SyedHasnat/Papers
Contains the code for the paper "Multi-Horizon Short-Term Load Forecasting Using Hybrid of LSTM and Modified Split Convolution"
This project helps power system operators and energy analysts accurately predict electricity demand over short periods. It takes historical load data, often alongside correlated features like temperature, and produces single-step or multi-step forecasts of future electricity loads. The ideal user is an operations engineer or energy planner responsible for managing grid stability and resource allocation.
No commits in the last 6 months.
Use this if you need highly accurate, multi-horizon short-term electricity load forecasts for operational planning, unit commitment, or demand response management.
Not ideal if you are looking for long-term strategic energy planning, real-time control, or forecasting for domains other than electricity load.
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11
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4
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 28, 2023
Commits (30d)
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