A review on big data based on deep neural network approaches

M Rithani, RP Kumar, S Doss - Artificial Intelligence Review, 2023 - Springer
Big data analytics has become a significant trend for many businesses as a result of the
daily acquisition of enormous volumes of data. This information has been gathered because …

A mini-review of machine learning in big data analytics: Applications, challenges, and prospects

IK Nti, JA Quarcoo, J Aning… - Big Data Mining and …, 2022 - ieeexplore.ieee.org
The availability of digital technology in the hands of every citizenry worldwide makes an
available unprecedented massive amount of data. The capability to process these gigantic …

Flight trajectory prediction enabled by time-frequency wavelet transform

Z Zhang, D Guo, S Zhou, J Zhang, Y Lin - Nature Communications, 2023 - nature.com
Accurate flight trajectory prediction is a crucial and challenging task in air traffic control,
especially for maneuver operations. Modern data-driven methods are typically formulated as …

Efficient automated disease diagnosis using machine learning models

N Kumar, N Narayan Das, D Gupta… - Journal of healthcare …, 2021 - Wiley Online Library
Recently, many researchers have designed various automated diagnosis models using
various supervised learning models. An early diagnosis of disease may control the death …

[HTML][HTML] Machine learning and mixed reality for smart aviation: Applications and challenges

Y Jiang, TH Tran, L Williams - Journal of Air Transport Management, 2023 - Elsevier
The aviation industry is a dynamic and ever-evolving sector. As technology advances and
becomes more sophisticated, the aviation industry must keep up with the changing trends …

Research on the natural language recognition method based on cluster analysis using neural network

G Li, F Liu, A Sharma, OI Khalaf… - Mathematical …, 2021 - Wiley Online Library
Withthe technological advent, the clustering phenomenon is recently being used in various
domains and in natural language recognition. This article contributes to the clustering …

Complex-valued networks for automatic modulation classification

Y Tu, Y Lin, C Hou, S Mao - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
Deep learning (DL) has been recognized as an effective solution for automatic modulation
classification (AMC). However, most recent DL based AMC works are based on real-valued …

LightAMC: Lightweight automatic modulation classification via deep learning and compressive sensing

Y Wang, J Yang, M Liu, G Gui - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
Automatic modulation classification (AMC) is an promising technology for non-cooperative
communication systems in both military and civilian scenarios. Recently, deep learning (DL) …

A CNN-LSTM framework for flight delay prediction

Q Li, X Guan, J Liu - Expert Systems with Applications, 2023 - Elsevier
Flight delay prediction has become one of the most critical topics in intelligent aviation
systems due to its essential role in flight scheduling, airline planning, and airport operation …

Vehicle assisted computing offloading for unmanned aerial vehicles in smart city

M Dai, Z Su, Q Xu, N Zhang - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Smart city emerges a promising paradigm for improving operational efficiency of city and
comfort of people. With embedded multi-sensors, Unmanned Aerial Vehicles (UAVs) hold …