A dandelion algorithm (DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA, which might not be appropriate for all optimization problems. A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure. Only the normal sowing operator is retained; while the other operators are discarded. An adaptive seeding radius strategy is designed for the core dandelion. The results show that the proposed algorithm achieves better performance on the standard test functions with less time consumption than its competitive peers. In addition, the proposed algorithm is applied to feature selection for credit card fraud detection (CCFD), and the results indicate that it can obtain higher classification and detection performance than the-state-of-the-art methods.

中文翻译：

---

一种自适应高效蒲公英算法及其在信用卡欺诈检测特征选择中的应用

蒲公英算法（DA）是最近发展起来的一种针对函数优化问题的智能优化算法。它的许多参数需要根据DA经验来设置，这可能并不适合所有优化问题。本文提出了一种自适应高效的蒲公英算法，以减少DA的参数数量并简化DA的结构。只保留正常播种操作员；而其他运算符则被丢弃。针对核心蒲公英设计了自适应播种半径策略。结果表明，所提出的算法在标准测试功能上取得了更好的性能，并且比竞争对手的算法消耗更少的时间。此外，该算法应用于信用卡欺诈检测（CCFD）的特征选择，结果表明它可以获得比最先进的方法更高的分类和检测性能。