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Combinatorial Development Of Solid Catalytic Materials: Design Of High-throughput Experiments, Data Analysis, Data Mining

Autor: Manfred Baerns, Martin Hole

Język:

Oprawa: Twarda

Wydawca: Imperial College Press

Dostępność: Dostępna u dostawcy

Wysyłamy za 9-15 dni

436.70 zł

The book provides a comprehensive treatment of combinatorial development of heterogeneous catalysts....

Informacje o książce

Autor

Manfred Baerns, Martin Hole

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2009

strony

192

EAN

9781848163430

ISBN

1848163436

Enbook ID

05103263

Wydawca

Imperial College Press

Waga

502

Wymiary

159 x 236 x 16

Pełny opis

The book provides a comprehensive treatment of combinatorial development of heterogeneous catalysts. In particular, two computer-aided approaches that have played a key role in combinatorial catalysis and high-throughput experimentation during the last decade - evolutionary optimization and artificial neural networks - are described. The book is unique in that it describes evolutionary optimization in a broader context of methods of searching for optimal catalytic materials, including statistical design of experiments, as well as presents neural networks in a broader context of data analysis.It is the first book that demystifies the attractiveness of artificial neural networks, explaining its rational fundamental - their universal approximation capability. At the same time, it shows the limitations of that capability and describes two methods for how it can be improved. The book is also the first that presents two other important topics pertaining to evolutionary optimization and artificial neural networks: automatic generating of problem-tailored genetic algorithms, and tuning evolutionary algorithms with neural networks. Both are not only theoretically explained, but also well illustrated through detailed case studies.