RBF神经网络在大坝安全综合评价中的应用  

APPLICATION OF RADIAL BASIS FUNCTION NEURAL NETWORK TO COMPREHENSIVE EVALUATION OF DAM SAFETY

作　　者：闫滨[1] 高真伟 李东艳[1] 

机构地区：[1]沈阳农业大学水利学院,辽宁沈阳110161 [2]辽宁省水利厅,辽宁沈阳110003

出　　处：《岩石力学与工程学报》2008年第A02期3991-3997,共7页Chinese Journal of Rock Mechanics and Engineering

基　　金：沈阳农业大学青年教师科研基金资助项目(20070110)

摘　　要：大坝安全评价常用的多级灰关联评估、模糊综合评判等方法均需设计各评价指标对各级标准的隶属函数及各指标的权重,然后综合考虑大坝的安全程度。由于具体问题的复杂性和多样性,其评价结果受评价者主观因素的影响较大。人工神经网络则可以通过学习自动调整各影响因素的权值,它不仅能较好地吸收学习样本中领域专家的思维和经验,还具备较高的抗干扰能力和较好的容错性。因而,已有学者将改进的BP神经网络用于大坝安全综合评价。然而,BP网络收敛速度慢,稳定性差,易陷入局部极小,极大地限制其实际应用。为此,提出将径向基函数神经网络应用于大坝安全综合评价。通过对给定学习样本模式的学习,获取学习样本中所体现的评价专家的知识、经验、主观判断及对目标重要性的倾向。当应用训练好的网络对非样本集中的新的输入进行映射时,就可在输出的评价结果中再现专家的直觉思维和经验,从而得出比较合理的评价结论。以丰满大坝10个典型坝段的安全评价为例,验证该方法的有效性。The methods of multi-step grey-correlation evaluation and fuzzy comprehensive evaluation are usually used in dam safety evaluation. Both of them need to design weights of each index and membership of evaluation indexes, and then the dam safety is determined synthetically. Due to the complexity and diversity of each problem, the subjective factors have great influences on the final evaluating conclusion. The artificial neural network could adjust the weights of each influencing factor automatically. It could not only absorb the experts＇ thought and experiences embodied in the study samples, but also possess high anti-jamming ability and better error permissibility. As a result, an improved BP neural network has been applied to comprehensive evaluation of dam safety. However, the shortcomings of slow convergent rate, poor stability and local minimum of BP neural network have extremely restricted its application. Therefore, the radial basis function neural network is proposed to apply to comprehensive evaluation of dam safety. By study of the given samples, the experts＇ knowledge, experiences, subjective judgment and tendency towards the importance of objectives embodied in the samples are obtained. When applying the well trained network to map a new input of given samples, the output results can reproduce the experts＇ instinctive thought and experiences and make a reasonable evaluation conclusion. Evaluation examples of ten typical dam sections of Fengman dam testifies the validity of the new method.

关 键 词：水工结构工程 大坝安全综合评价 神经网络 

分 类 号：TV13[水利工程—水力学及河流动力学]