算法
计算机科学
测试套件
回溯
启发式
分割
帝国主义竞争算法
混合算法(约束满足)
元启发式
图像分割
数学优化
元优化
人工智能
模式识别(心理学)
数学
测试用例
机器学习
回归分析
概率逻辑
约束满足
约束逻辑程序设计
作者
Debao Chen,Yuanyuan Ge,Yujie Wan,Yu Deng,Yuan Chen,Feng Zou
标识
DOI:10.1016/j.eswa.2022.117118
摘要
• The POA algorithm mimics the sexual and asexual propagation mechanism of poplar. • The performance of POA is tested on two test suites with different features. • POA is used to find optimal thresholds for image segmentation. • The results indicate that POA is competitive and has its superiority in some cases. A novel algorithm called Poplar Optimization Algorithm (POA) is developed in this paper to solve continuous optimization problems. The algorithm mimics the sexual and asexual propagation mechanism of poplar, where the basic philosophy of how to execute sexual and asexual propagation for individuals is detail designed in the algorithm. Mutation strategy of backtracking search algorithm is adopted in POA to maintain the diversity in a certain degree. The performance of POA algorithm is tested on 25 functions from the CEC2005 test suite and 30 functions from the CEC2017 test suite with different features. The results of POA are compared with some other population-based algorithms in terms of the quality and efficiency. Finally, the proposed algorithm is used to find the optimal threshold for image segmentation. The results indicate that the poplar optimization algorithm can obtain competitive or superior performance.
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