基于此，本文提出了基于集成神经网络的城市道路交通流量的融合预测模型。
Accordingly, this paper proposes a fusion-prediction model of traffic-flow in urban road-intersection based on integrated ANN (Artificial Neural Network).
该模型在传统专家系统基础上，增加了神经网络集成模块，以解决知识的自动获取和推理问题。
Based on the traditional expert system, the integrated module of neural network ensembles is applied in this model in order to insure the automatic acquisition of knowledge and reasoning.
通过对神经网络集成的理论分析，提出了一种多级神经网络结构的手写体汉字识别模型。
By analyzing the theory of neural network integration, I developed a multi-level neural network model for recognition handwritten Chinese characters.
提出一种基于神经网络集成的专家系统模型，并给出神经网络集成的构造算法。
The expert system model based on neural network ensembles is presented. A construction algorithm of the neural network ensembles is given.
集成神经网络模型以故障层次模型为参考，可以大大缩小诊断推理的求解空间，最终快速定位发生故障的根本部位。
Refer to hierarchical fault model, the integrated ANN diagnostic model can contract the scope of diagnostic reasoning, and find quickly the fault components.
集成神经网络模型以故障层次模型为参考，可以大大缩小诊断推理的求解空间，最终快速定位发生故障的根本部位。
Refer to hierarchical fault model, the integrated ANN diagnostic model can contract the scope of diagnostic reasoning, and find quickly the fault components.
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