Zhou Yongquan, Xie Jian, Li Liangliang, Ma Mingzhi
College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, Guangxi 530006, China.
ScientificWorldJournal. 2014;2014:237102. doi: 10.1155/2014/237102. Epub 2014 May 19.
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization.
蝙蝠算法（BA）是一种新型的随机全局优化算法。云模型是实现定性概念与其定量表示之间转换的有效工具。基于蝙蝠回声定位机制以及云模型在不确定性知识表示方面的优异特性，提出了一种新的云模型蝙蝠算法（CBA）。本文着重基于蝙蝠的生存和捕食特性对回声定位模型进行重塑，利用云模型的转换理论来描述定性概念：“蝙蝠接近其猎物”。此外，引入了蝙蝠的 Lévy 飞行模式和种群信息通信机制，以平衡探索和利用之间的优势。仿真结果表明，云模型蝙蝠算法在函数优化方面具有良好的性能。
