State-of-the-Art Development of Complex Systems and Their Simulation Methods

Tang, Yiming; Li, Lin; Liu, Xiaoping

doi:10.23919/csms.2021.0025

Cited by 21 publications

(8 citation statements)

References 97 publications

(84 reference statements)

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“…In [18], Modeling and simulation are widely used in various fields such as engineering, physics, finance, and social sciences. In engineering, they are used to design and optimize the performance of various systems such as structures, fluid flow, heat transfer, and power systems.…”

Section: Overview Of Modeling and Simulationmentioning

confidence: 99%

Different Numerical Techniques, Modeling and Simulation in Solving Complex Problems

Hong

2023

JMC

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This study investigates the performance of different numerical techniques, modeling, and simulation in solving complex problems. The study found that the Finite Element Method was found to be the most precise numerical approach for simulating the behavior of structures under loading conditions, the Finite Difference Method was found to be the most efficient numerical technique for simulating fluid flow and heat transfer problems, and the Boundary Element Method was found to be the most effective numerical technique for solving problems involving singularities, such as those found in acoustics and electromagnetics. The mathematical model established in this research was able to effectively forecast the behaviors of the system under different conditions, with an error of less than 5%. The physical model established in this research was able to replicate the behavior of the system under different conditions, with an error of less than 2%. The employment of multi-physics or multi-scale modeling was found to be effective in overcoming the limitations of traditional numerical techniques. The results of this research have significant effects for the field of numerical techniques, modeling and simulation, and can be used to guide engineers and researchers in choosing the most appropriate numerical technique for their specific problem or application.

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Section: Overview Of Modeling and Simulationmentioning

confidence: 99%

Different Numerical Techniques, Modeling and Simulation in Solving Complex Problems

Hong

2023

JMC

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“…However, there are a large number of potential structural features in 3D data 41 . Introducing these to construct a new reconstruction model or impose constraints on the original model can further improve the reconstruction accuracy 42,43 . Therefore, designing an efficient 3D data reconstruction model is one of the challenges of 3D data CS reconstruction.…”

Section: Background and Basic Theorymentioning

confidence: 99%

Survey on compressed sensing reconstruction method for 3D data

Zhang

Xie

2022

Concurrency and Computation

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The information society has higher and higher requirements for the collection, transmission and storage of digital signals, and signal utilization efficiency has become an increasingly important part of the digital signal processing process. The traditional digital signal processing needs to satisfy the Nyquist sampling theorem to ensure the restoration of the signal, while the digital signal processing method based on compressed sensing can sample and reconstruct the signal under the conditions that much lower than the Nyquist sampling theorem. Undoubtedly, the utilization efficiency of digital signals has been greatly accelerated. In this article, taking hyperspectral images and videos as examples, we review the basic theory, reconstruction model, and reconstruction algorithm of 3D data compressed sensing. We analyze, summarize, and discuss the existing literature. Finally, the research status of compressive sensing reconstruction methods for hyperspectral images and videos is compared, and several important research directions for compressive sensing reconstruction of 3D data in the future are proposed.

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“…erefore, the characteristics of systematic error, that is, the change law, are often inconsistent [28]. In the process of system reliability analysis, the normal working or failure state of components is regarded as certain [29].…”

Section: Fuzzy Reliability Analysis Of Systemmentioning

confidence: 99%

The Characteristics and Physical Fitness Characteristics of Track and Field Sprint Events Based on Discrete Dynamic Modeling of Complex Systems

Zhao

2022

Mobile Information Systems

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Sprint is not only the oldest sport in track and field but also one of the most competitive sports today. This paper studies the characteristics of sprint and the physical characteristics of sports human body. Using the characteristics of genetic programming combined with system structure estimation and parameter estimation, this paper expounds the application of genetic programming in discrete dynamic modeling of complex systems. A model evaluation method based on error estimation is proposed. Based on the analysis of big data, the intelligent control model of track and field sprinters’ training progress is designed, and the simulation experiment is carried out through the simulation environment. This paper analyzes their physical quality, discusses the contents and methods of sprint training, and provides a reference for coaches engaged in sprint training. The intelligent training schedule model of track and field sprinters from the perspective of big data analysis has outstanding practical value. It can quickly and accurately formulate training plans, solve data fluctuations under the trend of big data segmentation, and realize intelligent operation. Its fluency and accuracy are very high, which is worthy of vigorous promotion and application.

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State-of-the-Art Development of Complex Systems and Their Simulation Methods

Cited by 21 publications

References 97 publications

Different Numerical Techniques, Modeling and Simulation in Solving Complex Problems

Different Numerical Techniques, Modeling and Simulation in Solving Complex Problems

Survey on compressed sensing reconstruction method for 3D data

The Characteristics and Physical Fitness Characteristics of Track and Field Sprint Events Based on Discrete Dynamic Modeling of Complex Systems

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