Improved Automeshing Using the Genetic Algorithm

Autor: Chi-Chung Chang, 張啟仲
Rok vydání: 2003
Druh dokumentu: 學位論文 ; thesis
Popis: 91
When we use the FDTD method to analyze electromagnetic problems, it has to properly discretize the space and time. Automeshing can non-uniformly discretize the simulated structure and generate gradual grids. To improve the efficiency of automeshing, we optimize the parameter of automeshing using the genetic algorithm. Without sacrificing accuracy, it searches a suitable ratio to reduce the generated grids and to save simulation time. At last, we optimize the PIFA using genetic algorithm and search automatically the height of the substrate and the feed position in order to obtain optimal performance. When we use the genetic algorithm, it is the key point to define an objective function evaluating the fitness of the optimized problem. It is important that the function has to appropriately describe the performance at that time.
Databáze: Networked Digital Library of Theses & Dissertations