CAJ | 학술논문

在全三维粒子模拟软件CHIPIC平台上，分别开发了粒子群及基因算法模块。以相对论返波管为例，采用三种不同类型的参数（连续参数、离散参数、混合参数），对粒子群及基因算法进行比较。优化结果表明：粒子群算法的收敛速度更快，在有限的迭代步数内得到的目标结果也更优良，总体表现优于基因算法。
재전삼유입자모의연건CHIPIC평태상，분별개발료입자군급기인산법모괴。이상대론반파관위례，채용삼충불동류형적삼수（련속삼수、리산삼수、혼합삼수），대입자군급기인산법진행비교。우화결과표명：입자군산법적수렴속도경쾌，재유한적질대보수내득도적목표결과야경우량，총체표현우우기인산법。
Based on platform of three-dimensional particle-in-cell (PIC), CHIPIC, modules of particle swarm optimization ( PSO) and genetic algorithm ( GA) are designed to optimize a relativistic backward wave oscillator ( RBWO) , respectively. Comparisons of PSO and GA are implemented in three kinds of parameters of RBWO:Continuous parameter, discrete parameter, and mix parameters. It shows that performances of PSO are better than that of GA. PSO has higher optimization accuracy and convergence rate than GA.