scholarly journals Computational Intelligence in Modeling Complex Systems and Solving Complex Problems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Laszlo T. Koczy ◽  
Jesus Medina ◽  
Marek Reformat ◽  
Kok Wai Wong ◽  
Jin Hee Yoon
Keyword(s):  
Complex Systems ◽  
Computational Intelligence ◽  
Complex Problems

Hybrid Computational Intelligence and the Basic Concepts and Recent Advances

2018 ◽  
pp. 180-190
Author(s):  
Georgios Dounias
Keyword(s):  
Computational Intelligence ◽  
Intelligent Systems ◽  
Domain Knowledge ◽  
Hybrid Intelligent Systems ◽  
Complex Problems ◽  
Recent Advances ◽  
New Findings ◽  
Wide Range ◽  
Computational Intelligent ◽  
Computational Technology

In this paper computational intelligence and its major methodologies are introduced in the first place, and then hybrid intelligent systems are defined and the most popular hybrid intelligent approaches are discussed. The increased popularity of hybrid intelligent systems during the last decade, is the result of the extensive success of these systems in a wide range of real-world complex problems, but also has to do with the increased capabilities of computational technology. One of the reasons for this success has to do with the synergy derived by the computational intelligent components, such as machine learning, fuzzy logic, neural networks, genetic algorithms, or other intelligent algorithms and techniques. Each of the partial methodologies provides hybrid systems with complementary reasoning and searching methods that allow the use of domain knowledge and empirical data to solve complex problems. The paper includes recent advances and new findings in the area of hybrid computational intelligence.

Modeling and optimization in complex systems based on computational intelligence

Kybernetes ◽  
2012 ◽  
Vol 41 (9) ◽  
pp. 1235-1243 ◽  
Author(s):  
Yingying Su ◽  
Taifu Li ◽  
Debiao Wang ◽  
Xinghua Liu
Keyword(s):  
Complex Systems ◽  
Computational Intelligence ◽  
Modeling And Optimization

scholarly journals A Physics Based Novel Approach for Travelling Tournament Problem: Optics Inspired Optimization

2019 ◽  
Vol 48 (3) ◽  
pp. 373-388 ◽  
Author(s):  
Bilal Alatas ◽  
Harun Bingol
Keyword(s):  
Computational Intelligence ◽  
Search Space ◽  
Complex Problems ◽  
Candidate Solution ◽  
Novel Approach ◽  
Light Point ◽  
Convex Mirror ◽  
Total Movement ◽  
Computational Intelligence Methods ◽  
First Time

Computational intelligence search and optimization algorithms have been efficiently adopted and used for many types of complex problems. Optics Inspired Optimization (OIO) is one of the most recent physics inspired computational intelligence methods which treats the search space of the problem to be optimized as a wavy mirror in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each candidate solution is treated as an artificial light point that its glittered ray is reflected back by the search space of the problem and the artificial image is formed based on mirror equations adopted from Optics, as a new candidate solution. In this study, OIO for the first time has been designed as solution search strategy for travelling tournament problem which is one of the current sports problems and aids to minimize transportation and total movement of teams. Furthermore, this problem has been firstly solved by League Championship Algorithm and obtained results from both synthetic and real datasets have been compared in this study for the first time. Obtained results show the superiority of OIO which is a novel algorithm and seems to efficiently solve many complex problems.

Harnessing Complex Systems

2020 ◽  
pp. 283-298
Author(s):  
Yorghos Apostolopoulos
Keyword(s):  
Complex Systems ◽  
Population Health ◽  
Scientific Evidence ◽  
Health Science ◽  
Knowledge Generation ◽  
Systems Science ◽  
Dynamic Complexity ◽  
Complex Problems ◽  
Complex Systems Science ◽  
Fundamental Shift

Many population health challenges have eluded scientists and policymakers for years because of misunderstanding of dynamic complexity. This chapter advocates an epistemological overhaul in population health science based on the premise that population health problems should be studied as complex systems because they operate as such. The proposed overhaul is predicated on the development of a new complex-systems-science–driven paradigm for a new population health science. It is founded on a fundamental shift in scientific thinking: from a quest for causes and accurate predictions to “control” problems, which inappropriate science and sheer uncontrollability of complex problems have curtailed, to knowledge generation, based on complex-systems-science–grounded theories and analytical methods to better understand, anticipate, curb, and manage health challenges, by way of harnessing their complexity. As both current and proposed epistemologies represent models of simpler and complex problems, respectively, appropriate use of each under the proposed paradigm can only strengthen population health science. These emerging ideas delve into the known as well as the possible and still unknown. Some ideas are grounded in long-standing scientific evidence, while others are of an emerging nature. Some are testable while others are partially tested, and still others remain untested “fantasies” about how to contend with intractable population health challenges.

scholarly journals Development of Perceived Complex Problem-Solving Instrument in Domain of Complex Systems

Systems ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 51
Author(s):  
Morteza Nagahi ◽  
Alieh Maddah ◽  
Raed Jaradat ◽  
Mohammad Mohammadi
Keyword(s):  
Problem Solving ◽  
Complex Systems ◽  
Systems Thinking ◽  
21St Century ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Final Model ◽  
Complex Problems ◽  
High Level ◽  
The Relationship

The ability to solve modern complex systems becomes a necessity of the 21st century. The purpose of this study is the development of an instrument that measures an individual’s perception toward solving complex problems. Based on literature and definitions, an instrument with four stages named perceived complex problem-solving (PCPS) was designed through exploratory and confirmatory stages. The instrument is validated and scaled through different models, and the final model is discussed. After completing validation and scale development of the PCPS instrument, the final model of the PCPS instrument was introduced to resolve the gap in the literature. The final model of the PCPS instrument is able to find and quantify the degree of perception an individual holds in dealing with complex problems and can be utilized in different settings and environments. Further research about the relationship between Systems Thinking and CPS revealed individuals with a high level of systems thinking have a better understanding of the characteristics of complex problems and so better perception of CPS.

scholarly journals Special issue on new trends and challenges of bio‐inspired computational intelligence algorithms in massively complex systems

2020 ◽  
Vol 37 (6) ◽  
Author(s):  
Antonio Gonzalez‐Pardo ◽  
Antonio J. Tallón‐Ballesteros ◽  
Hujun Yin
Keyword(s):  
Complex Systems ◽  
Computational Intelligence ◽  
Special Issue
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