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The Application of SOFM Fuzzy Neural Network in Project Cost Estimate

机译:SOFM模糊神经网络在工程造价估算中的应用。

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Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM to improve the fault such as poor convergence and insufficient forecast. After optimizing of T-S fuzzy neural network model, construct project cost estimate model had been built up. Finally, the model was set up with the purpose of comparing generalization ability by 18 examples and 2 testing samples. Comparing the simulation, a positive result was found that SOFM fuzzy neural network had a better performance in reducing the forecast error and iterating times than BP, and GA-BP. Therefore, this model is fit for handling construct project cost estimate.
机译:神经网络的应用被广泛应用于建设项目成本估算中。为了解决收敛性差,预测不足的缺点,提出了一种基于SOFM(自组织特征图)的改进的模糊神经网络方法来代替流行的T-S模糊神经网络。该方法说明了如何应用SOFM来改善收敛性差和预测不足等故障。在对T-S模糊神经网络模型进行优化之后,建立了工程造价估算模型。最后,建立模型以比较18个实例和2个测试样本的泛化能力。通过仿真比较,发现与BP和GA-BP相比,SOFM模糊神经网络在减少预测误差和减少迭代次数方面具有更好的性能。因此,该模型适合处理建设工程造价估算。

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