Design of IRT-based adaptive learning management system

A reverse transmission calculation of self adapting learning rate with momentum gradient reduction is described in the paper against the problems of slow convergence and easy trapping into smallest spot.

针对BP网络学习收敛速度慢和易陷入局部最小点的不足，提出了一种自适应学习速率动量梯度下降反向传播算法对BP神经网络进行训练。

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The application of fuzzy adaptive learning control ( FALCON) in milling-classification operation system

模糊自适应学习控制（FALCON）在磨矿分级系统中的应用

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By the use of the additional momentum method and adaptive learning rate of BP network, a neural network model was established to calculate the speed of tidal bore.

运用BP网络附加动量法和自适应学习速率法，建立神经网络模型，模拟计算涌潮波速。

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The improved BP algorithms based on adaptive parameters adjustment and error contracting gradually are presented, which are applied successfully to fault diagnosis of steam-turbine generator unit.

提出了自适应学习率及动量因子的BP神经网络算法和误差逼近度渐近收缩学习的BP神经网络算法，并将其应用于汽轮发电机组振动故障诊断与识别。

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At last, a kind of BP algorithm with adaptive learning rate is evaluated and compared with standard BP algorithm by XOR problem.

最后结合XOR问题把一种自适应学习率BP算法和标准BP算法进行了比较和评价。

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To improve the networks' classification effect and train speed, the additive momentum and self-adaptive – study-rate adjustment method are adopted further to improve traditional BP algorithm.

为了提高网络的分类效果以及训练速度，采用了附加动量法和自适应学习速率调整法对BP算法进行了改进。

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Artificial neural network is a nonlinear system which simulates biological neural systems. It has powerful parallel processing, distributed storage, adaptive learning, a high degree of fault-tolerant capability.

人工神经网络（Artificial neural network，ANN）是模拟生物神经系统的非线性系统，具有强大的并行处理、分布式存储、自适应学习、高度容错的能力。

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Because of the existing problems of general BP algorithm, operation speed of BP Network is improved by using adaptive learning rate and additional item.

针对普通BP算法存在的问题，采用自适应学习率及附加动量项的方法进行改进，以提高BP网络的运算速度。

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Realize Adaptive Learning in E-learning System

实现E-learning平台中的学生自适应学习

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The neural network has the ability of self adaptive learning and remembering, and the three-layer BP network has wide application.

人工神经网络具有自适应学习和记忆能力，尤其是3层BP网络模型。

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An Adaptive Learning Algorithm for T-S Fuzzy Model Based RBF Neural Network

一种基于T-S模糊模型的RBF神经网络的自适应学习算法

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Compared to the standard BP, this algorithm integrated the additional momentum method with the adaptive learning rate method.

与标准BP算法比较，该系统通过结合附加动量法和自适应学习速率形成新的BP改进算法。

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BP neural network use adaptive learning rate momentum algorithm has fast convergence rate and high error precision.

BP神经网络采用收敛速度较快和误差精度较高的动量&自适应学习速率调整算法。

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This algorithm enhances the convergence speed by using additional momentum item and taking auto-adapted study rate measure.

通过附加动量项、采取自适应学习率措施等方法，加快了BP网络的收敛速度。

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BP Network Algorithm with Self-adaptive Learning Rate and Its Use in the Fuzzy Diagnosis of Turbogenerator Failures

自适应学习率的BP网络算法及其在汽轮发电机组故障模糊诊断中的应用

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BP Neural Network with Adaptive Learning Rate

BP网络自适应学习率研究

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A Self-adaptive Learning Algorithm for BP Network

BP网络的快速自适应学习算法

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The system adopts back-propagation learning algorithm with momentum.

神经网络采用带有动量项和自适应学习率的反向传播算法（BP）进行训练。

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Research of improved BP algorithm based on self-adaptive learning rate

基于自适应学习速率的改进型BP算法研究

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Momentum-Adaptive-Learning-Rate BP Algorithm Compared With the Standard BP Algorithm and Its Application

神经网络动量-自适应学习率BP算法与BP算法的性能比较及其应用

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