A mini-review of machine learning in big data analytics: Applications, challenges, and prospects
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 …
available unprecedented massive amount of data. The capability to process these gigantic …
A review on big data based on deep neural network approaches
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 …
daily acquisition of enormous volumes of data. This information has been gathered because …
Flight trajectory prediction enabled by time-frequency wavelet transform
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 …
especially for maneuver operations. Modern data-driven methods are typically formulated as …
Research on the natural language recognition method based on cluster analysis using neural network
Withthe technological advent, the clustering phenomenon is recently being used in various
domains and in natural language recognition. This article contributes to the clustering …
domains and in natural language recognition. This article contributes to the clustering …
Efficient automated disease diagnosis using machine learning models
Recently, many researchers have designed various automated diagnosis models using
various supervised learning models. An early diagnosis of disease may control the death …
various supervised learning models. An early diagnosis of disease may control the death …
LightAMC: Lightweight automatic modulation classification via deep learning and compressive sensing
Automatic modulation classification (AMC) is an promising technology for non-cooperative
communication systems in both military and civilian scenarios. Recently, deep learning (DL) …
communication systems in both military and civilian scenarios. Recently, deep learning (DL) …
Complex-valued networks for automatic modulation classification
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 …
classification (AMC). However, most recent DL based AMC works are based on real-valued …
Deep reinforcement learning based mobile edge computing for intelligent Internet of Things
R Zhao, X Wang, J Xia, L Fan - Physical Communication, 2020 - Elsevier
In this paper, we investigate mobile edge computing (MEC) networks for intelligent internet
of things (IoT), where multiple users have some computational tasks assisted by multiple …
of things (IoT), where multiple users have some computational tasks assisted by multiple …
Vehicle assisted computing offloading for unmanned aerial vehicles in smart city
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 …
comfort of people. With embedded multi-sensors, Unmanned Aerial Vehicles (UAVs) hold …
Intelligent intrusion detection based on federated learning aided long short-term memory
Deep learning based intelligent intrusion detection (IID) methods have been received
strongly attention for computer security protection in cybersecurity. All these learning models …
strongly attention for computer security protection in cybersecurity. All these learning models …