no code implementations • 2 Dec 2021 • Haiquan Wang, Hans-DietrichHaasis, Panpan Du, Xiaobin Xu, Menghao Su, Shengjun Wen, Wenxuan Yue, Shanshan Zhang
As an effective algorithm for solving complex optimization problems, artificial bee colony (ABC) algorithm has shown to be competitive, but the same as other population-based algorithms, it is poor at balancing the abilities of global searching in the whole solution space (named as exploration) and quick searching in local solution space which is defined as exploitation.
no code implementations • 1 Dec 2021 • Haiquan Wang, Wenxuan Yue, Shengjun Wen, Xiaobin Xu, Menghao Su, Shanshan Zhang, Panpan Du
Moreover, XGBoost is used to recognize the faults from the obtained features, and an improved artificial bee colony algorithm(ABC) where the evolution is guided by the importance indices of different search space is proposed to optimize the parameters of XGBoost.