对逐孔起爆技术的机理、爆破网络设计以及爆破震动和质量等结果进行了分析。
The analysis has be done about the mechanism of the technology and the design of blasting net and the blasting vibration and quality.
在施工网络计划的优化过程中，就关键工序光面爆破进行了优化设计。
Optimization of smooth blasting procedure, the most important one for network plan, is discussed.
应用遗传神经网络模型对台阶压碴爆破效果进行了预测，增强了预测结果的可靠性。
Predicts bench tight blasting effects by genetic neural network, which can enhance the reliability of predicting effects. Genetic neural network is the model of human brain.
应用遗传神经网络模型对台阶压碴爆破效果进行了预测，增强了预测结果的可靠性。
In this paper bench tight blasting effects are predicted by genetic neural network, then the reliability of predicting effects is enhanced.
应用遗传神经网络模型对台阶压碴爆破效果进行了预测，增强了预测结果的可靠性。
Predicts bench tight blasting effects by genetic neural network, which can enhance the reliability of predicting effects.
近几年，爆破界学者把人工神经网络运用在预测爆破效果及爆破振动峰值上取得了较好的效果。
In the last few years, people have acquired better knowledge in estimating the result of blasting and the peak of vibration in blasting.
文中介绍了爆破方案确定、爆破参数选择、装药量计算、起爆网络及安全措施等。
Determination of blasting scheme, selection of blasting parameters, calculation of charge weight, priming network, safety precautions and others were presented in this paper.
叙述了孔内微差爆破时间间隔的确定、起爆方式、网络连接及其应用效果。
The paper describes the determination of in-hole and between-holes microsecond delay time, the detonation mode and the network connection and their application effect.
提出了比较系统的药壶爆破设计方法，包括药壶爆破参数的确定、扩壶施工、起爆网络等。
A relative systemic spring blasting design is put forward, including the blasting parameters choice, the expanding springing engineering and the initiating system.
利用BP神经网络模型对民房安全进行预测，并对爆破参数进行优化。
Lately, the forecast of the civil houses' safety by using BP neural net model and optimize of the blasting parameters will also be discussed in the dissertation.
对震动放炮揭煤的爆破参数、起爆网络等进行了精心设计与施工，安全顺利地揭开了煤层。
The blasting parameters, circuit, etc. of vibration shot uncovering coal, are designed and constructed and coal seam is uncovered safely and successfully.
预报值与实测值符合较好，证实人工神经网络能有效预报爆破地震动峰值。
The results indicate that the predicted values accord with the measured ones and the artificial neural network is reliable in predicting blasting vibration peak velocities.
预报值与实测值符合较好，证实人工神经网络能有效预报爆破地震动峰值。
The results indicate that the predicted values accord with the measured ones and the artificial neural network is reliable in predicting blasting vibration peak velocities.
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