| Περίληψη: | In recent decades, there has been a demand for the development of practical, cost-effective control system applications that properly address the negative effects of vibration and protect various machines from natural or man-made hazards. For this reason, vibration control has received considerable research attention. Vibration control devices can be divided into three categories called passive, active, and semi-active control systems. A parallel development in the last two decades has been the emergence of the field of computational intelligence (CI) consisting mainly of the three fields of neural networks, evolutionary computing, and fuzzy logic. This study focused on the application of genetic algorithms (GAs) to optimize the vibration behavior of two types of mechanical systems, a single-degree-of-freedom (SDoF) vibration system, and a mechanical system with a dynamic vibration absorber (DVA) that are both widely used as vibration isolation devices. In addition, a passive vehicle suspension system was modeled, and the system was optimized to check the reliability of the genetic algorithm. Finally, suitable user-friendly Suitable graphical user interfaces (GUIs) were created by applying the above optimization process, to train users in both the theory of oscillations and the understanding of the theory of genetic algorithms. From a technical point of view, this research argues that the use of GA to find optimal solutions in oscillation control cases can be a reliable and well-performing tool that can contribute to the training of people interested in such educational fields.
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