Experimental Research in Evolutionary Computation
Thomas Bartz-Beielstein
Reading Time
at 250 WPM3h 49m
The average reader, reading at a speed of 250 WPM, would take 3h 49m to read Experimental Research in Evolutionary Computation.
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229
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Experimental Research in Evolutionary Computation
Published
2010
Publisher
Springer Berlin / Heidelberg
Pages
229
ISBN-13
9783642068737
Description
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 results from the author's consulting to industry and his experience teaching university courses and conducting tutorials at international conferences. The book will be supported online with downloads and exercises.
Subjects
Evolutionary Computation in Combinatorial Optimization Lecture Notes in Computer Science Theoretical Computer Sci
Applications of Evolutionary Computation Evoapplications 2010 Lecture Notes in Computer Science Theoretical Computer Sci
Swarm Evolutionary and Memetic Computing Lecture Notes in Computer Science
Computational Intelligence
Foundations of Software Technology and Theoretical Computer Science
Genetic and Evolutionary Computing
Frequently Asked Questions
How many pages are in Experimental Research in Evolutionary Computation?
This edition of Experimental Research in Evolutionary Computation has approximately 229 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Experimental Research in Evolutionary Computation?
For most readers, Experimental Research in Evolutionary Computation typically takes between 4h 46m and 3h 11m to complete. This is based on the book's length of approximately 57,250 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 3h 49m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 8 days • Estimated word count: 57,250 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Experimental Research in Evolutionary Computation?
The estimated word count for Experimental Research in Evolutionary Computation is approximately 57,250 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Experimental Research in Evolutionary Computation?
Experimental Research in Evolutionary Computation was written by Thomas Bartz-Beielstein.
When was Experimental Research in Evolutionary Computation published?
The publication date for this specific edition is 2010. The original work may have been published on a different date.