共查询到18条相似文献,搜索用时 93 毫秒
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用粗集-模糊神经网络评定空袭目标威胁程度 总被引:2,自引:0,他引:2
针对模糊神经网络运算过程中,当模糊规则较多时,网络学习速度慢,方法实时性差的缺点,本文提出采用粗糙集理论对该模型进行优化,该方法利用粗集数据分析方法,通过知识约简从数据中推理逻辑规则,并用约简后规则集作为模糊神经网络的规则将输入映射到输出的子空间上:在这个子空间上用改进的BP算法训练进行逼近.实验结果表明:通过粗集数据挖掘后提取的规则,不仅规则数目减少,且规则是不完全规则,减少了网络输入维数和各层神经元的个数,提高了网络运算速度,满足了系统实时性要求. 相似文献
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把知识生产划分为批量型知识生产和订单型知识生产两类,绘制了它们的流程,并系统地比较了它们与传统制造行业供应链的差异。针对知识生产的流程更加复杂多变,供应链更新更快且对象更难于量化的特点,提出了批量型和订单型两类知识生产的绩效评估指标体系,在此基础上通过BP神经网络模型,得出了它们的绩优度,为知识生产绩效的评估提供了参考和依据。 相似文献
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故障诊断的模糊神经网络模型 总被引:11,自引:2,他引:9
论证了单症兆和多症兆诊断的模糊模型分别与一定条件的单层神经网络等价,从而建立了单症兆和多症兆诊断的模糊神经网络模型。基于模糊诊断原理,阐述了模糊神经网络模型是由若干独立单元组成的可扩充的组合式结构,进而提出一种修改或扩充子网络或子结点及其权重连线的可塑性学习方法。基于此模型建立了旋转机械故障诊断专家系统,以现场实际例子对模型的应用进行了说明。 相似文献
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赊销客户信用度分析的神经网络模型 总被引:4,自引:1,他引:3
根据企业与客户之间的互动关系,作出影响客户信用的价值因素和行为因素分析,引入数据挖掘算法中的神经网络模型,进行客户信用等级的评价,以此制定相应的赊销政策,控制客户信用风险。 相似文献
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本文提出了在空调负荷计算中引入神经网络模型的思想,介绍了神经网络的概念、原理及其在空调冷负荷计算中的应用方法。 相似文献
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We present a method for solving partial differential equations using artificial neural networks and an adaptive collocation strategy. In this procedure, a coarse grid of training points is used at the initial training stages, while more points are added at later stages based on the value of the residual at a larger set of evaluation points. This method increases the robustness of the neural network approximation and can result in significant computational savings, particularly when the solution is non-smooth. Numerical results are presented for benchmark problems for scalar-valued PDEs, namely Poisson and Helmholtz equations, as well as for an inverse acoustics problem. 相似文献
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通过建立物理标准的某一物理量值与该物理标准的其它特性指标之间的神经网络模型,求解得出该物理量值。研究结果表明此方法性能良好,可望成为预先估计物理标准量值的有效手段。 相似文献
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An Efficient Model for Batch Annealing Using a Neural Network 总被引:2,自引:0,他引:2
A comprehensive process model, capturing heat transfer, phase transformation, and microstructural evolution, was recently developed for efficient process cycle design of a batch annealing operation. However, the high computation time for such an integrated model makes it difficult to design process cycles for a battery of furnaces or their model based online control. In the present work, an accurate prediction tool has been derived using neural network modeling from the simulations of the comprehensive process model. Using this approach, the computational efficiency of this prediction tool increases by over 100 times, making it amenable to cycle design of multiple furnaces or their online process control. Subsequently, an exhaustive search technique and genetic algorithm have been used to optimize the coil dimensions to maximize the plant productivity. It was found that batch annealing productivity can be maximized by optimizing the coil inner diameter, while constraining the coil width and outer diameter at the maximum permissible dimensions. 相似文献