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Submit a Manuscript to the Journal
Cogent Engineering

For a Special Issue on
Bio-inspired Algorithm & Complex System in Electrical and Computer Engineering

Manuscript deadline
28 February 2022

Cover image - Cogent Engineering

Special Issue Editor(s)

Sangeeta Singh, National Institute of Technology Patna
[email protected]

Subodh Srivastava, National Institute of Technology Patna
[email protected]

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Bio-inspired Algorithm & Complex System in Electrical and Computer Engineering

Recently there is a huge surge in the research related to Bio-inspired algorithms and methods from computational intelligence techniques as swarm or evolutionary algorithms to other techniques based on principles or models of biological systems. The problems related to the representation and practical application of these kinds of algorithms provide new and interesting solutions in traditionally complex domains. Distributed computing develops methods and technology to build systems that are composed of collaborating components. The domains and problems traditionally handled by distributed computing allow us to look for new challenges in bio-inspired computation approaches. This special issue welcomes submissions of original papers introducing research results in all aspects covering the roles of knowledge and intelligence in distributed systems, ranging from concepts and theoretical developments to advanced technologies and innovative applications. The key topic will be based on practical and real world utilization of bio-inspired methods, techniques and algorithms in previous types of systems and domains.

This special issue is targeted to cover all aspects of the Bio-inspired Algorithm & Complex System in Electrical and Computer Engineering and the interaction of metaheuristics –evolutionary algorithms, swarm intelligence, etc.- with complex systems and latest research and development, up-to-date issues, and challenges in the fields of BioMedical Data Analysis, and related applications. Proposed submissions should be original, unpublished, and present novel in-depth fundamental research contributions either from a methodological perspective or from an application point of view.

The special issue focuses primarily on papers developing new optimization models, modeling features and/or solution techniques that were driven by the need for a particular application, such as science and technology such as electrical engineering, electrotechnics, electric machines modeling and design, control of sensors, electronics, communications, data transmission, energy converters, transducers modeling and artificial intelligence, pattern recognition, knowledge engineering, process control theory and applications, distributed systems, computer networks and software engineering and showing the impact these models and algorithms had for the application.
Topics of interest include, but are not limited to, the following:

  • New theories and methods in different BIC paradigms applied to Biomedical data analysis, such as linear programming semi-definite and conic programming, semi-infinite programming
  • Stochastic programming, global optimization, nonlinear and non-smooth optimization, multi-objective optimization
  • Hybrid systems involving software agents and human actors
  • Bio-inspired integration of data, information and processes
  • Autonomic, adaptive and self-organized distributed computing
  • Intelligent service-oriented distributed systems
  • Self-organising and adaptive distributed systems
  • Emerging behaviours in complex distributed systems
  • Knowledge integration and fusion from distributed sources
  • Data mining and knowledge discovery in distributed settings based on bio-inspired methods
  • Intelligent distributed problem solving and decision making
  • Bio-inspired computation in complex and real applications (videogames, e-business/e-commerce, e-learning, e-health, e-science, e-government, crisis management, etc.)
  • Swarm intelligence and evolutionary computation in distributed and intelligent applications
  • Bio-inspired computation for unmanned systems
  • Bio-inspired computation for social-based knowledge
  • Forecasting through complex system models and bio-inspired models
  • New theories and methods in different BIC paradigms applied to Biomedical data analysis, such as linear programming semi-definite and conic programming, semi-infinite programming
  • Stochastic programming, global optimization, nonlinear and non-smooth optimization, multi-objective optimization
  • Evolutionary Computations
  • Evolutionary Strategies/Programming
  • Genetic Algorithms/Programming
  • Granular Computing Organic Computing
  • Particle Swarm Optimization Swarm-based Algorithms