Estimation of catalytic performance by neural network — product distribution in oxidative dehydrogenation of ethylbenzene
Authors:
- Shigeharu KiteSKShigeharu Kite
- Tadashi HattoriTHTadashi Hattori
- Yuichi MurakamiYMYuichi Murakami
- 1 July 1994
- journal article
- Published by Elsevier in Applied Catalysis A: General
- Vol. 114 (2) , L173-L178
Abstract
No abstract availableKeywords
This publication has 9 references indexed in Scilit:
- Prediction of carbon-13 nuclear magnetic resonance chemical shifts by artificial neural networksAnalytical Chemistry, 1992
- Estimation of the acid strength of mixed oxides by a neural networkIndustrial & Engineering Chemistry Research, 1992
- Artificial intelligence approach to catalyst designCatalysis Today, 1991
- Neural networks: A new method for solving chemical problems or just a passing phase?Analytica Chimica Acta, 1991
- DETERMINATION OF SYNERGISTICALLY GENERATED ACID STRENGTH BY NEURAL NETWORK COMBINED WITH EXPERIMENTAnalytical Sciences, 1991
- An expert systems approach to computer-aided design of multi-component catalystsChemical Engineering Science, 1990
- Performance of promoted SnO2 catalysts designed by an expert systems approach for oxidative dehydrogenation of ethylbenzeneApplied Catalysis, 1989
- Expert systems approach to computer-aided design of catalystsApplied Catalysis, 1989
- Integration of Catalyst Activity Pattern (INCAP) Artificial Intelligence Approach in Catalyst DesignChemistry Letters, 1988