ABSTRACT: This project aimed to assess the performance of attention extended LSTM and Gated Recurrent Unit models in stock price movement forecasting. The traditional models suffer from the challenges ...

Real-time anomaly detection on NYC taxi demand data using an LSTM Encoder-Decoder model, Kafka streaming, Spark Structured Streaming, and a Dash visualization dashboard. Based on Malhotra et al. (2016 ...

This research paper presents a proactive approach to congestion control in IoT networks using an encoder–decoder LSTM (ED-LSTM) model to predict packet loss ratios ahead of time. By forecasting ...

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...

Abstract: With the development of vehicular network technology, the prediction of vehicle power demand has become significant in intelligent transportation systems and energy consumption optimization.

Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral ...

Abstract: Automatic highlighting from texts is an abstractive summarization problem that is frequently focused on in natural language processing. In encoder-decoder architectures, developed for ...

The RF803E encoder and RF803D decoder deliver a chipset that is convenient to use and incorporates value-added features such as efficient encoding for optimum radio range and provision for an LED ...