CAJ | 학술논문

针对标准遗传算法在对城市空间增长分析时还存在精度不高、误差较大等问题，提出了一种基于种群优化遗传算法的城市空间增长分析模型，该模型在标准遗传算法的基础上，首先采用动态自适应调整策略对原算法遗传算子中的交叉算子和变异算子进行优化，然后引入蚁群算法，利用小生境方法限制种群个体的繁衍，以达到种族多样化的优化。仿真试验结果表明，本文提出的基于种群优化遗传算法的城市空间增长分析模型相对于标准遗传算法，其精度得到了很大的提升，降低了城市空间增长预测的误差。
침대표준유전산법재대성시공간증장분석시환존재정도불고、오차교대등문제，제출료일충기우충군우화유전산법적성시공간증장분석모형，해모형재표준유전산법적기출상，수선채용동태자괄응조정책략대원산법유전산자중적교차산자화변이산자진행우화，연후인입의군산법，이용소생경방법한제충군개체적번연，이체도충족다양화적우화。방진시험결과표명，본문제출적기우충군우화유전산법적성시공간증장분석모형상대우표준유전산법，기정도득도료흔대적제승，강저료성시공간증장예측적오차。
For standard genetic algorithm to analyze the growth of urban space exists Shihai accuracy is not high, large errors and other issues, this paper presents a growth model based on analysis of population genetic algorithm optimization of urban space, the model on the basis of the standard genetic algorithm, first, the use of dynamic adaptive strategy for the original operator of the genetic algorithm crossover and mutation operator to optimize, and then introduced into the ant colony algorithm, limiting the proliferation of the population of individuals using a niche approach to optimize ethnic diversity. Simulation results show that the proposed optimization genetic algorithm based on population growth in urban space analysis model relative to the standard genetic algorithm, its accuracy has been greatly improved, reducing the urban space growth forecast error.