Based on the immune algorithm, an optimizing method is presented which is used to search the weights of B-P network.
提出了一种基于免疫算法的B - P网络权值设计方法，用于实现B - P网络权值空间的搜索。
This paper mainly discusses the application of B-P network in stock forecasting and analysis. contrasts the network function in different conditions.
该文主要研究人工神经网络中的B-P网在股票分析和预测中的应用，对比各种情况的网络性能。
Aim at data inspection and mode identification of atmospheric environment, B-P network evaluation mode was established by the application of artificial neural network theory.
针对大气环境中的数据监测与模式识别问题，应用人工神经网络理论，在自然环境大气腐蚀试验网站建立大气环境质量B - P网络评价模型。
A new method of prediction on the radiant brightness values of deuterium lamps is proposed using back propagation (b p) neural network.
本文提出了应用B - P神经网络预测氘灯辐亮度值的新方法。
Then, as artificial neural network is better in constructing financial prewarning model than other linear and regression models, a new financial prewarning model based on B-P model was constructed.
然后，利用人工神经网络在建立财务预警模型方面优于其他线性和回归模型的特点，基于B - P模型构建了一个新的混合财务预警模型。
The assessment model of atmospheric environment quality of city using B-P artificial neural network is proposed.
应用人工神经网络理论，建立了城市大气环境质量的B - P网络评价模型。
In order to evaluate environmental quality, this paper proposed the B-P decision model for environmental quality by using artificial neural network method.
为了对环境质量进行综合评价，运用误差反向传播算法的人工神经网络方法建立了环境质量评价的B - P决策模型。
These features are used to train a B-P neural network, it is a classifier and can improve greatly the recognition rate of Chinese characters.
使用该B-P神经网络作为汉字的分类器，可以大大提高车牌汉字的识别率。
With GIS (Geographic Information system), applying the B-P Nerve Network the nonlinear forest biomass RS (Remote Sensing) modeling system was designed.
结合GIS技术，应用B - P神经网络建立了森林生物量非线性遥感模型系统。
An intelligent pattern classifier with B-P neural network is used in recognition of those five kinds of AE signals successfully.
采用B - P型反向传播神经网络构成的智能化模式分类器，对此五类声发射信号进行识别，获得了满意的效果。
An intelligent pattern classifier with B-P neural network is used in recognition of those five kinds of AE signals successfully.
采用B - P型反向传播神经网络构成的智能化模式分类器，对此五类声发射信号进行识别，获得了满意的效果。
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