Exploring the frontiers of deep learning and natural language processing: A comprehensive overview of key challenges and emerging trends

Natural Language Processing Journal, Journal Year: 2023, Volume and Issue: 4, P. 100026 - 100026

Published: July 25, 2023

In the recent past, more than 5 years or so, DL especially large language models (LLMs) has generated extensive studies out of a distinctly average downturn field knowledge made up traditional society researchers. As result, (DL) is now so pervasive that its use widespread across body research related to machine learning computing. The rapid emergence and apparent dominance architectures over techniques on variety tasks have been truly astonishing witness. outperformed in areas, including natural processing (NLP), image analysis, understanding, translation, computer vision, speech processing, audio recognition, style imitation, computational biology. this study, aim explain rudiments DL, such as neural networks, convolutional deep belief various variants DL. study will explore how these applied NLP delve into underlying mathematics behind them. Additionally, investigate latest advancements NLP, while acknowledging key challenges emerging trends field. Furthermore, it discuss core component namely embeddings, from taxonomic perspective. Moreover, literature review be provided focusing application for six popular pattern recognition tasks: question answering, part tagging, named entity text classification, translation. Finally, demystify state-of-the-art libraries/frameworks available resources. outcome implication reveal LLMs face dealing with pragmatic aspects due their reliance statistical lack genuine understanding context, presupposition, implicature, social norms. provides comprehensive analysis current highlights significant obstacles developments. article potential enhance readers' subject matter.

Language: Английский

---

Achieving wind power and photovoltaic power prediction: An intelligent prediction system based on a deep learning approach

Energy, Journal Year: 2023, Volume and Issue: 283, P. 129005 - 129005

Published: Sept. 9, 2023

Language: Английский

---

Improving short-term offshore wind speed forecast accuracy using a VMD-PE-FCGRU hybrid model

Energy, Journal Year: 2024, Volume and Issue: 295, P. 131016 - 131016

Published: March 14, 2024

Language: Английский

---

Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization

Advances in Economics Management and Political Sciences, Journal Year: 2024, Volume and Issue: 91(1), P. 142 - 149

Published: June 19, 2024

In this paper, a time series algorithm based on Genetic Algorithm (GA) and Long Short-Term Memory Network (LSTM) optimization is used to forecast stock prices effectively, taking into account the trend of big data era. The are first analyzed by descriptive statistics, then model built trained tested dataset. After adjustment, mean absolute error (MAE) gradually decreases from 0.11 0.01 tends be stable, indicating that prediction effect close real value. results test set show optimized (GA)-Long able accurately predict prices, highly consistent with actual price trends values, strong generalization ability. MAE 2.41, MSE 9.84, RMSE 3.13, R2 0.87. This research result not only provides novel method, but also useful reference for financial market analysis using computer technology data.

Language: Английский

---

Enhancing prediction of dissolved oxygen over Santa Margarita River: Long short-term memory incorporated with multi-objective observer-teacher-learner optimization

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 70, P. 106969 - 106969

Published: Jan. 11, 2025

Language: Английский

---

Short-term solar radiation forecasting using hybrid deep residual learning and gated LSTM recurrent network with differential covariance matrix adaptation evolution strategy

Energy, Journal Year: 2023, Volume and Issue: 278, P. 127701 - 127701

Published: May 10, 2023

Language: Английский

---

An ensemble model for monthly runoff prediction using least squares support vector machine based on variational modal decomposition with dung beetle optimization algorithm and error correction strategy

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 629, P. 130558 - 130558

Published: Dec. 7, 2023

Language: Английский

---

Refined offshore wind speed prediction: Leveraging a two-layer decomposition technique, gated recurrent unit, and kernel density estimation for precise point and interval forecasts

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108435 - 108435

Published: April 25, 2024

Language: Английский

---

Multivariate GRU and LSTM models for wave forecasting and hindcasting in the southern Caspian Sea

Ocean Engineering, Journal Year: 2024, Volume and Issue: 298, P. 117193 - 117193

Published: Feb. 25, 2024

Language: Английский

---

A transportation Revitalization index prediction model based on Spatial-Temporal attention mechanism

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 61, P. 102519 - 102519

Published: April 3, 2024

Language: Английский

---