大连理工大学学报
大連理工大學學報
대련리공대학학보
JOURNAL OF DALIAN UNIVERSITY OF TECHNOLOGY
2009年
4期
576-579
,共4页
围岩变形%预测%ANFIS%BP网络
圍巖變形%預測%ANFIS%BP網絡
위암변형%예측%ANFIS%BP망락
surrounding deformation%prediction%ANFIS%BP network
针对目前应用人工神经网络(ANN)方法预测地下洞室围岩变形时间序列的缺陷,提出一种将神经元网络和模糊逻辑有机结合的新型模糊推理系统--ANFIS(adaptivenetwork-based fuzzy inference systems),该系统采用反向传播算法和最小二乘法的混合算法分别调整前提参数和结论参数,充分地利用了神经网络的学习能力和模糊逻辑的表达能力,实现了回归模型的自适应调整.通过龙滩电站的实例应用可以发现,ANFIS预测系统较传统ANN方法具有简单、快速以及预测精度高等特点.
針對目前應用人工神經網絡(ANN)方法預測地下洞室圍巖變形時間序列的缺陷,提齣一種將神經元網絡和模糊邏輯有機結閤的新型模糊推理繫統--ANFIS(adaptivenetwork-based fuzzy inference systems),該繫統採用反嚮傳播算法和最小二乘法的混閤算法分彆調整前提參數和結論參數,充分地利用瞭神經網絡的學習能力和模糊邏輯的錶達能力,實現瞭迴歸模型的自適應調整.通過龍灘電站的實例應用可以髮現,ANFIS預測繫統較傳統ANN方法具有簡單、快速以及預測精度高等特點.
침대목전응용인공신경망락(ANN)방법예측지하동실위암변형시간서렬적결함,제출일충장신경원망락화모호라집유궤결합적신형모호추리계통--ANFIS(adaptivenetwork-based fuzzy inference systems),해계통채용반향전파산법화최소이승법적혼합산법분별조정전제삼수화결론삼수,충분지이용료신경망락적학습능력화모호라집적표체능력,실현료회귀모형적자괄응조정.통과룡탄전참적실례응용가이발현,ANFIS예측계통교전통ANN방법구유간단、쾌속이급예측정도고등특점.
In allusion to the insufficiency of the prediction accuracy of artificial neural network (ANN) algorithm for underground cavern rock surrounding stability,the method of ANFIS (adaptive-network-based fuzzy inference systems) machines is applied to researching into evolution law for a nonlinear deformation time series of rock surrounding.ANFIS is a new fuzzy inference system which combines neural network and fuzzy logic organically.The hybrid algorithm of back propagation algorithm and least square method is adopted to adjust the premise parameter and the consequent parameter respectively,which makes full use of the learning ability of neural network and the expression ability of fuzzy logic to realize the adaptive adjustment of the regression model.Compared with the conventional ANN method,the application of ANFIS forecasting system in Longtan Hydropower Station can be found simple,fast and accurate.