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以水口水电站坝体为例,基于Matlab中BP神经网络构建了效应量与环境量的网络模型,结合网络的权值和偏置值的综合影响,定量分析和研究了决定大坝效应量的水位、温度和时效等因素的重要性,并与传统的统计结果进行对比。结果表明,该方法可确定水位、温度等分量占效应量的比例,具有实用性和有效性。
Taking the dam of Shuikou Hydropower Station as an example, a network model of effect quantity and environment quantity is constructed based on BP neural network in Matlab. Combined with the comprehensive influence of network weight and offset value, the water level of dam effect is quantitatively analyzed and studied , Temperature and aging and other factors, and compared with the traditional statistical results. The results show that this method can determine the proportion of water level, temperature and other components of the amount of effect, practical and effective.