Guest Editors
Dr. Govind Vashishtha
Email: govind.vashishtha@pwr.edu.pl
Affiliation: Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, Wroclaw, Poland
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Research Interests: fault diagnosis, condition monitoring, optimization, signal processing and application of artificial intelligence and machine learning
Dr. Sumika Chauhan
Email: sumika.sumika@pwr.edu.pl
Affiliation: Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, Wroclaw, Poland
Homepage:
Research Interests: optimization, signal processing, filter design, wireless sensor design and application of machine learning and artificial intelligence
Summary
This special issue explores the dynamic and rapidly evolving field of swarm-based optimization, focusing on its transformative impact across diverse domains within modern engineering. Swarm intelligence algorithms, inspired by the collective behavior of social insects and animal groups, offer powerful solutions to complex optimization problems. This issue highlights cutting-edge research, innovative applications, and emerging trends that leverage the unique advantages of swarm-based approaches to address challenges in areas ranging from artificial intelligence, predictive maintenance, fault diagnosis, condition monitoring and robotics to data science and network optimization. We aim to showcase the versatility and potential of these algorithms to drive advancements and foster interdisciplinary collaborations. The scope of the issue includes:
· New swarm-based optimization algorithms and hybrid approaches
· Applications in machine learning and deep learning
· Robotics and autonomous systems
· Condition monitoring, fault diagnosis, and predictive maintenance
· Evolutionary computation and genetic algorithms
· Real-world applications
· Theoretical advancements
Keywords
Swarm intelligence, optimization algorithms, computer science, cross-disciplinary applications, machine learning, robotics, data Science, Network Optimization, condition monitoring, fault diagnosis and predictive maintenance
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