# 蝙蝠算法

## 算法方程

${\displaystyle f_{i}=f_{\min }+(f_{\max }-f_{\min })\beta ,}$
${\displaystyle v_{i}^{t}=v_{i}^{t}+(x_{i}^{t-1}-x_{*})f_{i},}$
${\displaystyle x_{i}^{t}=x_{i}^{t-1}+v_{i}^{t}.}$

A和r应该在迭代中变换：

${\displaystyle A_{i}^{t+1}=\alpha A_{i}^{t},}$
${\displaystyle r_{i}^{t+1}=r_{i}^{0}[1-\exp(-\gamma t)].}$

## 參考文獻

1. ^ X. S. Yang, A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010), Studies in Computational Intelligence, Springer Berlin, 284, Springer, 65-74 (2010). http://arxiv.org/abs/1004.4170
2. ^ J. D. Altringham, Bats: Biology and Behaviour, Oxford University Press, (1996).
3. ^ P. Richardson, Bats. Natural History Museum, London, (2008)
4. ^ X. S. Yang and A. H. Gandomi, Bat algorithm: a novel approach for global engineering optimization, Engineering Computations, Vol. 29, No. 5, pp. 464-483 (2012).
5. ^ S. Mishra, K. Shaw, D. Mishra, A new metaheuristic classification approach for microarray data,Procedia Technology, Vol. 4, pp. 802-806 (2012).
6. ^ K. Khan and A. Sahai, A comparison of BA, GA, PSO, BP and LM for training feed forward neural networks in e-learning context, Int. J. Intelligent Systems and Applications (IJISA), Vol. 4, No. 7, pp. 23-29 (2012).

## 延伸閱讀

• 蝙蝠算法的详细的介绍：Yang, X. S., Nature-Inspired Metaheuristic Algoirthms, 2nd Edition, Luniver Press, (2010).
• Matlab/Octave程序