中图分类号： TP391.9
文献标识码： A
DOI：10.16157/j.issn.0258-7998.211532
中文引用格式： 刘新建，孙中华. 狮群优化核极限学习机的分类算法[J].电子技术应用，2022，48(2)：69-72.
英文引用格式： Liu Xinjian，Sun Zhonghua. Classification algorithm of loin swarm optimization kernel extreme learning machine[J]. Application of Electronic Technique，2022，48(2)：69-72.

Classification algorithm of loin swarm optimization kernel extreme learning machine

Abstract： Based on the classification and application of the kernel based extreme learning machine(KELM)，combined with the strong global optimization ability and fast convergence characteristics of the lion swarm optimization(LSO) algorithm, an LSO optimization KELM algorithm is proposed. The test accuracy is taken as the fitness function of LSO to optimize KELM, and the evaluation standard for data classification test is obtained according to the mobile position to obtain the optimal fitness value. Using UCI data set simulation test, the experimental results show that compared with KELM classification, LSO optimization KELM can obtain better classification accuracy. Compared with sparrow search algorithm(SSA) optimization KELM, LSO optimization KELM has faster convergence speed and better classification performance.

Key words : kernel extreme learning machine(KELM)；lion swarm optimization(LSO)；sparrow search algorithm(SSA)