Microgrid Group Control Method Based on Deep Learning under Cloud Edge Collaboration

Deep Neural Network-Based Method for Economic Dispatch in Microgrid

Action-based collaboration analysis for group learning

In computer-supported collaborative learning, technology is used for enabling constructive approaches to learning as well as group interaction, particularly in distant and asynchronous situations. Recently, shared workspace systems have been developed that allow for jointly constructing conceptual problem representations by means of graphical structures and direct manipulation as well as the in...

Efficient Method Based on Combination of Deep Learning Models for Sentiment Analysis of Text

People's opinions about a specific concept are considered as one of the most important textual data that are available on the web. However, finding and monitoring web pages containing these comments and extracting valuable information from them is very difficult. In this regard, developing automatic sentiment analysis systems that can extract opinions and express their intellectual process has ...

Operation Scheduling of MGs Based on Deep Reinforcement Learning Algorithm

: In this paper, the operation scheduling of Microgrids (MGs), including Distributed Energy Resources (DERs) and Energy Storage Systems (ESSs), is proposed using a Deep Reinforcement Learning (DRL) based approach. Due to the dynamic characteristic of the problem, it firstly is formulated as a Markov Decision Process (MDP). Next, Deep Deterministic Policy Gradient (DDPG) algorithm is presented t...

SPORC: Group Collaboration using Untrusted Cloud Resources

Cloud-based services are an attractive deployment model for user-facing applications like word processing and calendaring. Unlike desktop applications, cloud services allow multiple users to edit shared state concurrently and in real-time, while being scalable, highly available, and globally accessible. Unfortunately, these benefits come at the cost of fully trusting cloud providers with potent...