深度学习(deep neural network)是机器学习的分支,是一种试图使用包含复杂结构或由多重非线性变换构成的多个处理层对数据进行高层抽象的算法。 --Wiki 在人工智能领域,有一个方法叫机器学习。在机器学习这个方法里,有一类算法叫神经网络。神经网络如下图所示: 上图中每个圆圈都是一个神经元,每条线表示神经元之间的连...
autonomous driving, and natural language processing. However, unlike biological brains who tackle similar problems in a very efficient manner, DL algorithms require a large number of trainable parameters, making them energy-intensive and
logits = tf.layers.dense(hidden2, n_outputs, name="outputs") Fine-Tuning Neural Network Hyperparameters 神经网络的灵活性同样也是它最主要的缺点,因为有太多的参数可以调整,比方说,网络拓扑,层数,每一层神经元的个数,每一层的激活函数,权值初始化等等很多参数,那么如何来获取最优的参数呢? 当然,我们可以...
prediction (of more complex objects). The neural net learns by varying the weights or parameters of a network so as to minimize the difference between the predictions of the neural network and the desired values. This phase where the artificial neural network learns from the data is called ...
深度学习(deep neural network)是机器学习的分支,是一种试图使用包含复杂结构或由多重非线性变换构成的多个处理层对数据进行高层抽象的算法。 --Wiki 在人工智能领域,有一个方法叫机器学习。在机器学习这个方法里,有一类算法叫神经网络。神经网络如下图所示: ...
Neural networks can be supervised or unsupervised in nature. The learning is supervised when the trained model is validated by a separate test set. The training set helps in fitting weight parameters and decides the number of hidden layers in the network architecture. ANN methods have been proven...
Neural-Network-Based Parameter Estimations of Induction Motors The goal of this paper is to use artificial neural networks (ANNs) for online identification of induction-motor parameters. ANNs such as feedforward and re... HA Toliyat,M Wlas,Z Krzemiriski - 《IEEE Transactions on Industrial ...
neural network required target response is set at the output and from the difference of the desired response along with the output of real system an error is obtained. The error information is fed back to the system and it makes many adjustments to their parameters in a systematic order which...
Kulaksiz, A.A.: ANFIS-based estimation of PV module equivalent parameters: application to a stand-alone PV system with MPPT controller. Turk. J. Electr. Eng. Comput. Sci. 21, 2127–2140 (2013) Article Google Scholar Roger, J.-S.J.: ANFIS: adaptive-network-based fuzzy inference system...
(L = 5\), since there are at least 5 measurements for every sub-phase after the interpolation. The neural network parameters used in our experiments are\(\alpha =10^{-6}\)and\(\# epochs = 10\). Table3shows the mean and standard deviation of classification accuracies obtained with ...