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Therefore, this study proposes a particle swarm optimized attention-LSTM prediction model (PSOA-LSTM). By introducing the attention mechanism into the LSTM structure to strengthen modeling of critical ...

In this brief, we investigate online training of long short term memory (LSTM) architectures in a distributed network of nodes, where each node employs an LSTM-based structure for online regression.

📈 LSTM-Based Stock Price Predictor (Built From Scratch in Python) This academic project implements a custom Long Short-Term Memory (LSTM) network from scratch in pure Python for next-day stock price ...

Accurate estimation of lithium-ion batteries’ state of health (SOH) is critical for ensuring the efficient, safe, and long-lasting operation of battery systems. To address the challenge of ...

The Long Short-Term Memory network or LSTM network is a type of recurrent neural network used in deep learning because very large architectures can be successfully trained. In this post, you will ...

A good alternative to Enc1 is Mix3 with balanced and slightly lower accuracy scores, both of them outperformed LSTM in terms of accuracy. The execution time for a single prediction was measured using ...