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Improved Automeshing Using the Genetic Algorithm

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.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0721103-170738
Date21 July 2003
CreatorsChang, Chi-Chung
ContributorsChih-Wen Kuo, Tzyy-Sheng Horng, Tzong-Lin Wu, Ken-Huang Lin
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721103-170738
Rightsoff_campus_withheld, Copyright information available at source archive

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