Papers

1. Machine Learning with IIoT
2. Deep Learning -based forecasting approach in Smart Grids with micro-clustering and Bi-directional LSTM Network
3. Energy Load Clustering in Smart Grid: Methodologies, Applications and Future Trends
4. Continue survey of related works to gain understanding of research works in IIoT and IoT

Last Week's Progress

1. Attended Lectures
2. Submitted Reports and Assignments
3. Surveyed paper on Smart Grids and Machine Learning

This Week Todo's

1. Attend Lectures
2. Continue with review of Deep Learning -based forecasting approach in Smart Grids with micro-clustering and Bi-directional LSTM Network and Energy Load Clustering in Smart Grid: Methodologies, Applications and Future Trends
3. Continue with Machine Learning

Project Progress

Smart Grid Energy Forecasting using LSTM Model

Last Week's Project

1. Reviewed paper on Deep Learning -based forecasting approach in Smart Grids with micro-clustering and Bi-directional LSTM Network
Worked on PPT for Presentation

This Week's Project

1. Continue with review of Continue with review of Deep Learning -based forecasting approach in Smart Grids with micro-clustering and Bi-directional LSTM Network and other related literatures

Monthly Goals

1. To get familiar with Latex Environment
2. Continue survey of Papers on Smart Grid Energy Project
3. Continue with Machine Learning

Annual Goals

1. To attend at least one NSL approved Domestic Conference
2. To attend at least one International Conference
3. Submit or Publish at least two International Journal Papers