Gerçek Kodlu Genetik Algoritma ile Optimum Geçiş Sürelerinin Hesaplanması

Elektron enerjisi analizörleri, belirli enerjilerdeki yüklü parçacık ışınlarını analiz etmek için tasarlanmıştır. Tasarım, farklı enerjilerdeki elektronların dedektöre farklı zamanlarda ulaşması prensibine dayanmaktadır. Farklı enerjilere sahip elektronlar bu analizörlerde farklı yörüngeler takip ettiğinden. Çarpışma deneylerinde yüklü parçacıkların analizördeki yörüngelerinin ve geçiş sürelerinin belirlenmesi çok önemlidir. Bu çalışmada, yüklü parçacıkların geçiş süreleri için gerçek kodlu bir genetik algoritma kullanılarak optimum çözümler sağlanmıştır. Bu çalışmada hiper parametreler ve genetik algoritma türleri deneme yanılma yöntemleri kullanılarak elde edilmiştir. Bu çalışmanın sonuçları, genetik algoritmanın geniş bir veri kümesinde zaman çözünürlük değerlerini yüksek doğrulukla verdiğini göstermektedir. Sonuçlar, genetik algoritmaların (GA) arama ve optimizasyon problemlerini çözmek için ilgi çekici bir yaklaşım olduğunu göstermektedir.

Anahtar Kelimeler:

Elektron spektroskopisi, elektron demeti, enerji analizörü, genetik algoritma.

Calculation of Optimum Transit Times with Real-Coded Genetic Algorithm

Electron energy analysers have been designed to analyse charged-particle beams at specific energies. The design is based on the principle that electrons with different energies arrive at the detector at different times. Since electrons with different energies follow different orbits within these analysers. In collision experiments, it is very important to determine the trajectories and transit times of the charged particles in the analyser. In this study, optimum solutions for transit times of charged particles were provided using a real-coded genetic algorithm. Hyper parameters and types of genetic algorithm were obtained using trial and error methods, in this study. The results of this study indicate that genetic algorithm gives time resolution values in a wide data set with high accuracy. The results show that genetic algorithms (GA) are a fascinating approach for solving search and optimization problems.

Keywords:

Electron spectroscopy, electron beam, energy analyser, genetic algorithm.,

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