循环神经网络

高阶对称循环神经网络的非线性辨识

Identification of nonlinear based on high order diagnoal recurrent neural network

基于雷达距离象序列的循环神经网络飞机目标识别

Aircraft target recognition based on radar range profile sequences using recurrent neural network

基于循环神经网络的宽带CDMA系统的功率控制

W-CDMA Systems Power Control Based on Circular Neural Networks

循环神经网络建模在非线性预测控制中的应用

Recurrent Neural Network Modeling and Its Application in Nonlinear Predictive Control

基于循环神经网络的多传感信息融合系统的应用

Multisense Information mixing System Based on Round Nerve Network

一种训练循环神经网络的演化算法

An evolutionary algorithm of constructs recurrent neural Networks

基于循环神经网络的语音识别模型

Speech Recognition Model Based on Recurrent Neural Networks

基于循环神经网络的传感器漂移补偿方法

An RNN-Based Approach to Compensating Sensor Drift

基于循环神经网络的辨识建模研究

Recurrent Neural Network-based Identification Modeling Study

本文讨论了一种基于循环神经网络的传感器补偿新方法。

An approach to compensating sensor drift based on recurrent neural networks is discussed in the paper .

其独特的结构，良好的短期记忆能力，方便的学习方法，不俗的非线性特性是以前循环神经网络所不可比的。

It appears special construction , excellent short-term memory , facile learning approach , stunning non-linearity that former RNN never done .

一个循环神经网络是一个特定的子集，最擅长处理长的数据序列，比如《冰与火之歌》前5部冗长的文本。

A recurrent neural network is a specific subclass , which works best when it comes to processing long sequences of data , such as lengthy text from five previous books .

目前循环神经网络语言模型的组句部分尚不具备处理包括设定题目在内的全局主题和特征的能力，而这种算法产生的句子在前后衔接得并不顺畅。

Currently , RNNLM is not capable of implementing global themes or features , such as a set topic , within its sentence generation . Each sentence produced by the algorithms doesn 't necessarily flow smoothly into the next .

谷歌目前正在和斯坦福大学及马赛诸塞大学合作，改进一项名为循环神经网络语言模型的人工智能技术（RNNLM）。这项技术普遍应用于机器翻译和图像捕捉的任务中。

Google is working with Stanford University and University of Massachusetts in the US to enhance the natural language skills of an AI technique called recurrent neural network language model ( RNNLM ) , which is used within machine translation and image captioning among other tasks .

软件工程师扎克·图特让一种名为循环神经网络的人工智能学习了马丁所写的《冰与火之歌》前五部约5000页的内容，然后利用该算法预测接下来的情节。

After feeding a type of artificial intelligence ( AI ) known as a recurrent neural network the roughly 5000 pages of Martin 's five previous books of " A Song of Ice and Fire , " software engineer Zack Thoutt has used the algorithm to predict what will happen next .

基于循环多层神经网络的联想存贮器

An Associative Memory Model Based on Recurrent Multi-layer Neural Networks

本文将循环前馈神经网络应用到容错系统的可靠性分析中，达到了简化容错系统可靠性分析与设计的目的。

What the paper introduces is a feed forward recursive NN used in the reliability analysis and the design of fault tolerant systems .

第一重GA循环用于优化神经网络结构，第二重GA循环进一步优化神经网络的连接权重。两重GA循环可以搜索确定用于故障诊断的最优神经网络。

The dual GA loops are designed for optimizing both topology and connection weights of the neural network and establishing global optimal neural network for fault diagnosis .

基于循环多层感知器神经网络的符号逻辑推理系统

Symbol Logic Inference System Based on Recurrent Multi-layer Perceptron Neural Networks

电厂水汽循环系统模糊神经网络故障诊断

Diagnostic method of power plant water vapor cycle system based on fuzzy neural networks

基于事例的推理循环中人工神经网络和遗传算法的4种应用模型

Four Application Models for Artificial Neural Network and Genetic Algorithm in Case Based Reasoning Cycle

介绍一种用循环多层感知器神经网络实现符号逻辑推理系统的方法。

A method of implementing symbol logic inference system using recurrent multilayer perceptron neural networks is presented in this paper .

水循环系统中基于神经网络的故障诊断

Fault Diagnosis Based on ANN in Water Circulation System

汽轮机功率与循环水系统功耗神经网络模型的建立及其应用

Modeling and application of ANN models for power output of steam turbine and power consumption in circulating water system

建立汽轮机发电功率和循环水系统功耗神经网络模型以确定不同工况下凝汽器真空运行最优值，实现对二者的模拟预测，有很高的精度和可靠性。

The neural network models for steam turbine power output and power needed in cycle cooling water system are established for the reference values of vacuum value of condenser and have a high precision and reliability .

利用该模型和建立的循环水系统功耗神经网络模型可确定不同工况下的真空运行最优值（基准值），为凝汽器真空运行最优值的确定提供了一个全新的方法。

With the established ANN models of steam turbine power output and the power needed in circulating water system , the optimum vacuum value ( reference value ) of condenser as well as the energy loss deviation of several main operation parameters from reference can be determined .