欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
文章基于同步振子 Kuramoto 模型，提出了影响力传动的 Kuramoto 股市趋势预测模型（IT-KFM ）。IT-KFM 模型运用贝叶斯网络构建振子之间的结构关系，引入影响力传动，给出传动因子量化方法，将传动因子的传动参数加入到原 Kuramoto 模型中，进而根据不同振子间相位协方差的趋势变化分析和预测股市趋势，实验结果证明，IT-KFM 算法相对于标准的 SVM 网络，在股票的走势预测方面有较好的预测效果。
英文摘要：
Based on the synchronous vibrator Kuramoto model ,a stock market trends forecasting model with influence transmission （IT-KFM ） is presented .In IT-KFM algorithm ,Bayesian network is uti-lized to build the structural relationships between the oscillators ,and the influence transmission is in-troduced .Then the quantitative method of transmission factor is given ,and the transmission parame-ters of transmission factor are added to the original Kuramoto model .Finally ,the stock market trends are analyzed and forecasted according to the trend change of the covariance between different oscillator phases .The experimental results show that the performance of the proposed method is better than the standard SVM algorithm in stock trend forecast .
同期刊论文项目
同项目期刊论文
期刊信息
位置：