Being one of the largest social media platforms, Twitter has a diverse community collaborating on multitude ideas. With large amounts data being generated and collected every day, it is perfect platform to implement machine learning algorithms analyze information in different tweets. A recurrent Neural Network (RNN) specific algorithm that used solve problems involving sequential such as texts ...

This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in discrete time. Its architecture is based on a recurrent neural network (RNN), which is extended by an additional control network. The latter has the particular task to learn the optimal policy. This method has the advan...

A deep learning approach to reinforcement learning led to a general learner able to train on visual input to play a variety of arcade games at the human and superhuman levels. Its creators at the Google DeepMind’s team called the approach: Deep Q-Network (DQN). We present an extension of DQN by “soft” and “hard” attention mechanisms. Tests of the proposed Deep Attention Recurrent Q-Network (DAR...

In this article, we present a not fully connected recurrent network applied to the problem of load forecasting. Although many authors have pointed out that Recurrent Networks were able to modelize NARMAX process (Non linear Auto Regressive Moving Average with eXogeneous variables), we present a constructing scheme for the MA part. In addition we present a modification of the learning step which...

This paper presents a study on computational promise of Simultaneous Recurrent Networks to solve large-scale optimization problems. Specifically the performance of the network for solving Traveling Salesman Problem is addressed and analyzed. A recurrent and trainable neural network, Simultaneous Recurrent Network, with Recurrent Backpropagation training algorithm is employed to address difficul...

To maintain the security of vulnerable network is most essential thing in system; for protection or to eliminate unauthorized access internal as well external connections, various architectures have been suggested. Various existing approaches has developed different detect suspicious attacks on victimized machines; nevertheless, an user develops malicious behaviour and gains victim machines via...

Neural networks can be classified into recurrent and nonrecurrent categories. Nonrecurrent (feedforward) networks have no feedback elements; the output is calculated directly from the input through feedforward connections. In recurrent networks the output depends not only on the current input to the network, but also on the current or previous outputs or states of the network. For this reason, ...