1 August 2017

Call for papers: "Advances and Applications of Computational Intelligence"

For a special issue of the International Journal of Intelligent Engineering Informatics.

Computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. The principal constituents of Computational Intelligence (CI) are Fuzzy Logic (FL), Evolutionary Computation (EC), Machine Learning (ML) and Probabilistic Reasoning (PR), etc.
 
The development of Computational Intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Without them, the development of this field would be almost impossible, and its application practically marginal. That is why these techniques have especially developed in recent years. Developed theories of computational intelligence have been quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualisation, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations.
 
This special issue aims at presenting the latest developments, trends, research solutions and applications of computational intelligence to modelling and engineering problems with effective use of fuzzy logic control, neural networks and biology inspired optimisation techniques, etc.
 
We invite researchers to contribute original research articles as well as review articles that will stimulate the continuing efforts to improve the current state of art on the aforementioned fields.
 
Suitable topics include, but are not limited, to the following:
  • Ant colony optimisation (ACO)
  • Bayesian network
  • Bee colony optimisation (BCO)
  • Cellular neural network (CNN)
  • Chaos theory
  • Computational intelligence (CI)
  • Evolutionary computing
  • Fuzzy logic control (FLC)
  • Genetic algorithms (GA)
  • Intelligent control
  • Machine learning
  • Meta-heuristic and swarm intelligence
  • Nature-inspired optimisation methods
  • Particle swarm optimisation (PSO)
  • Support vector machines
 
Important Dates
Manuscripts due by: 30 September, 2017
Notification to authors: 30 November, 2017
Final versions due by: 30 January, 2018

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