accuracy and global search ability of PSO for hospital equipment risk management.
  • To improve the prediction and control of risks associated with hospital equipment.

Main Methods:

  • The proposed CPSO algorithm integrates k-clustering for risk management particle swarm optimization.
  • Multidimensional particle swarms are segmented to create an ordered set for risk prediction.
  • A fusion function is employed to construct a risk particle swarm set based on clustering degree for optimal extreme value identification.

Main Results:

  • MATLAB simulations demonstrate that CPSO outperforms standard PSO in global search accuracy and reduces search time.
  • The CPSO algorithm shows improved calculation time and accuracy in risk assessment.
  • The developed algorithm effectively analyzes hospital equipment risks and supports management control.

Conclusions:

  • The composite particle swarm optimization algorithm offers a superior approach to analyzing and managing hospital equipment risks.
  • CPSO enhances the accuracy and efficiency of risk assessment compared to traditional PSO.
  • This algorithm provides a valuable tool for improving hospital equipment management and mitigating associated risks.