摘要
针对影响高性能混凝土强度的主要因素作为输入因子,28 d抗压强度作为输出变量,应用遗传规划理论(GP)建立了高性能混凝土强度预测的非线性显式数学解析式模型。为了更好地保持进化过程中的遗传多样性,提高求解此问题的效率,提出了多重群体遗传规划理论。通过实测数据进行验证,并分别与线性回归模型和神经网络模型相比较,结果表明,多重群体遗传规划(MGGP)模型具有更高的拟合精度和更好的预测效果,在高性能混凝土强度预测方面有很强的实用价值。
The main factors that influence the strength of high performance concrete are considered as input variables of genetic programming（GP） model and 28-day compressive strength is seen as output variable.A visible nonlinear-mathematical-model of high performance concrete strength is given by applying the method of improved GP,in which creating initial population and fitness function are adjusted aiming at the special problem.In order to keep the variety and improve the efficiency,Multi-Group GP（MGGP） is put forward.The performance of the proposed MGGP model is analysed and the result of it is compared with that of the linear regression and BP neural network model which show that the MGGP model have higher fitting precision with the experiment data and better prediction effect,thus,the proposed MGGP model is useful to be used to predict the strength of high performance concrete.
出处
《四川建筑科学研究》
北大核心
2011年第4期210-212,215,共4页
Sichuan Building Science
基金
河北省自然基金(No.E2010000802)
关键词
遗传规划
高性能混凝土
强度预测
多重群体
genetic programming
high performance concrete
strength forecast
Multi-Group
