| 1. | Error back propagation network is one kind of ann and it ' s widely used in economics prediction
误差反向传播网络( ebp网络)是人工神经网络的一种，它被大量运用在经济学的预测问题上。 |
| 2. | Genetic algorithm is used to optimize the initial weight of back propagation network and the operation efficiency is enhanced
用遗传算法优化bp网络的初始权值,提高神经网络的运算速度。 |
| 3. | The essence of back propagation networks is that make the change of weights become little by gradient descent method and finally attain the minimal error
其实质是采用梯度下降法使权值的改变总是朝着误差变小的方向改进，最终达到最小误差。 |
| 4. | To get the much more quality and rate of image compression , we bring forward another new three layers back propagation networks and it ' s arithmetic
基于此我们提出了新型二层误差逆传播网络拓扑结构和算法，为进一步提高图像压缩的压缩比和压缩质量，我们提出了新型三层误差逆传播网络拓扑结构和算法。 |
| 5. | Taking the evaluation criterion of lake nutrient states as sample pattern , the network was trained in the light of learning rule of error back propagation network
将湖泊营养状态评价标准作为样本模式提供给网络，按照误差逆传播网络的学习规则对网络进行训练，经过39925次学习后，网络达到预先给定的收敛标准。 |
| 6. | Firstly , second harmonic component ratio and dead angles of two phase inrush ' s dispersion in three - phase transformes are acted as input variable . secondly , the method applies improved algorithm based on the original algorithm of multi - layer forward back propagation network , that is to say , adding last variational effect of weight value and bias value to this time and making use of variable learning rate . at the same time , this method also adopts dynamic form in the number of hidden floor node
首先，文中将三相变压器两相涌流差流的二次谐波含量比和间断角作为网络的输入变量；其次，利用对原有bp网络训练算法基础上的改进型算法(即在计算本次权值和阈值的变化时增加上一次权值和阈值变化的影响以及采用变学习率，与此同时隐含层神经元个数采用动态形式) ，通过样本训练使网络结构模型达到最优。 |
| 7. | In the process of image compression , considering that the three or more layers bp networks have some redundancies in the weights between input layer and meddle layer so as to effect the network ' s study speed and compression quality , we bring forward a new two layers back propagation networks and it ' s arithmetic
考虑到利用三层及三层以上bp网络对图像压缩，其有效信息是中间层单元上的输出值和中间层与输出层之间的连接权，而输入层与中间层的连接权是冗余的，以至于对学习速度和压缩质量有负面影响。 |
