| 书目名称 | Experimental Research in Evolutionary Computation | | 副标题 | The New Experimental | | 编辑 | Thomas Bartz-Beielstein | | 视频video | | | 概述 | There are no directly competing books that combine modern statistical approaches and evolutionary computing approaches in the design of experiments and the solution to optimization problems, and the a | | 丛书名称 | Natural Computing Series | | 图书封面 |  | | 描述 | .Experimentation is necessary - a purely theoretical approach is not reasonable. The new experimentalism, a development in the modern philosophy of science, considers that an experiment can have a life of its own. It provides a statistical methodology to learn from experiments, where the experimenter should distinguish between statistical significance and scientific meaning. ..This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. The book develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. Treating optimization runs as experiments, the author offers methods for solving complex real-world problems that involve optimization via simulation, and he describes successful applications in engineering and industrial control projects...The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples, so it is suitable for practitioners and researchers and also for lecturers and students. It summarizes res | | 出版日期 | Book 2006 | | 关键词 | Performance; algorithm; algorithms; evolution; evolutionary algorithm; evolutionary computation; heuristic | | 版次 | 1 | | doi | https://doi.org/10.1007/3-540-32027-X | | isbn_softcover | 978-3-642-06873-7 | | isbn_ebook | 978-3-540-32027-2Series ISSN 1619-7127 Series E-ISSN 2627-6461 | | issn_series | 1619-7127 | | copyright | Springer-Verlag Berlin Heidelberg 2006 |
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发表于 2025-3-21 18:55:36
