experimental research evolutionary computation de bartz beielstein thomas (34 résultats)

Hardcover. Etat : Wie neu. 229 S., Like new. Shrink wrapped. / Wie neu. In Folie verschweißt. Sprache: Englisch Gewicht in Gramm: 610.

Etat : New. pp. 232.

Etat : New. pp. 232.

Etat : New. pp. 232 66 Illus.

Etat : New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.

Etat : New. In.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch.

Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Etat : New. pp. 232.

Etat : As New. Unread book in perfect condition.

Etat : New.

Paperback. Etat : Brand New. 228 pages. 9.00x6.00x0.52 inches. In Stock.

Etat : New. In.

Etat : New.

Etat : New.

Paperback. Etat : new. Paperback. 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. This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Etat : new. Hardcover. 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. Introduces the experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. This book develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Etat : new. Paperback. 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. This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Etat : new. Hardcover. 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. Introduces the experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. This book develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

hardcover. Etat : New. In shrink wrap. Looks like an interesting title!

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 author is very well positioned to address this gap given h.

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 author is very well positioned to address this gap given h.