摘要： 人工蜂群(ABC)算法易陷入局部极小点，搜索精度不高且算法收敛速度慢。为此，提出一种改进的混沌蜜蜂群(CBC)算法，修改ABC算法的食物源位置更新公式，引入混沌搜索机制进行局部搜索。将CBC算法应用于瓦斯突出预测中，建立神经网络预测模型，实验结果证明了该模型的有效性。

关键词: 混沌蜜蜂群算法, 人工蜂群算法, 混沌搜索, 瓦斯突出预测

Abstract: Artificial Bee Colony(ABC) algorithm has some drawbacks such as getting in local minima, searching accuracy is not high and convergence rate is slow. This paper presents a Chaos Bee Colony(CBC) algorithm with a new formula to replace the standard food source position updating formula of ABC, and chaotic search mechanism is introduced to the bee swarm local search. Performance analysis shows that CBC algorithm has faster convergence rate, more global search capability. The algorithm is introduced into the construction of gas outburst prediction model, experimental results prove the validity of the model.

Key words: Chaos Bee Colony(CBC) algorithm, Artificial Bee Colony(ABC) algorithm, chaotic search, gas outburst prediction

中图分类号: 

• TP273