Scientific Research Publishing

Intelligent Agents in Cybersecurity: Deep Learning to Analyze User Behavior Applying ()

The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...
GitHub

[RNN] LSTM model crashing during conversion to int8x8 tflite

import numpy as np import tensorflow as tf print(f"TensorFlow: {tf.__version__}") # Load model (handle legacy LSTM parameter) class CustomLSTM(tf.keras.layers.LSTM ...
Frontiers

A hybrid LSTM–transformer model for accurate remaining useful life prediction of lithium-ion batteries

With the widespread application of lithium-ion batteries in electric vehicles and energy storage systems, health monitoring and remaining useful life prediction have become critical components of ...
Frontiers

A hybrid VMD-LSTM-SVR model for landslide prediction

Landslides are one of the most prevalent natural geological disasters, causing significant economic losses, damaging public environments, and posing severe threats to human lives. Landslide ...
Autoblog

Tesla’s Cheap Model Y Strips Out Everything You’d Actually Want

View post: Would You Be At Fault for Rear-Ending a Car in the Rain If Its Lights Were Off? I Ask A Lawyer. At the front of the car, the front fascia and headlight assembly have been revised, with the ...
Carscoops

You’ll Notice What’s Gone From Tesla’s New Budget EV Before You Even Step Inside

Tesla sales are in free-fall and the automaker doesn’t have any genuinely new product on the horizon ready to save the day. Instead, as Elon Musk himself hinted, Tesla is stripping features from the ...
InfoWorld

Python-powered AI agents are here

Python has been the language of data science since before machine learning was trendy, and now you can use it for building AI agents, too. Get the scoop on the new Google Agent Development Kit and ...
IEEE

The CNN-SE-LSTM Model for Phase Interferometer Ambiguity Resolution

Abstract: To address the phase ambiguity problem arising from baseline extension in phase interferometer for improving direction-finding accuracy, this paper proposes a CNN-SE-LSTM model-based phase ...
thecooldown

Researchers develop game-changing tool to predict deadly natural disasters: 'Of paramount importance'

A recent study published in the Water Resources Research journal discussed using a new deep learning framework — known as Long Short-Term Memory Station Approximated Models, or LSTM-SAM — to predict ...
IEEE

A Variational Inference-Based LSTM-Enhanced Deep Neural Model for Sequential Recommendations

Abstract: Long Short-Term Memory (LSTM) networks are particularly useful in recommender systems since user preferences change over time. Unlike traditional recommender models which assume static ...
Scientific Research Publishing

Hybrid PINN-LSTM Model for River Temperature Prediction: A Physics-Informed Deep Learning Approach ()

This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...