该模型包括输入层、隐含层和输出层。
This model includes the input layer, hidden layer and output layer.
然后，将每个像素的灰阶值 提供给6 个输入层节点。
Each pixel's grayscale value is then fed to each of six input layer nodes.
网络模型由三层构成：输入层、隐含层、输出层。
The network model consists of three layers: the input layer, the hidden layer, and the output layer.
网络的输入层引入模糊集合理论，使网络能处理语义变量。
The fuzzy set theory was employed at the input layer to make the processing of linguistic variables possible.
我们选择的网络结构包括一个输入层、一个隐含层、一个输出层。
The chosen neural network architecture consisted of one input layer, one hidden layer and the output layer.
通过对字符特征的分析，确定输入层，隐含层，输出层单元数目。
Through the analysis of character features, confirm the input layer, hidden layer and the License of output layer units.
第一层即输入层，包含一组处理单元，负责接受向网络输入的数据。
The first layer is input layer consisting of a group of processing units which are responsible for acceptance of data imported to the network.
输入层分别为小车的位移和速度、摆杆偏离铅垂线的角度和角速度。
Input layer is respectively the displacement and speed of car, the Angle and Angle speed between pendulum bar and vertical line.
使用pull方法则无法知道节点究竟位于输入层、隐藏层还是输出层。
With the pull methodology, individual nodes have no way of knowing if they are in the input, hidden, or output layer.
网络学习结束后，得到输入层、中间层和输出层各单元的连接系数矩阵。
After studying network, coefficient matrix of each unit which includes input layer, intermediate layer and output layer was gained.
BP神经网络模型的输入层设12个结点，输出层设22结点，设一层隐含层。
The model consists of three neuron layers: input layer with 12 nodes, output layer with 22 nodes and hidden layer.
当输入层接收到输入时，其神经元产生输出，这些输出又成为系统其它层的输入。
Some of the neurons interface the real world to receive its inputs and other neurons provide the real world with the network's outputs.
网络隐层-输出层的权值采取最速下降法学习，输入层-隐层的权值采用遗传算法进行学习；
The learning method of hidden-output layer weights is the steepest descent method and the one of input-hidden layer weights is genetic algorithm(GA) .
为了解决红外光谱定量分析中的特征提取和校正规模问题，提出了一种输入层自构造神经网络。
In order to solve the problems of feature extraction and calibration modeling in the area of quantitatively infrared spectral analysis, a structural adaptive neural network is proposed.
再将各个输入层节点的输出 提供给6 个隐藏层节点，这些隐藏层节点将依次提供给3 个输出接点。
The output of each input layer node is fed to each of six hidden-layer nodes, which in turn feed three output nodes.
在不破坏单个神经元的输入权值的基础上，采用数据预处理的方法来减少输入层的个数，从而提高进化学习的能力。
Without the destruction of single neurons based on input weights, adopt data pretreatment methods to reduce the number of input layers, so as to improve the ability of evolutionary learning.
利用人工神经网络法中的自适应共振理论优选钻头 ，将定性、定量优选因素作为输入层神经元 ，形成一种综合性选型方法 。
The new network model is formed by incorporating the two concepts of fuzzy set theory, closeness and closest principles, with adaptive resonance theory (ART).
在BP网络模型建立时采用了对研究区泥石流活跃程度影响最主要的8个参数作为输入层，并选取了研究区的20个样本对网络进行训练。
When BP network model is established, 8 parameters affecting the debris flows activity of the studying area are chose as the net input layer, and 20 samples are used to train the network.
因此，在输入面板中，第二个查询被指定为第1层。
Therefore, the second query is specified for layer 1 in the input panel.
此函数将以输入点为基础，按照用户指定的距离创建一个新缓冲区轮廓数据层。
This function will create a new buffer feature data layer around the input point features at user specified distance.
在实现集成组件后，BPM层将提供事件数据和统计数据（这些数据还可以被输入到建模环境中）的捕获和交付。
Following implementation of integration components, the BPM layer provides capture and delivery of event data and statistics, which can also be input back into the modeling environment.
虽然大多数EUP规程工作于组织层，并且作为企业架构过程的输入，但是EUP本质上不是企业架构开发框架。
Although most EUP disciplines function at an organization level and act as inputs to enterprise architecture processes, EUP is not an enterprise architecture development framework per se.
不过，对于整个协议层，只有一个称为IP输入队列的协议队列。
However, there is only one protocol queue, which is called the IP input queue, for the entire protocol layer.
由于其复杂的结构，你可以对活动递归地进行分组并对流进行连接以形成更高的层，这种层次清晰地定义了输入和输出。
As with complex structures, you can recursively group activities and their interconnection flows into higher-level activities with clearly defined inputs and outputs.
每一层的设备都实现了模型(计算，应用程序)，视图(展现)和控制器(输入和交互能力)。
At each tier, the devices embody models computation, apps, views the display, and controllers input and interaction capability.
此过程可以轻松地完成，因为用户输入是通过Web应用程序的结构层和HTTP来路由的。
This process is easy to accomplish because input from the user is routed through the structured layers of Web applications and HTTP.
这是我们置于Cascading和Haooop之上的那一层东西的关键，可以让我们免于处理Hadoop输入格式。
This is a critical part of our layer of goodness on top of Cascading and Haooop that lets us weasel out of dealing with Hadoop input formats.
这是我们置于Cascading和Haooop之上的那一层东西的关键，可以让我们免于处理Hadoop输入格式。
This is a critical part of our layer of goodness on top of Cascading and Haooop that lets us weasel out of dealing with Hadoop input formats.
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