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

被引：0

作者：

Anwar, Muhammad ^{[1
]}

Hidayat, Hendra ^{[1
]}

Sabrina, Elsa ^{[1
]}

机构：

[1] Univ Negeri Padang, Jalan Prof Hamka,Kampus Air Tawar Barat, Padang, Indonesia

来源：

TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS | 2023年 / 12卷 / 03期

关键词：

Engineering education; genetic algorithm; digital filter design; signal processing; DIGITAL-FILTER DESIGN;

D O I：

10.18421/TEM123-54

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1719 / 1724

页数：6

共 23 条

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