| 1. | This paper focuses on the classification based on back - propagation neural network
本文主要研究以误差反向传播bp神经网络处理的分类问题。 |
| 2. | 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。 |
| 3. | The application of hybrid algorithm which combines improved genetic algorithm and error back - propagation algorithm in artificial neural network training is studied first
首先研究了将改进遗传算法和误差反向传播( bp )算法相结合的混合算法来训练人工神经网络。 |
| 4. | In order to satisfy the requirement of the given precision , the connection power of the networks is studied and adjusted using the baekpropagation training algorithm ( bp algorithm )
采用误差反向传播算法( bp算法)对网络的连接权值进行学习和调整，以满足给定的精度要求。 |
| 5. | In this article we use a bp neural network to classify the eddy current signal and its result is also presented , which indicate that artificial neural network has vast potential in eddy current signal processing
本文选用基于误差反向传播( bp )算法的神经网络对信号分类，并给出分类结果，表明了神经网络在涡流材质检测信号处理中应用的巨大潜力。 |
| 6. | Secondly , binary probability hypothesis detection is studied and is utilized as actuators " fdi residual decision . thirdly , multi - layer feed - forward ann and error backward propagation ( bp ) algorithm are studied and are utilized as control surfaces " failure detection and sortation
第三，研究多层前馈神经网络及相应的bp ( errorbackwardpropagation误差反向传播)算法，设计基于模型残差的故障分类器，并通过其来完成全局舵面的故障检测与分类。 |
| 7. | Using the back - propagation artificial neural networks which have the satisfactory nonlinear prediction ability , the correlation between molecular structures and flash points of fatty alcohols was studied with molecular structure descriptors as input parameters and flash point as output one
同时引入具有高度非线性预测能力的误差反向传播人工神经网络方法，以分子结构描述符作为神经网络的输入参数，闪点作为输出，研究脂肪醇的闪点与分子结构之间的相关性。 |
| 8. | 2 . based on the original bp network , some improvement on error back propagation arithmetic is made . the executing speed of the algorithm is increased through online adjustment of learning rate . combined with traditional pid control , this method generated two integral schemes : bp network + pid serial control and self - confirming control of parameters of pid controller based on bp network are constructed
在原有的误差反向传播（ bp ）网络的基础上，对其学习算法进行了改进，通过在线调节学习速率，提高了算法的实现速度，并且与传统的比例积分微分（ pid ）控制方法进行结合，分别实现了两种集成方法： bp网络与pid串行控制方法和基于bp网络的pid参数自整定控制方法。 |
| 9. | The main point of this project is to research the theories and applications of artificial neural network ( ann ) which is suitable for large scale science data mining . especially , our research focus include : dimension reduction techniques based on independent component analysis ( ica ) and wavelet - based denoising or compressing techniques for feature extraction in scientific datasets which have complex features ; classify and clustering techniques of ann combination with data grid , back - propagation neural network , self - growing multilevel self - organizing map for large scale knowledge founding in sdm
特别深入研究以独立分量分析( ica )为主的降维技术、以小波神经网络为主的压缩降噪技术解决科学数据特征复杂不便识别的问题;以同网格结合的神经网络、误差反向传播的bp神经网络、自适应多级自组织特征映像网络为主的分类、聚类技术解决科学数据挖掘中的大规模知识发现问题。 |
