基于Matlab和BP神经网络的爆破振动预测系统

爆破振动预测是一个复杂的非线性问题，可应用非线性功能强大的BP神经网络技术来解决，但由于其数值计算量大、可操作性不强等特点，在实际工程中应用困难。为了解决该问题，本文中将Matlab程序的强大计算能力与VB的友好界面相结合，利用ActiveX自动化技术和BP神经网络算法，开发得到爆破振速峰值预测系统。该预测系统可根据各工程实际情况选取影响爆破振动的主要因素作为输入参数，以预测爆破振速峰值。通过在北京市昌平线暗挖区间隧道工程中的应用表明:该预测系统在实际工程中使用方便，操作简单，预测精度高，人机交互界面友好。

Forecast system for blasting vibration velocity peak based on Matlab and BP neural network

In this work we combined the powerful computing capabilities of Matlab programs combined with VB friendly interface and developed the forecast system for blasting vibrational velocity peak using ActiveX automation technologies and BP neural network algorithm. The forecast system can select as an input parameter various factors affecting an engineering project's blasting vibration. The actual application of the system in the construction of the underground cut tunnel in the Beijing-Changping Line shows that this system is simple and convenient to use in practical engineering, accepted for its high precision of prediction, good application effect and friendly human-computer interaction interface.