Topic Editors

Department of Advanced Computational Methods, Faculty of Science and Technology Jan Dlugosz University in Czestochowa 13/15 Armii Krajowej Av., 42-200 Czestochowa, Poland
Faculty of Science and Technology, Jan Dlugosz University in Czestochowa, Armii Krajowej 13/15, 42-200 Czestochowa, Poland
Faculty of Science and Technology, Jan Dlugosz University in Czestochowa, Armii Krajowej 13/15, 42-200 Czestochowa, Poland
Faculty of Science and Technology, Jan Dlugosz University in Czestochowa, 13/15 Armii Krajowej Av., 42-200 Czestochowa, Poland
Dr. Ghulam Moeen Uddin
Department of Mechanical Engineering, University of Engineering & Technology, Lahore, Punjab 54890, Pakistan

AI and Computational Methods for Modelling, Simulations and Optimizing of Advanced Systems: Innovations in Complexity

Abstract submission deadline
30 November 2024
Manuscript submission deadline
30 January 2025
Viewed by
1846

Topic Information

Dear Colleagues,

Due to the increasing computational capability of current data processing systems, new opportunities emerge in the modelling, simulations and optimization of complex systems and devices. Difficult-to-apply, highly demanding and time-consuming methods may now be considered when developing complete and sophisticated models in many areas of science and technology. Combining AI algorithms and computational methods, including numerical and other methods, allows for conducting multi-threaded analyses to solve advanced and interdisciplinary problems.

This article collection aims to bring together research on advances in the modelling, simulations and optimization issues of complex systems, considering the great interest received for the part I of the topic.

Original research, review articles and short communications focusing on (but not limited to) artificial intelligence and other computational methods are welcome.

Prof. Dr. Jaroslaw Krzywanski
Dr. Marcin Sosnowski
Dr. Karolina Grabowska
Dr. Dorian Skrobek
Dr. Ghulam Moeen Uddin
Topic Editors

Keywords

  • artificial intelligence
  • artificial neural networks
  • deep learning
  • genetic and evolutionary algorithms
  • artificial immune systems
  • fuzzy logic
  • information theory
  • expert systems
  • bio-inspired methods
  • CFD
  • fractal and fractional problems
  • fractional and fractal dynamics
  • functional analysis
  • quantum mechanics
  • micro and nano-mechanics
  • fluidics and nano-fluidics
  • modelling
  • simulation
  • optimization
  • complex systems

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Algorithms
algorithms
2.3 3.7 2008 15 Days CHF 1600 Submit
Energies
energies
3.2 5.5 2008 16.1 Days CHF 2600 Submit
Entropy
entropy
2.7 4.7 1999 20.8 Days CHF 2600 Submit
Fractal and Fractional
fractalfract
5.4 3.6 2017 18.9 Days CHF 2700 Submit
Machine Learning and Knowledge Extraction
make
3.9 8.5 2019 19.9 Days CHF 1800 Submit
Materials
materials
3.4 5.2 2008 13.9 Days CHF 2600 Submit

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Published Papers (2 papers)

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12 pages, 3122 KiB  
Article
Numerical Simulation of Soliton Propagation Behavior for the Fractional-in-Space NLSE with Variable Coefficients on Unbounded Domain
by Fengzhou Tian, Yulan Wang and Zhiyuan Li
Fractal Fract. 2024, 8(3), 163; https://doi.org/10.3390/fractalfract8030163 - 12 Mar 2024
Viewed by 893
Abstract
The soliton propagation of the fractional-in-space nonlinear Schrodinger equation (NLSE) is much more complicated than that of the corresponding integer NLSE. The aim of this paper is to discover some novel fractal soliton propagation behaviors (FSPBs) of this fractional-in-space NLSE. Firstly, the exact [...] Read more.
The soliton propagation of the fractional-in-space nonlinear Schrodinger equation (NLSE) is much more complicated than that of the corresponding integer NLSE. The aim of this paper is to discover some novel fractal soliton propagation behaviors (FSPBs) of this fractional-in-space NLSE. Firstly, the exact solution is compared with the present numerical solution, and the validity and accuracy of the present numerical method are verified. Secondly, the effect of fractional derivatives on soliton propagation is explored through the present numerical simulation results. At the same time, the present method is extended to the three-dimensional fractional-order NLSE. Finally, some novel FSPBs of the fractional-in-space NLSE are given. Full article
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19 pages, 6293 KiB  
Article
Reaction Curve-Assisted Rule-Based PID Control Design for Islanded Microgrid
by T. K. Bashishtha, V. P. Singh, U. K. Yadav and T. Varshney
Energies 2024, 17(5), 1110; https://doi.org/10.3390/en17051110 - 26 Feb 2024
Viewed by 467
Abstract
In a renewable energy-based islanded microgrid system, frequency control is one of the major challenges. In general, frequency oscillations occur in islanded microgrids due to the stochastic nature of load and variable output power of distributed generating units (DGUs). In the presented research [...] Read more.
In a renewable energy-based islanded microgrid system, frequency control is one of the major challenges. In general, frequency oscillations occur in islanded microgrids due to the stochastic nature of load and variable output power of distributed generating units (DGUs). In the presented research proposal, frequency oscillations are suppressed by implementing the proportional integral derivative (PID) controller-based control design strategy for an islanded microgrid. The modeling of the islanded microgrid is firstly presented in the form of a linearized transfer function. Further, the derived transfer function is approximated into its equivalent first-order plus dead time (FOPDT) form. The approximated FOPDT transfer function is obtained by employing the reaction curve method to calculate the parameters of the FOPDT transfer function. Furthermore, the desired frequency regulation is achieved for the manifested FOPDT transfer function by incorporating PID control design. For PID controller tuning, different rule-based methods are implemented. Additionally, comparative analysis is also performed to ensure the applicability of the comparatively better rule-based tuning method. The Wang–Chan–Juang (WCJ) method is found effective over other rule-based tuning methods. The efficacy of the WCJ method is proved in terms of transient response and frequency deviation. The tabulated data of tuning parameters, time domain specifications, and error indices along with responses are provided in support of the presented control strategy. Full article
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