Advances in Natural Computing: Methods and Application
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 15005
Special Issue Editor
Interests: swarm intelligence; natural computing; evolutionary computation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
One of the ever-present grand challenges and central goals of computer science is to understand the world around us in terms of information processing. Each time progress is made in achieving this goal, both the world around us and computer science benefit.
Nature is a dominating part of the world around us, and one way to understand it in terms of information processing is to study computing taking place in nature. Natural computing is concerned with this type of computing and with its main benefit for computer science, viz., human-designed computing inspired by nature.
By its very nature, the science of natural computing is genuinely interdisciplinary; therefore, natural computing forms a bridge between natural sciences and computer science. In this way, natural computing elevates computer science to an even more prominent role in the broad rainbow of scientific disciplines.
Human-designed computing inspired by nature is based on the use of paradigms, principles, and mechanisms underlying natural systems. Some disciplines of human-designed computing are relatively old and are well established by now. Well-known examples of such disciplines are evolutionary computing and neural computing. Evolutionary algorithms are based on the concepts of mutation, recombination, and natural selection from the theory of evolution, while neural networks are based on concepts originating in the study of the highly interconnected neural structures in the brain and nervous system. On the other hand, molecular computing and quantum computing are younger disciplines of natural computing: molecular computing is based on paradigms from molecular biology, while quantum computing is based on quantum physics and exploits quantum parallelism.
Natural computing refers to computational processes observed in nature, and human-designed computing inspired by nature. When complex natural phenomena are analyzed in terms of computational processes, our understanding of both the nature and essence of computation is enhanced. Characteristic for human-designed computing inspired by nature is the metaphorical use of concepts, principles, and mechanisms underlying natural systems. Natural computing includes evolutionary algorithms, neural networks, molecular computing, and quantum computing.
The purpose of this Special Issue is to gather a collection of articles reflecting the latest developments in different fields of evolutionary algorithms, neural networks, molecular computing, quantum computing and artificial immune systems, and others.
Prof. Dr. Gaige Wang
Guest Editor
Manuscript Submission Information
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Keywords
- natural computing
- evolutionary algorithms
- swarm intelligence
- neural networks
- molecular computing
- quantum computing
- artificial immune systems
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: A Deep Learning Model to Forecast the Spanish Electricity Demand Caused by Pandemic COVID-19
Authors: Juan Antonio Martínez Lao; Silvia Sánchez-Salinas; Alejandro Cama Pinto; Natalia Fernanda Pascual Gómez; Francisco G. Montoya; Francisco Manuel Arrabal Campos
Affiliation: (1) Department of Engineering, CIMEDES Research Center (CeiA3), University of Almería, Carretera Sacramento s/n, 04120 Almería, Spain;
(2) Faculty of Engineering, Universidad de la Costa, Calle 58 # 55–66, 080002 Barranquilla, Atlántico, Colombia;
(3) Clinical Analysis Service Hospital Universitario de la Princesa, Madrid;
(4) Department of Chemistry and Physics, Research Centre CIAIMBITAL, University of Almería, Carretera Sacramento s/n, 04120 Almería, Spain;