Optimization Learning Algorithms And Applications
Download Optimization Learning Algorithms And Applications PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Optimization Learning Algorithms And Applications book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Optimization, Learning Algorithms and Applications
This two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in July 2024. The 41 papers presented here were carefully reviewed and selected from 105 submissions. They have been organized in the two volumes under the following topical sections:- Part I: Learning Algorithms in Engineering Education; Machine Learning; Deep Learning; Optimization in the SDG context. Part II: Optimization in Control Systems Design; Optimization.
Optimization in Machine Learning and Applications
This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
Teaching Learning Based Optimization Algorithm
Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.