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Honey Bees Inspired Learning Algorithm: Nature Intelligence Can Predict Natural Disaster

机译:蜜蜂灵感学习算法:自然智能可以预测自然灾害

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Artificial bee colony (ABC) algorithm which used the honey bee intelligence behaviors, is a new learning technique comparatively attractive for solving optimization problems. Artificial Neural Network (ANN) trained with the ABC algorithm normally has poor exploration and exploitation processes due to the random and similar strategies for finding best position of foods. Global artificial bee colony (Global ABC) and Guided artificial bee colony (Guided ABC) algorithms used to produce enough exploitation and exploration strategies respectively. Here, a hybrid of Global ABC and Guided ABC is proposed called Global Guided ABC (GG-ABC) algorithm, for getting balance and robust exploitation and exploration process. The experimental result shows that the GG-ABC performed better than other algorithms for prediction of earthquake hazards.
机译:使用蜂蜜蜂智能行为的人造蜜蜂殖民地(ABC)算法是一种新的学习技术,对解决优化问题相对吸引力。由于ABC算法培训的人工神经网络(ANN)通常具有较差的勘探和剥削过程,因为寻找食物最佳位置的随机和类似的策略。全球人造蜂殖民地(全球ABC)和引导人工蜂殖民地(引导ABC)算法用于分别产生足够的利用和勘探策略。这里,提出了全球ABC和引导ABC的混合动力,称为全球指导ABC(GG-ABC)算法,以获得平衡和鲁棒利用和探索过程。实验结果表明,GG-ABC比其他算法更好地进行,用于预测地震危害。

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