摘要
基于改进的BP算法,建立了2个粉煤灰混凝土钢筋握裹力BP网络计算模型,模型1为2-6-1型,即该模型输入层为2个神经元,隐含层为6个神经元,输出层为1个神经元,模型1的输入为水胶比及粉煤灰掺量,输出为混凝土钢筋握裹力;模型2为2—8—2型,即该模型输入层为2个神经元,隐含层为8个神经元,输出层为2个神经元,模型2的输入为水胶比及粉煤灰掺量,输出为混凝土强度及钢筋握裹力.模型1混凝土钢筋握裹力计算相对误差为0.01908%~3.12892%;摸型2混凝土强度及钢筋握裹力计算相对误差分别为2.24855%~6.80800%和0.11274%~9.77329%.计算结果较为理想.
Based on the optimized BP algorithm, two computation models are developed for the bonding strength of fly-ash concrete which wraps reinforcements. The model 1 is of 2-6-1 type, i. e., 2,6 and 1 neurons are in input, hidden and output layers, respectively, where the input is defined including the water-binder ratio and fly-ash content and the output as the bonding strength of the concrete. The model 2 is of 2-8-2 type, i.e., 2, 8 and 2 neurons are in input, hidden and output layers, respectively, where the input is the same to that in model 1 but the output includes the compressive strength in addition to the bonding strength of the concrete. The relative error of the bonding strength calculated through model 1 is 0.019 08 %- 3. 128 92 %, while the relative errors of the compressive strength and bonding strength calculated through model 2 are 2.248 55% -6.808 00% and 0. 112 74% -9.773 29%, respectively. Such results are quite .satisfactory.
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2007年第2期274-277,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(50174013)
关键词
BP网络
粉煤灰混凝土
钢筋握裹力
抗压强度
水胶比
BP network
fly-ash concrete
bonding strength
compressive strength
water-binder ratio