By Manfred Baerns, Martin Holena
The ebook offers a complete therapy of combinatorial improvement of heterogeneous catalysts. specifically, computer-aided ways that experience performed a key function in combinatorial catalysis and high-throughput experimentation over the last decade - evolutionary optimization and synthetic neural networks - are defined. The ebook is exclusive in that it describes evolutionary optimization in a broader context of equipment of attempting to find optimum catalytic fabrics, together with statistical layout of experiments, in addition to offers neural networks in a broader context of knowledge analysis.It is the 1st e-book that demystifies the popularity of synthetic neural networks, explaining its rational basic - their common approximation strength. whilst, it exhibits the restrictions of that potential and describes tools for the way it may be enhanced. The publication is usually the 1st that offers different very important subject matters relating evolutionary optimization and synthetic neural networks: automated producing of problem-tailored genetic algorithms, and tuning evolutionary algorithms with neural networks. either aren't in basic terms theoretically defined, but additionally good illustrated via targeted case reviews.
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Extra resources for Combinatorial Development of Solid Catalytic Materials: Design of High-Throughput Experiments, Data Analysis, Data Mining (Catalytic Science
Multi-objective optimization in catalytical chemistry applied to the selective catalytic reduction of NO with C3H6, J. , 252, 205–214. C. and Schüth, F. (2008). On the suitability of different representations of solid catalysts for combinatoral library design by genetic algorithms, J. Comb. , 10, 835–846. Goldberg, D. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, 412 p. , van Geem, P. and Parton, R. (2003). Fundamental insights into the oxidative dehydrogenation of ethane to ethylene over catalytic materials discovered by an evolutionary approach, Catal.
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