And it studied relation between chaos mapping parameters and training error, puts forward chaos mapping parameter adjust steps and applications.
给出了应用实例。还研究了混沌参数与训练误差的关系，提出了混沌参数的调整步骤及应用。
More likely, Dr. McHugh said, they fell victim to a training error, which, he explained, "in reality can mean any abrupt change in training patterns."
麦克休博士说，很有可能，他们是错误训练的受害者，也就是训练方式的突然改变。
Through finding, organization error has 5 big categories, that is supervision error, information error, training error, surrounding environment error and work condition error;
通过研究发现，组织失误有监管失误、信息交流失误、培训失误、周围环境失误与工作条件失误5大类；
A performance index of error was presented. This index is a kind of evaluation of neural fuzzy model performance and synthetically considered training error and checking error of NFS.
提出了一种综合考虑了训练误差和检验误差的评价神经模糊模型性能的误差性能指标。
Parameters value of sites in ants' route was bestowed on BP network, while parameters and training error stored in stored units were changed along with the adjustment of training error of BP network.
又将蚂蚁行经路径上的存储单元存放的参数值赋予BP网络训练，而存储单元存放的参数和训练误差值亦随BP网络训练误差的调整而改变。
The obvious result was that the three use cases came to resemble one another closely, and from that you can expect reduced training requirements and fewer defects due to human error.
明显的结果在于，三个用例变得彼此紧密相似，在此基础上预期可以减少培训需求和人为错误导致的缺陷。
Minimum Classification Error (MCE) criterion based sub-words weighting parameters estimation algorithm is proposed in which the sub-word weighting parameters are derived by the MCE training.
本文提出了一种基于最小分类错误准则(MCE)的子词权重参数估计算法，通过MCE训练得到子词的权重系数。
This model adopted direct prediction method, so error accumulation effect was avoided. The training data set was real-time updated so that the model was always the newest.
该模式采用直接预报的方法，避免了误差累积效应；对训练集实时更新，以保证模式的不断更新；模式的输入比较简单，便于应用。
The optimum programs are made for the target error, the learning of Neural Network, the time of training.
对目标误差、网络的学习率和训练次数进行了具体的优化。
Simulation results show that compared with fixed training interval schemes, the improved algorithm can achieve better BER (Bit Error Rate) performance while keeping lower system overhead.
与采用固定训练周期相比，该方法可以在保证比较低的导频开销的同时，使系统获得更好的误比特性能。
The model was trained with training sample aggregation. The maximum error between the forecasted and real value was 0.97%.
用训练样本集对网络训练后，检验样本的预测结果与实际值最大误差为0.97%。
An improved design method on pattern classifier based on multi-layer perceptrons (MLP) by means of minimum classification error (MCE) training was proposed.
提出了一种基于最小分类错误(MCE)训练的采用多层感知器(MLP)结构的模式分类器设计方法。
Secondly, the hybrid training algorithm is proposed on the base of the Error Back-propagation algorithm's disadvantage analysis in the paper.
其次，从误差反传算法在预测中存在的问题入手，提出一种混合训练算法。
Because the error transfer function of rough neural network is not differentiable, genetic algorithms are applied for training the network.
由于粗神经网络的误差传递函数不可微，所以采用遗传算法来训练粗神经网络。
This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
A low degree of specialization of judges, some of them not subject to professional training, business is comparatively low, lack of experience and so may lead to the fact that the error found.
二是法官专业化程度较低，部分法官没有受过专业训练，业务能力较低，经验不足等都可能导致事实认定错误的发生。
Further, a hybrid BP algorithm with dead interval of error is derived for training the neural classifier in order to increase training speed and classification accuracy.
此外，提出用带输出误差死区的混合BP算法训练神经元分类器，提高了网络学习训练速度和分类准确性。
It can identify the parameters of a controlled object by forming a fake output and bring in a feedback error for performing an on-line training to decouple the neural network.
它通过构造伪输出辨识被控对象参数，引进反馈误差，实现对解耦神经网络的在线训练。
A neural network model with dynamical compensating capability is analyzed. During the training of this network model, we apply the principle of dynamic error back-propagation.
本文分析了一种动态补偿神经网络模型，模型的训练利用反向传播原理实现。
Minimum classification error (MCE) rate method is the most straightforward criterion for HMM training. Inprinciple, it is much better than the maximum likelihood method.
最小错识率(MCE)HMM训练方法是最直接的判决训练方法之一，原理上比最大似然接方法优越得多。
The appropriate training targets are set to lessen the tracking error being caused by overshoot and other undesirable characteristics.
为克服船舶过冲引起的航迹偏差等缺点，还设置了适当的训练目标。
This algorithm USES the prediction error threshold to retain the useful information to decrease sample training scale.
该算法利用预测误差阈值进行样本的取舍，在尽量保留有用信息的情况下减小样本训练规模。
At last the proposed network is used to the construction bidding system. The results of the simulation indicate that it can obtain higher error precision, training speed and generalization ability.
最后将提出的网络结构应用于建筑工程的投标报价中，仿真结果证明：该网络能达到更高的误差精度、更快的训练速度和更好的泛化能力。
Specifies the percentage of training cases used to calculate the holdout error, which is used as part of the stopping criteria during neural network learning.
指定用于计算？效组错误的培训案例之百分比，以在类神经网路学习期间作为停止准则的一部分。
The effect of training set size on the error of neural network model is analyzed. The results show that the model has reasonable accuracy when the training set size is not less than 14.
分析了训练样本集的大小对模型误差的影响，指出在训练样本不少于14个的情况下，模型具有较高的预测精度。
This method utilizes the nonlinear mapping ability of the BP neural network. By training, the BP neural network achieves the error compensation for multi sensor system.
该方法利用BP网络较强的非线性映射能力，网络通过学习能实现对传感器系统误差的补偿。
The structure of a partially connected feed forward neural network and the training algorithm based on the recursive prediction error are constructed.
构造了局部连接的前馈神经网络的结构和基于递推预报误差的网络训练算法；
In the training process, the adaptive learning rate and error batch-mode process are introduced to accelerate the training rate.
在神经网络自学习过程中，引入了自适应学习速率和误差批处理法，加快了学习速度。
In the training process, the adaptive learning rate and error batch-mode process are introduced to accelerate the training rate.
在神经网络自学习过程中，引入了自适应学习速率和误差批处理法，加快了学习速度。
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