A Self‐adaptive Bald Eagle Search optimization algorithm with dynamic opposition‐based learning for global optimization problems-Reference-Cited by-同舟云学术

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A Self‐adaptive Bald Eagle Search optimization algorithm with dynamic opposition‐based learning for global optimization problems

Published:2022-10-19 Issue:2 Volume:40 Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Sharma Suvita Rani¹^ORCID,Kaur Manpreet²^ORCID,Singh Birmohan¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering Sant Longowal Institute of Engineering and Technology, Longowal Sangrur Punjab India

2. Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology, Longowal Sangrur Punjab India

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.13170

Reference75 articles.

1. A novel Whale Optimization Algorithm integrated with Nelder–Mead simplex for multi-objective optimization problems

2. Aquila Optimizer: A novel meta-heuristic optimization algorithm

3. Chaotic bee colony algorithms for global numerical optimization

4. A Novel Solution for Day-Ahead Scheduling Problems Using the IoT-Based Bald Eagle Search Optimization Algorithm

5. A PEMFC model optimization using the enhanced bald eagle algorithm

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1. Bald eagle search algorithm: a comprehensive review with its variants and applications;Systems Science & Control Engineering;2024-08

2. A multi-strategy improved beluga whale optimization algorithm for constrained engineering problems;Cluster Computing;2024-07-29

3. Dynamic Random Walk and Dynamic Opposition Learning for Improving Aquila Optimizer: Solving Constrained Engineering Design Problems;Biomimetics;2024-04-04

4. Improvement of medical data security using SABES optimization algorithm;The Journal of Supercomputing;2024-02-25

5. An improved gazelle optimization algorithm using dynamic opposition-based learning and chaotic mapping combination for solving optimization problems;The Journal of Supercomputing;2024-02-22

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