English translation for "connection weight"
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- 连接权
Related Translations:
- Example Sentences:
| 1. | The merits and limitations of genetic algorithms used in optimizing the connection weights of the neural network are discussed
摘要讨论了遗传算法优化神经网络连接权的优点及存在的局限性。 | | 2. | A learning algorithm was introduced , in which most connection weights of the network are fixed , only those between the output layer and the last hidden layer are needed to be adjusted
给出了网络的学习算法，网络的大部分权值都是固定的，只有输出层与最后隐层之间的权值需要调节。 | | 3. | The algorithms is carried into training connection weights of nn and simulation experiments show the arithmetic can escape local optima and improve learning speed of nn to some extent
将其用于调整神经网络的连接权值，实验证明该方法可克服神经网络训练的局部最优解问题，并在一定程度上提高神经网络的学习速度。 | | 4. | In this method , ga is used to optimize connection weights of forward - back neural network until the learning error has tended to stability , then we use sp algorithm with optimized weights to finish short - term load forecasting process
我们用遗传算法来训练网络参数，直到误差趋于一稳定值，然后用优化的权值进行bp算法，实现短期负荷预测，仿真实验结果表明该方法加快网络学习速度，并能提高负荷预测精度。 | | 5. | Thirdly , considering the characters of bp neural networks which is good at local minimum and bad in global optimization and the feature of ga neural networks which is bad in local minimum and good at global optimization , the paper proposes a new algorithm combined ga with bp , referred as to hybrid intelligence learning algorithm , which is applied to the problem optimizing the connection weight of the feedforward neural networks
第三，针对bp神经网络局部搜索能力强、全局搜索能力差和基于遗传算法的神经网络全局搜索能力强、局部搜索能力差的特点，本文提出了一种集bp算法和遗传算法优点为一体的混合智能学习法，并将其应用到优化多层前馈型神经网络连接权问题。 | | 6. | Firstly , this paper analyzes the development and the current situation of the neural networks and genetic algorithm , the related theories of genetic algorithm , such as the basic concept , components , learning rule and simple genetic algorithm , and applies genetic algorithm to the problem optimizing the connection weight of the feedforward neural networks
本文首先分析了神经网络和遗传算法的发展和应用现状，以及遗传算法的基本概念、构成要素、运算过程、特点、理论基础和基本遗传算法所涉及到的内容的研究，并将其应用于优化前馈型神经网络的连接权问题。 | | 7. | It is very important to estimate the basic parameters in helicopter preliminary design . neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods . however , there are some difficulties in using nn , e . g . , how to select a proper network structure and the number of hidden layers . in this paper , structure and connection weight of a three - layer nn are optimized by genetic algorithm , and the optimized network is applied to helicopter sizing . the proposed method can not only give an optimal nn structure and connection weight , but also reduce the prediction error and has the capability of self - learning when the latest data are available . furthermore , this method can be easily applied to helicopter design systems
在直升机初步设计阶段估算其基本参数是很重要的.神经网络的通用性和精度比传统的估算方法有更多的优势,但是在应用神经网络时存在如何选择合适的网络结构和隐层节点数目等一些困难.应用遗传算法优化三层神经网络结构和连接权重,并将优化得到的网络应用于直升机参数选择中.该方法不但可以给出一个最优的神经网络结构和连接权重,而且降低了估算误差,具有及时应用最新数据学习的能力.此外,该方法易于在直升机设计系统中得到应用 | | 8. | Using the indices of trajectory follow error and steering busyness in evaluation of the steering stability , a quadratic form performance index function for the neuron learning was established and the tuning of the connection weight values of the single neuron controller was realized using the algorithm of gradient descent
利用操纵稳定性评价中的轨迹跟随误差和方向盘忙碌程度的评价指标，建立了神经元学习的二次型性能指标函数，并采用梯度下降算法实现了单神经元控制器的滚接权值的调整。 | | 9. | Realization of improved bp algorithm - single output three layers " artificial neural network generator base on improved bp algorithm has been developed by the author , and the generator has some functions that the number of neuron in first and second layer and theirs related training parameters such as learning rate . momentum factor a and the value of sum error e can all be self - defined by the users ; connection weights and threshold in each layer ' s neuron training data and teaching signals can also be input or modified in the friendly interface
生成器功能是:网络结构中的第一、二层神经元个数和训练参数中的学习速率粉，动量因子a和期望误差值:可由用户在一定范围内自定义;各层的权值、阀值、网络初始样本值及教师值可在友好的界面下输入、修改。 | | 10. | Abstract : it is very important to estimate the basic parameters in helicopter preliminary design . neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods . however , there are some difficulties in using nn , e . g . , how to select a proper network structure and the number of hidden layers . in this paper , structure and connection weight of a three - layer nn are optimized by genetic algorithm , and the optimized network is applied to helicopter sizing . the proposed method can not only give an optimal nn structure and connection weight , but also reduce the prediction error and has the capability of self - learning when the latest data are available . furthermore , this method can be easily applied to helicopter design systems
文摘:在直升机初步设计阶段估算其基本参数是很重要的.神经网络的通用性和精度比传统的估算方法有更多的优势,但是在应用神经网络时存在如何选择合适的网络结构和隐层节点数目等一些困难.应用遗传算法优化三层神经网络结构和连接权重,并将优化得到的网络应用于直升机参数选择中.该方法不但可以给出一个最优的神经网络结构和连接权重,而且降低了估算误差,具有及时应用最新数据学习的能力.此外,该方法易于在直升机设计系统中得到应用 |
- Similar Words：
- "connection triangle method" English translation, "connection tube" English translation, "connection type" English translation, "connection units for telephoning aids" English translation, "connection valve" English translation, "connection weld" English translation, "connection wire" English translation, "connection with hong kong" English translation, "connection with the sea" English translation, "connection, connexion" English translation
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