首页> 外文期刊>Engineering Applications of Artificial Intelligence >Multi-objective optimization of two stage thermoelectric cooler using a modified teaching-learning-based optimization algorithm
【24h】

Multi-objective optimization of two stage thermoelectric cooler using a modified teaching-learning-based optimization algorithm

机译:基于改进的基于学习的优化算法的二级热电冷却器的多目标优化

获取原文
获取原文并翻译 | 示例
           

摘要

Teaching-learning-based optimization (TLBO) is a recently developed heuristic algorithm based on the natural phenomenon of teaching-learning process. In the present work, a modified version of the TLBO algorithm is introduced and applied for the multi-objective optimization of a two stage thermoelectric cooler (TEC). Two different arrangements of the thermoelectric cooler are considered for the optimization. Maximization of cooling capacity and coefficient of performance of the thermoelectric cooler are considered as the objective functions. An example is presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization obtained by using the modified TLBO are validated by comparing with those obtained by using the basic TLBO, genetic algorithm (GA), particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms.
机译:基于教学的优化(TLBO)是基于教学过程的自然现象而开发的一种启发式算法。在当前工作中,引入了TLBO算法的修改版本,并将其应用于两级热电冷却器(TEC)的多目标优化。为了优化,考虑了热电冷却器的两种不同布置。热电冷却器的冷却能力和性能系数的最大化被视为目标函数。给出了一个例子来证明所提算法的有效性和准确性。通过与使用基本TLBO,遗传算法(GA),粒子群优化(PSO)和人工蜂群(ABC)算法获得的结果进行比较,验证了使用改进的TLBO获得的优化结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号