Natural Computing (journal)

Natural Computing is a peer-reviewed scientific journal published by Springer. It focuses on research exploring computation inspired by natural phenomena. The journal aims to provide a multidisciplinary forum for researchers, practitioners, and educators interested in the theory, design, and application of computation techniques based on principles observed in biology, physics, and other natural systems.

The scope of Natural Computing includes a wide array of topics, such as:

• Evolutionary Computation: Genetic algorithms, genetic programming, evolution strategies, and other methods inspired by biological evolution.

• Neural Computation: Artificial neural networks, spiking neural networks, and other computational models based on the structure and function of the brain.

• Swarm Intelligence: Ant colony optimization, particle swarm optimization, and other algorithms inspired by the collective behavior of social insects and other animal groups.

• Artificial Immune Systems: Computational techniques inspired by the principles of the vertebrate immune system.

• DNA Computing: Computation using DNA molecules and other biological materials.

• Membrane Computing: Computational models inspired by the structure and function of cell membranes.

• Quantum Computing: Computation using the principles of quantum mechanics.

• Fractal Geometry: Computational models leveraging the properties of fractal patterns found in nature.

• Amorphous Computing: Computational paradigms for managing and programming systems composed of large numbers of unreliable, locally interacting components.

• Self-Organizing Systems: Computational models capable of self-assembly, self-repair, and other forms of self-organization.

The journal publishes original research articles, review articles, and short communications. It is aimed at researchers in computer science, engineering, biology, physics, and other related fields. The Natural Computing journal contributes to the advancement of understanding and development of novel computational paradigms and applications.