A full-stack inflation-forecasting toolkit that pairs classical ARIMA diagnostics in Stata with an LSTM pipeline in Python. The project walks from raw CPI data ingestion and exploratory visualisation ...

This project implements CLAM (CNN-LSTM-AM), a hybrid deep learning model combining Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and an Attention Mechanism (AM) for ...

Abstract: Power load forecasting is the foundation of maintaining power grid stability, and can assist in decision-making to reduce operating costs. Fine-grained long sequence load forecasting ...

Abstract: A recent study showcased the efficacy of Long Short-Term Memory (LSTM) in significantly reducing average indoor localization Root Mean Square Error (RMSE ...