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所在平台: Udemy |
课程主页: https://www.udemy.com/course/metaheuristic-optimization-techniques-with-matlab/
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课程名称：Matlab中的启发式优化技术 课程概述：本课程是优化技术入门的理想选择。如果您熟悉Matlab或Python，并希望学习如何为任何问题找到最佳解决方案，那么本课程非常适合您。在课程的开始，我们将介绍优化的基本概念，随后探讨广度优先搜索（BFS）和深度优先搜索（DFS），这两者在路径规划中至关重要。接下来，我们将深入学习模拟退火（SA）、遗传算法（GA）、粒子群优化（PSO）和蚁群优化（ACO）。在掌握这些技术后，我们将学习如何在Matlab中应用它们。课程中每两节课后都有小测验，以测试您对每个主题的理解，最后将进行一次包含25道题的考试，以评估您对课程内容的掌握程度以及能否运用这些优化技术解决实际问题。本课程适合任何希望学习优化并寻找最佳解决方案的人，尤其在某些人工智能应用和自主系统中，优化技术是非常重要的，因此本课程将为您的未来打开许多机会。课程共分为10节课，内容包括：1) 优化简介；2) 确定性技术（BFS和DFS）；3) 模拟退火（SA）；4) 遗传算法（GA）；5) 粒子群优化（PSO）；6) 蚁群优化（ACO）；7) 在Matlab中实现SA；8) 在Matlab中实现GA；9) 在Matlab中实现ACO；10) 在Matlab中实现PSO，以及11) 最终考试。 通过本课程，学员将获得坚实的优化基础，并能够运用所学技术解决各种实际问题。
This course is your introduction to the world of optimization techniques. If you know Matlab or pythons and want to learn how to find the best solution for any problem then this course is for you.In this course, we will start with an introduction to the world of optimization then we will take the Breadth First Search and Depth First Search which are very important for path planning. Then we will dive into Simulated Annealing, the genetic algorithm, Particle Swarm Optimization and Ant Colony Optimization. After understanding them all we will see how to use them on Matlab. This is all done with quizzes after each two lectures to test your understanding for each topic and at the end of the course you will get an exam to test how much you understood the course and whether you can use these optimization techniques to solve any problem.The course is important for anyone who wants to learn optimization and how to find the best solution for any problem. Optimization is very important for some artificial intelligence applications and in autonomous systems so this course will open lots of doors for you in the future. The course is divided into 10 lectures 1) Introduction where you will get to know more about optimization and its different types2) Deterministic techniques which are BFS and DFS3) SA4) GA5) PSO6) ACO7) Matlab for SA8) Matlab for GA9) Matlab for ACO10) Matlab for PSO11) final Exam of 25 questions
