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所在平台: Udemy |
课程主页: https://www.udemy.com/course/antcolonyoptimization/
课程评论：没有评论
课程简介：组合问题与蚁群优化算法 这门课程介绍了搜索方法和启发式算法，这是人工智能的基础技术之一。其中，蚁群优化算法被广泛认为是解决历史上一些最具挑战性问题的有效工具。课程详细讲解了该算法的相关内容，帮助学习以下概念： 第一部分： 1. 算法的主要组成部分 2. 组合优化问题的公式化 3. 组合优化问题的难度 4. 状态空间树 5. 搜索空间 6. 旅行商问题（TSP） 第二部分： 1. 精确方法 2. 启发式方法 3. 针对组合问题的暴力（穷举）算法 4. 针对组合问题的分支界限算法 5. 通过最近邻算法解决旅行商问题 第三部分： 1. 蚁群优化的灵感来源 2. 蚁群优化的数学模型 3. 蚁群优化的实现 4. 测试与分析蚁群优化的性能 5. 调整蚁群优化的参数 蚁群优化将作为主要算法，这是一种可以广泛应用于机器学习、数据科学、神经网络和深度学习等多个领域的搜索方法。 学员评价： - Fan表示：“又一门精彩的课程，非常感谢Dr Seyedali！我期待更多关于蚁群优化的应用和实例。” - Ashish说：“这门课程让我对蚁群优化有了清晰的理解，尤其是如何在MATLAB中应用。非常感谢老师设计如此有帮助的课程。” 欢迎加入100多名学员的行列，开启您的优化学习之旅。如果您在任何方面不满意，可以在30天内向Udemy申请全额退款，无需任何理由。但我相信您不会有这样的需求，我百分之百支持这门课程，并承诺将帮助您完成学习过程。
Search methods and heuristics are of the most fundamental Artificial Intelligence techniques. One of the most well-regarded of them is Ant Colony Optimization that allows humans to solve some of the most challenging problems in history. This course takes you through the details of this algorithm. The course is helpful to learn the following concepts: Part 1: 1. The main components of the 2. Formulating combinatorial optimization problems 3. Difficulty of combinatorial optimization problems 4. State space tree5. Search space 6. Travelling Salesman Problem (TSP)Part 2: 1. Exact methods 2. Heuristics methods 3. Brute-force (exhaustive) algorithm to solve combinatorial problems 4. Branch and bound algorithm to solve combinatorial problems 5. The nearest neighbour to solve the Travelling Salesman Problem Part 3: 1. Inspirations of the Ant Colony Optimization (ACO) 2. Mathematical models of the Ant Colony Optimization 3. Implementation of the Ant Colony Optimization 4. Testing and analysing the performance of the Ant Colony Optimization 5. Tuning the parameter of the Ant Colony Optimization Ant Colony Optimization will be the main algorithm, which is a search method that can be easily applied to different applications including Machine Learning, Data Science, Neural Networks, and Deep Learning. Some of the reviews are as follows: Fan said: "Another Wonderful course of Dr Seyedali，I really appreciate it！ I also look forward to more applications and examples of ACO."Ashish said: "This course clears my concept about Ant colony optimization specially with MATLAB and how to apply to our problem. Thank you so much, Sir, for design such a helpful course"Join 100+ students and start your optimization journey with us. If you are in any way not satisfied, for any reason, you can get a full refund from Udemy within 30 days. No questions asked. But I am confident you won't need to. I stand behind this course 100% and am committed to help you along the way.
