Vol.12, No.3, August 2023.                                                                                                                                                                               ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Exploring the use of Genetic Algorithms Toolbox in Engineering Education: Did it Provide an Interesting Learning Experience for Students?


Muhammad Anwar, Hendra Hidayat, Elsa Sabrina


© 2023 Muhammad Anwar, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 12, Issue 3, Pages 1719-1724, ISSN 2217-8309, DOI: 10.18421/TEM123-54, August 2023.


Received: 01 April 2023.

Revised:   13 July 2023.
Accepted: 01 August 2023.
Published: 28 August 2023.




Teaching in engineering education using Genetic Algorithms (GAs) toolbox as a teaching tool in engineering education can be an effective approach, particularly in Signal Processing subjects, as it encourages students to learn how to find optimal values required in designing digital filters. This research investigates the use of GAs for teaching digital filter design, where the evaluation function of the problem is optimized using Gas. The GAs toolbox simulation is designed to yield a stable, lowest-order H[z] that meets the tolerance parameters and satisfies the design criteria. Teaching GAs involves representing the filter design problem in a way that can be accepted by genetic programming.


Keywords –Engineering education, genetic algorithm, digital filter design, signal processing.



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