Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (22): 212-217.

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Optimized GEP algorithm and its application in blasting vibration predicting

WANG Bin1, ZHANG Xun2, SHENG Jinfang1, CHEN Xin3, SHI Xiuzhi3   

  1. 1.School of Information Science and Engineering, Central South University, Changsha 410083, China
    2.School of Software, Central South University, Changsha 410083, China
    3.School of Resources and Safety Engineering, Central South University, Changsha 410083, China
  • Online:2016-11-15 Published:2016-12-02

优化的GEP算法在爆破振动预测中的应用

王  斌1,张  迅2,盛津芳1,陈  新3,史秀志3   

  1. 1.中南大学 信息科学与工程学院,长沙 410083
    2.中南大学 软件学院,长沙 410083
    3.中南大学 资源与安全工程学院,长沙 410083

Abstract: Based on Principal Component Analysis and Gene Expression Programming, an optimum GEP algorithm is proposed and applied in the prediction of blasting vibration peak value and main frequency. In this algorithm, PCA method is used to preprocess the input data, the correlation among the inputs is eliminated, and then GEP is applied to construct the prediction model. The experiment results show that this algorithm is more accurate and stable than existing prediction algorithms.

Key words: Principal Component Analysis(PCA), Gene Expression Programming(GEP), prediction;blasting vibration

摘要: 结合主成分分析和基因表达式编程,提出了一种基于PCA的优化基因表达式编程的新算法,并将其应用在爆破振动峰值速度和主频率的预测。该算法首先利用主成份分析方法对影响爆破振动的参数进行预处理,有效地减少预测模型的输入量,消除输入数据间的相关性,而后通过基因表达式程序设计建立爆破振动预测模型。结果表明,基于PCA的优化基因表达式编程算法比BP神经网络等其他算法得到的结果具有更高的预测精度和稳定性。

关键词: 主成分分析, 基因表达式编程, 预测, 爆破振动