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Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network

This M.Tech Electrical Engineering topic focuses on Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network. It belongs to the Load Forecasting area within Power Systems. The work is suitable…

Load Forecasting
Abstract This M.Tech Electrical Engineering topic focuses on Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network. It belongs to the Load Forecasting area within Power Systems. The work is suitable for research topic selection, synopsis preparation, literature review, simulation planning, implementation design, result analysis, and dissertation documentation. Students can use this 2023-onward open-access research reference as the base paper and then customize the implementation using suitable datasets, MATLAB/Simulink, Python, power-system simulation tools, optimization methods, machine learning models, and performance metrics according to academic requirements.
Reference Paper Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network
Year 2023
Domain Power Systems
Sub-Domain Load Forecasting
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