Complexity

Computational Intelligence in Modeling Complex Systems and Solving Complex Problems


Publishing date
01 May 2018
Status
Published
Submission deadline
29 Dec 2017

1Budapest University of Technology and Economics, Budapest, Hungary

2University of Cadiz, Cadiz, Spain

3University of Alberta, Edmonton, Canada

4Sejong University, Seoul, Republic of Korea

5Murdoch University, Perth, Australia


Computational Intelligence in Modeling Complex Systems and Solving Complex Problems

Description

Models and procedures based on nature inspired approaches are called Computational Intelligence (CI). CI includes three major areas: fuzzy systems, artificial neural networks, and evolutionary (and population based) algorithms, including their hybrid combinations. It is often advantageous to combine them with traditional approaches, such as gradient type optimization or bounded exhaustive search. Such methods often successfully cope with complexity.

Computer Science (CS) defines complex systems as being intractable (usually NP-hard) and showing nondeterministic and uncertain behavior. Problems with complex systems are common in engineering, in natural sciences, in biomedical systems, and even in social systems. Modeling, control, decision support, search, and optimization here often lead to a dead end when classic mathematics and traditional CS are applied. From the application aspect, however, it is often sufficient to deploy approaches which offer good suboptimal solutions. Where no general algorithm exists, a “satisfactory solution” might be achieved by a proper metaheuristic, suitable for finding the exact optimum for a limited class of problems (with bounded dimensionality or bounded uncertainty) and delivering close to the optimum solution for a wider (still bounded) class of the same problem. The “goodness” of such a solution is measured by the “overall cost.”

It is possible to quantify the overall cost of a combined model and associated algorithm by adding the costs of time and space complexity to the cost of model errors. A “solution” (model or data structure and algorithm) is “efficient” if the overall cost is possibly low or is less than a predefined threshold. Often in search and optimization problems there are metaheuristics, which certainly find the exact solution for a limited size and may find the solution in a wider range, while in other cases (depending on structure and size) they will not find any solution at all. The need of resources is often unpredictable; thus it is never sure if a solution will be delivered at all. We expect “efficacious” solutions, which are efficient and predictable at the same time—and possibly generally applicable.

This special issue will focus on most recent research results on new models, structures, and algorithmic, mainly metaheuristic approaches to complex problems with reasonably good modeling accuracy and with reasonably low and predictable resources needed.

As CI approaches are often suitable for delivering such efficacious solutions, authors are invited to present theories, algorithms, and frameworks aimed at bringing about advanced techniques of Computational Intelligence for the modeling of complex systems and the solution of complex problems.

Potential topics include but are not limited to the following:

  • Interpolative and hierarchical fuzzy systems
  • Fuzzy signatures and signature sets
  • Fuzzy cognitive maps, artificial neural networks, and learning systems
  • Genetic, bacterial, and other evolutionary algorithms (Big Bang Big Crunch Algorithm, Particle Swarm Optimization, Imperialist Competitive Optimization, etc.)
  • Hybrid models consisting of fuzzy/neural/evolutionary algorithms
  • All in the context of complex systems and problems

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 6201356
  • - Research Article

Communication Analysis of Network-Centric Warfare via Transformation of System of Systems Model into Integrated System Model Using Neural Network

Bong Gu Kang | Kyung-Min Seo | Tag Gon Kim
  • Special Issue
  • - Volume 2018
  • - Article ID 5676504
  • - Research Article

Systematic Approach to Optimization for Protection Against Intentional Ultrashort Pulses Based on Multiconductor Modal Filters

Anton O. Belousov | Talgat R. Gazizov
  • Special Issue
  • - Volume 2018
  • - Article ID 3051854
  • - Research Article

An Improved MOEA/D Based on Reference Distance for Software Project Portfolio Optimization

Jing Xiao | Jing-Jing Li | ... | Chang-Qin Huang
  • Special Issue
  • - Volume 2018
  • - Article ID 3685927
  • - Research Article

Improved Method for Predicting the Performance of the Physical Links in Telecommunications Access Networks

Ferenc Lilik | Szilvia Nagy | László T. Kóczy
  • Special Issue
  • - Volume 2018
  • - Article ID 9540726
  • - Research Article

Trust-Based Situation Awareness: Comparative Analysis of Agent-Based and Population-Based Modeling

Zara Nasar | Syed Waqar Jaffry
  • Special Issue
  • - Volume 2018
  • - Article ID 2480365
  • - Research Article

Improved Optimization for Wastewater Treatment and Reuse System Using Computational Intelligence

Zong Woo Geem | Sung Yong Chung | Jin-Hong Kim
  • Special Issue
  • - Volume 2018
  • - Article ID 9073597
  • - Research Article

The Intuitionistic Fuzzy Linguistic Cosine Similarity Measure and Its Application in Pattern Recognition

Donghai Liu | Xiaohong Chen | Dan Peng
  • Special Issue
  • - Volume 2018
  • - Article ID 3927951
  • - Research Article

A Hybrid Approach for Modular Neural Network Design Using Intercriteria Analysis and Intuitionistic Fuzzy Logic

Sotir Sotirov | Evdokia Sotirova | ... | Stanimir Surchev
  • Special Issue
  • - Volume 2018
  • - Article ID 5036791
  • - Research Article

Legendre Cooperative PSO Strategies for Trajectory Optimization

Lei Liu | Yongji Wang | ... | Jiashi Gao
  • Special Issue
  • - Volume 2018
  • - Article ID 8546976
  • - Research Article

Extension of the Multi-TP Model Transformation to Functions with Different Numbers of Variables

Péter Baranyi
Complexity
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 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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