采用多层前向型神经网络，对燃煤循环流化床锅炉模型化进行了研究。
This paper presents a modelling method of the circulating fluidized bed combustion (CFBC) boiler using a feedforward neural network.
采用多层前向型神经网络，对电站锅炉对流受热面的实时污染状况建立了监测模型。
Fouling Monitoring Modeling System based on the BP neural network for boiler convection surfaces is presented in this paper.
神经网络可以很好的解决交通领域内的非线性问题，其中前向型神经网络特别适合对交通流的预测。
In traffic field, Neural Network has good advantage in the non-linear Neural Network, and it 's specially good at problem perfectly solving the traffic in the field of the forward flow forecasting.
基于前向型神经网络理论的时间序列分析跳出了传统的建立主观模型的局限，通过时间序列的内在规律作出分析与预测。
Time series analysis based on neural networks theory cross through traditional frame of subjective model draw out prediction on the inner rules of linear time series data.
其次，本文对神经网络理论进行了简要的阐述，并对两种前向型网络进行了详尽的分析，也对这两种网络的差异进行了探讨。
Secondly, the neural network theory is discussed briefly in this paper. At the same time, the paper analyses the two forward-type networks detailedly and also ascertains their differences.
把填充函数法与BP算法相结合，提出一种训练前向神经网络的混合型全局优化新算法。
This paper proposes a new global optimization technique in which combines the filled function method and BP algorithm for Training feedforward neural networks.
把填充函数法与BP算法相结合，提出一种训练前向神经网络的混合型全局优化新算法。
This paper proposes a new global optimization technique in which combines the filled function method and BP algorithm for Training feedforward neural networks.
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