Udemy

Optimization Using Genetic Algorithms : MATLAB Programming

立即報名
  • 7,731 名學生
  • 更新於 7/2022
4.4
(75 個評分)
CTgoodjobs 嚴選優質課程,為職場人士提升競爭力。透過本站連結購買Udemy課程,本站將獲得推廣佣金,有助未來提供更多實用進修課程資訊給讀者。

課程資料

報名日期
全年招生
課程級別
學習模式
修業期
0 小時 56 分鐘
教學語言
英語
授課導師
Karthik Karunakaran, Ph.D.
評分
4.4
(75 個評分)
5次瀏覽

課程簡介

Optimization Using Genetic Algorithms : MATLAB Programming

A Quick Way to Learn and Solve Optimization Problems in MATLAB. A Course for Beginners.

There has been a rapidly growing interest in a field called Genetic Algorithms during the last thirty years. Have you ever wondered how specific theories greatly inspire a particular invention?. The same goes with Genetic Algorithms. All of us would have heard of the famous view of Charles Darwin, “Survival of the fittest”, which extends to Evolution by Natural Selection. Inspired by Darwin’s theory, the Genetic Algorithm is a part of Evolutionary Algorithms, specifically to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover, and selection. The Genetic Algorithm can be easily applied to different applications, including Machine Learning, Data Science, Neural Networks, and Deep Learning.

This course will teach you to implement genetic algorithm-based optimization in the MATLAB environment, focusing on using the Global Optimization Toolbox. Various kinds of optimization problems are solved in this course.  At the end of this course, you will implement and utilize genetic algorithms to solve your optimization problems. The complete MATLAB programs included in the class are also available for download. This course is designed most straightforwardly to utilize your time wisely. Take advantage of learning and understanding the fast-growing field of evolutionary computation.

Happy learning.

課程章節

  • 4 個章節
  • 23 堂課
  • 第 1 章 Introduction to Optimization
  • 第 2 章 Objective of Fitness Functions
  • 第 3 章 Introduction to Genetic Algorithm
  • 第 4 章 Genetic Algorithm in MATLAB

課程內容

  • Implementation of Genetic Algorithm in MATLAB
  • Analyze the performance of the Genetic Algorithm
  • Modify or improve the Genetic Algorithm
  • Specifying objective functions
  • Specifying constraints
  • Vectorizing objective function and constraints
  • Obtaining local and global optima


評價

  • S
    Saliha Özgüngör
    1.0

    Düzeltme yapmam gerekirse oldukça yetersiz buldum. Kodları kendisi yazmıyor dahi ? Kurs başlangıcı için tanımlarım yapılması minik örneklerin verilmiş olması iyi. Akış yavaş ve örnekler yetersiz buluyorum. Umarım ilerleyen süreçlerde daha kaliteli örnekler alabilirim.

  • S
    Scott Santarelli
    5.0

    So far, so good!

  • B
    Bibhavari Bandyopadhyay
    1.0

    No clear explaination of steps. How to take input to the function and how to write a function?

  • N
    Nor Atiqah Zolpakar
    5.0

    Easy to understand

立即關注瀏覽更多

本網站使用Cookies來改善您的瀏覽體驗,請確定您同意及接受我們的私隱政策使用條款才繼續瀏覽。

我已閱讀及同意