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Combinatorial Development of Solid Catalytic Materials. Design of High Throughput Experiments, Data Analysis, Data Mining
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SYSNO ASEP 0334675 Druh ASEP B - Monografie Zařazení RIV B - Odborná monografie, kniha Název Combinatorial Development of Solid Catalytic Materials. Design of High Throughput Experiments, Data Analysis, Data Mining Tvůrce(i) Baerns, M. (DE)
Holeňa, Martin (UIVT-O) SAI, RIDVyd. údaje London: Imperial College Press, 2009 ISBN 978-1-84816-343-0 Edice Catalytic Science Series Č. sv. edice 7 Poč.str. 178 s. Poč.výt. 1400 Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova combinatorial catalyst design ; high-throughput experimentation ; computer-aided materials search ; catalyst design ; combinatorial computational chemistry ; data mining ; data analysis ; genetic algorithms ; artificial neural networks Vědní obor RIV IN - Informatika CEP GA201/08/0802 GA ČR - Grantová agentura ČR GA201/08/1744 GA ČR - Grantová agentura ČR GEICC/08/E018 GA ČR - Grantová agentura ČR CEZ AV0Z10300504 - UIVT-O (2005-2011) DOI https://doi.org/10.1142/9781848163447_fmatter Anotace 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 describes evolutionary optimization in the context of methods of searching for optimal catalytic materials, including statistical design of experiments, and neural networks in the 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 automatic generating of problem-tailored genetic algorithms, and tuning evolutionary algorithms with neural networks. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2010
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