关键词: 股票价格, 预测, 果蝇优化算法, 极限学习机

Abstract: Extreme Learning Machine（ELM） is not stable in predicting stock price. To address the problem, this paper proposes an Improved Fruit Fly of Algorithm（IFOA） that optimizes ELM by improving fruit fly. In the algorithm, fruit fly swarm constantly adjusts its radius to optimize the ELM input weights and thresholds of hidden layer, building an ELM prediction model with the optimized results. The IFOA-ELM model proposed in this paper can be applied to predicting stock price. Compared with ELM and FOA-ELM, IFOA-ELM model is more accurate and stable in predicting stock price.

Key words: stock price, prediction, Fruit Fly of Algorithm（FOA）, Extreme Learning Machine（ELM）