Special Issue "Bio-inspired Computer Modelling: Theories and Applications in Engineering and Sciences"

Submission Deadline: 28 April 2022
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Guest Editors
Dr. Xiaochun Cheng, Middlesex University, UK
Prof. Mario J. Pérez Jiménez, University of Seville, Spain
Prof. Sun-Yuan Kung, Princeton University, USA

Summary

Bio-inspired computer modelling researches computerised solutions (such as data structures, algorithms, computation or visualisation operations with data, ways to control cyber physical operations, topological structures, decision support systems, multisource data communication and analysis, et al.) from the living phenomena or biological systems (such as cells, tissues, the brain, neural network, immune system, ant colony, genetic evolution, human and organisational behaviour, crowd, swarm, social network, frog, et al.). The areas of bio-inspired computer modelling include Neural Networks, Brain-inspired Computing, Neuromorphic Computing and Architectures, Cellular Automata and Cellular Neural Networks, Evolutionary Algorithms, Swarm Intelligence, Logics and Symbolic Systems, DNA and Molecular Computing, Membrane Computing, Artificial Intelligence, Machine Learning, Deep Learning. There are relevant potential applications in engineering and sciences, such as computer vision for medical engineering, pattern recognition in medicine, decision support in cybernetics, intelligent building, intelligent transportation, smart city, etc.

 

This special issue aims to attract latest research results and the latest solutions for bio-inspired computer modelling. Both theory focused and application driven studies are welcome, especially papers with good technical depth or with emerging applications in engineering and sciences.

 

Potential topics include, but are not limited to the following:

- Neural Networks

- Neuromorphic Computing and Architectures 

- Evolutionary Computing

- DNA and Molecular Computing

- Membrane Computing

- Cellular Automata and Cellular Neural Networks

- Swarm Intelligence

- Crowd Sourcing

- Artificial Immune System

- Frog Algorithm


Keywords
Neural Networks, Neuromorphic Computing, Evolutionary Computing, DNA and Molecular Computing, Membrane Computing, Swarm Intelligence, Frog Algorithm