# bnn meaning in Chinese

班尼奴

生物神经网络

- bnn bronnoysund: 布劳塔伊森德
- bnn boundary network node: 边界网络节点; 边界网络结点

## Examples

More: Next- A binary neural network (
*bnn*) applies to problems in boolean space , extraction of rules is a important research area of it

二进神经网络是应用于布尔空间的神经网络，知识提取是它的一个重要研究领域。 - With these indexes , we applied the accelerated blur neural network (
*bnn*) , which is up rising at present , for simulation and optimization purposes

由于我国进行信贷风险度量起步较晚，信息往往残缺不全，如用传统的风险度量方法很难达到满意的效果，且耗时过长。 - Based on analyzing the relationship between linear separability and a connected set in boolean space , the particular effect of a restraining neuron in extraction of rules from a
*bnn*is discussed , and that effect is explained through a example called a mis problem in boolean space . in this paper , a pattern match learning algorithm of bnns is proposed . when a bnn has been trained by the algorithm , all the binary neurons of hidden layer belong to one or more ls series , if the logical meanings of those ls series are clear , the knowledge in the bnn can be dug out

另一个研究成果是在分析线性可分和样本连通性关系的基础上，以mis问题为例，讨论了抑制神经元在二进神经网络规则提取中的独特作用，提出了二进神经网络的模式匹配学习算法，采用这种算法对布尔空间的样本集合进行学习，得到的二进神经网络隐层神经元都归属于一类或几类线性可分结构系，只要这几类线性可分结构系的逻辑意义是清晰的，就可以分析整个学习结果的知识内涵。 - When a
*bnn*has been trained , because the learning algorithm for it is various , some binary neurons perhaps belong to a kind of linearly separable ( ls ) series , and some others perhaps belong to another kind of ls series . so it is very significative for extraction of rules from a bnn that the general judging methods and logical meanings of all those ls series are studied

由于二进神经网络的学习算法是多种多样的，因此在一个学习后的二进神经网络中，可能存在不同的神经元属于不同的几类线性可分结构系的情况，因此研究二进神经网络中各类线性可分结构系的判别方法和逻辑内涵，对二进神经网络的规则提取是十分有意义的。 - The expressions evaluated from the blur neural network models are then applied in judging the degree and establishing the limit of credit of the borrowers . we demonstrated that the accelerated
*bnn*is s uccessful in that it evolves solutions with greater generalization and forecast capacity than traditional methods . this work is supported by the natural science fund of hebei province education hall

追随目前本领域发展的趋势，本文建立了新的信贷风险度量模型? ?模糊神经网络模型，运用这一模型度量商业银行信贷风险，可克服很多不确定因素的干扰，更加直接、客观地度量信息残缺的银行信贷风险系统，以得出合理的评价结果，为银行进行信贷决策提供科学可靠的依据。