A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications

Information, Год журнала: 2024, Номер 15(12), С. 755 - 755

Опубликована: Ноя. 27, 2024

Deep learning (DL) has become a core component of modern artificial intelligence (AI), driving significant advancements across diverse fields by facilitating the analysis complex systems, from protein folding in biology to molecular discovery chemistry and particle interactions physics. However, field deep is constantly evolving, with recent innovations both architectures applications. Therefore, this paper provides comprehensive review DL advances, covering evolution applications foundational models like convolutional neural networks (CNNs) Recurrent Neural Networks (RNNs), as well such transformers, generative adversarial (GANs), capsule networks, graph (GNNs). Additionally, discusses novel training techniques, including self-supervised learning, federated reinforcement which further enhance capabilities models. By synthesizing developments identifying current challenges, insights into state art future directions research, offering valuable guidance for researchers industry experts.

Язык: Английский

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AI-Driven Business Intelligence and Financial Data Visualization: Transforming Modern Analytics

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Год журнала: 2025, Номер 11(1), С. 3461 - 3467

Опубликована: Фев. 25, 2025

The convergence of Artificial Intelligence (AI) with Business (BI) and Financial Data Visualization has fundamentally transformed how financial institutions approach data analysis decision-making. This comprehensive article examines the evolution impact AI-driven technologies in services, focusing on advanced analytics, visualization techniques, automated decision support systems. It explores machine learning, deep natural language processing capabilities have enhanced institutions' ability to process complex sets, detect patterns, generate actionable insights. investigates implementation frameworks necessary for successful AI integration, including technical architecture requirements governance best practices. further analyzes emerging trends challenges operations, particularly areas risk assessment, regulatory compliance, customer service. By examining both current applications future directions, this provides valuable insights into AI-powered solutions are reshaping sector's while highlighting importance balanced strategies that consider technological practical business needs.

Язык: Английский

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Leveraging artificial intelligence for enhanced decision-making in finance: trends and future directions

Journal of Accounting Literature, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

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Evaluating the Effectiveness of Optimized LSTM and XGBoost Classifiers in High-Frequency Futures Market Prediction

Advances in finance, accounting, and economics book series, Год журнала: 2025, Номер unknown, С. 357 - 386

Опубликована: Янв. 22, 2025

This study compares the performance of two machine learning models - Long Short-Term Memory (LSTM) networks and XGBoost in high-frequency intraday futures market forecasting. Using historical data from five major Chinese markets, research evaluates specialized classifiers terms prediction accuracy backtesting profits. The results show that LSTM outperforms volatile such as Crude Oil Silver Futures, with higher risk-adjusted returns. XGBoost, however, demonstrates better stability efficiency more stable markets like Soybean Rebar Futures. Backtesting suggest both can generate high-quality trading signals real-time, environments. offers insights into applying these for short-term predictions provides important implications strategies market.

Язык: Английский

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Classification of Object Shape by Machine Learning-Based Flow Maps Obtained with Laser Speckle Imaging

Опубликована: Янв. 1, 2024

Язык: Английский

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