Computational Intelligence and Neuroscience

Advances in Recent Nature-Inspired Algorithms for Neural Engineering


Publishing date
01 Dec 2019
Status
Published
Submission deadline
26 Jul 2019

Lead Editor

1Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile

2University of Extremadura, Cáceres, Spain

3CINVESTAV-Tamaulipas, Tamaulipas, Mexico

4University Carlos III of Madrid, Getafe, Spain


Advances in Recent Nature-Inspired Algorithms for Neural Engineering

Description

Nature-inspired algorithms are general-purpose problem solvers that operate as a collection of intelligent agents, mimicking interesting phenomena from nature in order to efficiently solve a specific problem. Many optimization techniques belonging to artificial intelligence were born under this paradigm, which are able to combine data, knowledge, learning, and search strategies for building advanced algorithms. This is a particularly interesting area for neural engineering, and other AI-related applications.

During the last three years, many new nature-inspired algorithms have been proposed, such as human behavior-based optimization, spotted hyena optimization, dragonfly optimization, Andean Condor Algorithm, water evaporation optimization, collective decision optimization, interactive search algorithm, vapour-liquid equilibrium metaheuristic, selfish herds algorithm, scattering and repulsive swarm intelligence, social engineering optimization, virus colony search, thermal exchange optimization, and kidney-inspired algorithm. Most of them involve interesting novel aspects that have enabled the efficient solving of complex problems, particularly from the NP-hard and NP-complete class of problems.

This special issue aims to publish original research and review articles involving theoretical and/or practical aspects of recent nature-inspired algorithms for Neural Engineering.

Potential topics include but are not limited to the following:

  • Recent nature-inspired algorithms in neural engineering
  • Recent nature-inspired algorithms in neural networks
  • Recent nature-inspired algorithms in computational neuroscience
  • Recent nature-inspired algorithms in real-world optimization problems
  • Neural network learning in recent nature-inspired algorithms and vice versa

Articles

  • Special Issue
  • - Volume 2020
  • - Article ID 7836239
  • - Editorial

Advances in Recent Nature-Inspired Algorithms for Neural Engineering

Ricardo Soto | Juan A. Gómez-Pulido | ... | Pedro Isasi
  • Special Issue
  • - Volume 2020
  • - Article ID 3287589
  • - Research Article

Double-Criteria Active Learning for Multiclass Brain-Computer Interfaces

Qingshan She | Kang Chen | ... | Yingchun Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 4854895
  • - Review Article

Cat Swarm Optimization Algorithm: A Survey and Performance Evaluation

Aram M. Ahmed | Tarik A. Rashid | Soran Ab. M. Saeed
  • Special Issue
  • - Volume 2020
  • - Article ID 2710561
  • - Research Article

A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm

Zhe Wang | Shangce Gao | ... | Yuki Todo
  • Special Issue
  • - Volume 2019
  • - Article ID 3238574
  • - Research Article

A Db-Scan Binarization Algorithm Applied to Matrix Covering Problems

José García | Paola Moraga | ... | Gino Astorga
  • Special Issue
  • - Volume 2019
  • - Article ID 4589060
  • - Research Article

A Neural Network-Inspired Approach for Improved and True Movie Recommendations

Muhammad Ibrahim | Imran Sarwar Bajwa | ... | Bakhtiar Kasi
  • Special Issue
  • - Volume 2019
  • - Article ID 8097213
  • - Research Article

Image Processing-Based Detection of Pipe Corrosion Using Texture Analysis and Metaheuristic-Optimized Machine Learning Approach

Nhat-Duc Hoang | Van-Duc Tran
Computational Intelligence and Neuroscience
 Journal metrics
Acceptance rate28%
Submission to final decision79 days
Acceptance to publication37 days
CiteScore4.700
Impact Factor2.284
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