In computer science, soft computing (SC) was inspired by the human mind as the role model. Soft computing deals with imprecision, uncertainty, partial truth, robustness and low solution cost. The principal constituents of soft computing are fuzzy logic control (FLC), artificial neural networks (ANN), evolutionary computation (EC), machine learning (ML), and probabilistic reasoning (PR). Soft computing has applications in several fields of engineering as well as complex systems arising in biology and medicine.
In computer science, intelligent control (IC) was inspired by observable and imitable aspects of intelligent activity of human beings and nature. The essence of the intelligent control systems is to process and interpret data of various nature so that computational intelligence is strictly connected with the increase in available data as well as their capabilities of processing mutually supportive factors.
Intelligent control and computational intelligence have applications in many fields of engineering, data analysis, forecasting, biomedicine, image and sound processing, system identification, signal processing, multidimensional data visualisation, analysis of lexicographic data, diagnostic systems, expert systems, etc. Intelligent control systems are very useful when no mathematical model is available, a priori and intelligent control develops a system to be controlled. Important types of intelligent control are fuzzy logic, artificial neural networks, ant colony optimisation, bee colony optimisation, particle swarm optimisation, support vector machines, etc.
This special issue focuses on the applications of soft computing and intelligent control and will feature high level research articles on the latest research applications of soft computing and intelligent control, especially on fuzzy logic, artificial neural networks and evolutionary optimisation techniques.
The issue will carry revised and substantially extended versions of selected papers presented at the Fourth International Conference on Control, Engineering and Information Technology (CEIT-2016), but we also strongly encourage researchers unable to participate in the conference to submit articles for this call.
Suitable topics include, but are not limited, to the following:
- Applications of intelligent control
- Ant colony optimisation
- Artificial neural networks
- Bayesian network
- Bee colony optimisation
- Cellular neural networks
- Chaos theory
- Computational Intelligence
- Evolutionary computation
- Fuzzy logic control
- Genetic algorithms
- Intelligent control
- Machine learning
- Metaheuristic and swarm intelligence
- Nature-inspired optimisation methods
- Neuro-fuzzy control
- Particle swarm optimisation
- Support vector machines
Manuscripts due by: 20 April, 2017