小波神经网络预测混凝土强度研究

STUDY ON PREDICTION OF CONCRETE STRENGTH USING WAVELET NEURAL NETWORK

1.
1. College of Traffic and Transportation Engineering,Southeast University Nanjing 210096;
2.
2. Jiangsu Architectural Research Institute Nanjing 210008

摘要: 小波神经网络是将小波理论和神经网络理论结合起来的一种神经网络，它避免了BP神经网络结构设计的盲目性和局部最优等非线性优化问题，大大简化了训练，具有较强的函数学习能力和推广能力及广阔的应用前景。小波神经网络用于混凝土强度预测的结果表明，它比传统的BP神经网络的收敛速度快，预测精度高。
- 小波神经网络 /
- 混凝土 /
- 强度预测
Abstract: Wavelet neural network is a kind of neural networks, which can closely combine wavelet theory with neural network theory, and avoid the blindness of framework designs for BP neural networks and the problem of nonlinear optimizations, such as local optimization.So it can greatly simplify the training of neural networks.It has good abilities of function learning and dissemination with a vast range of prospects for application.In this paper, the wavelet neural network is applied to predict the strength of concrete.The results show that the convergence speed of wavelet neural network is faster and its predicting result is more accurate than that of BP network
- wavelet neural network /
- concrete /
- prediction of strength

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