In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...

Abstract: Discrete time-variant equation systems represent a typical and complex problem across various disciplines. With the increasing complexity of systems in various fields, traditional methods ...

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...

1 State Grid Wuxi Power Supply Company, Wuxi, China 2 Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China The monitoring condition of the cable laying conveyor, such ...

This project uses sentiment analysis using tweepy and textblob and Deep Learning model, Long-Short Term Memory (LSTM) Recurrent neural network (RNN) algorithm to predict closing prices of stocks. This ...

This project uses sentiment analysis using tweepy and textblob and Deep Learning model, Long-Short Term Memory (LSTM) Recurrent neural network (RNN) algorithm to predict closing prices of stocks.

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...