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Comparison of Genetic Programing, Radial Basis Function Network and Polynomial Equation Used for Response Surface Method for Catalyst Optimization
Genetic programing Cobalt-magnesia catalyst Methane dry reforming
2009/8/4
Preparation conditions of Co-MgO catalyst for methane dry reforming were optimized to maximize the CO yield. Response surface method, composed of design of experiment and regression method, was appli...
Improved Ultrasonic Offshore Oil Pipeline Thickness Accurate Detection Using Hilbert-Huang Transform and Elman Neural Network
Elman neural network Hilbert-Huang transform Feature extraction
2009/7/27
Pipeline flaw detection and safety evaluation are very important because of internal corrosion usually caused by the presence of the water (salty or not), and external damage by anchors or other equip...
Screening Using Artificial Neural Network of Additives for Cu-Zn Oxide Catalyst for Methanol Synthesis from Syngas
Methanol synthesis Neural network Physicochemical property
2009/7/24
The activity of Cu-Zn oxide catalysts for methanol synthesis from syngas varies depending on the additives to the oxide, and optimum composition is sensitive to the reaction conditions. An artificial ...
Development of a Co-MgO Catalyst for High-pressure Dry Reforming of Methane Based on Design of Experiment, Artificial Neural Network and Grid Search
Methane dry reforming Combinatorial catalysis Design of experiment
2009/7/24
Dry reforming of methane is a potentially important process to convert the greenhouse gases carbon dioxide and methane simultaneously to syngas (CO + H2). The most serious problem with the dry reform...
Design of Cu-Zn-Al-Sc Oxide Catalyst for Methanol Synthesis Using Genetic Algorithm Based on Radial Basis Function Network as the Evaluation Function
Combinatorial chemistry High throughput screening Genetic algorithm
2009/7/24
Optimization of catalyst composition using a genetic algorithm (GA) is intended to increase the activity in a series of repetitive steps consisting of determination of the composition, catalyst prepa...
Optimization of Cu-based Oxide Catalyst for Methanol Synthesis Using a Neural Network Trained by Design of Experiment
Combinatorial chemistry High-throughput screening Neural network
2009/7/23
Cu-Zn oxide catalyst for methanol synthesis was optimized using an activity map by neural network method. The catalyst composition was determined randomly and the training data were measured in a hig...
Optimization of Cu-based Oxide Catalyst for Methanol Synthesis by the Activity Map Envelope Derived from a Neural Network
Combinatorial chemistry High-throughput screening Genetic algorithm
2009/7/23
The combinatorial approach is a successful tool for material development and for heterogeneous catalyst development. Combinatorial tools were developed consisting of a high-throughput screening react...