Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Programming Perl
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
LabVIEW for Everyone with Cdrom
LabVIEW for Everyone with Cdrom
Introduction to the Theory of Neural Computation
Introduction to the Theory of Neural Computation
Learning to be selective in genetic-algorithm-based design optimization
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
On a data-driven environment for multiphysics applications
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
On a data-driven environment for multiphysics applications
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
A novel sequential design strategy for global surrogate modeling
Winter Simulation Conference
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Engineering design optimization using concurrent integrated experiment and simulation is a Dynamic Data Driven Application System (DDDAS) wherein remote experiment and simulation can be synergistically utilized in real-time to achieve better designs in less time than conventional methods. The paper describes the Data Driven Design Optimization Methodology (DDDOM) being developed for engineering design optimization.