Artificial neural networks-based machine learning for wireless networks: A tutorial

M Chen, U Challita, W Saad, C Yin… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
In order to effectively provide ultra reliable low latency communications and pervasive
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …

Recent advances in artificial intelligence for wireless internet of things and cyber–physical systems: A comprehensive survey

BA Salau, A Rawal, DB Rawat - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Advances in artificial intelligence (AI) and wireless technology are driving forward the large
deployment of interconnected smart technologies that constitute cyber–physical systems …

Federated learning for UAVs-enabled wireless networks: Use cases, challenges, and open problems

B Brik, A Ksentini, M Bouaziz - IEEE Access, 2020 - ieeexplore.ieee.org
The use of Unmanned Aerial Vehicles (UAVs) for wireless networks is rapidly growing as
key enablers of new applications, including: surveillance and monitoring, military, delivery of …

[PDF][PDF] Bibliography of self-organizing map (SOM) papers: 1998–2001 addendum

M Oja, S Kaski, T Kohonen - Neural computing surveys, 2003 - researchgate.net
Abstract The Self-Organizing Map (SOM) algorithm has attracted a great deal of interest
among researches and practitioners in a wide variety of fields. The SOM has been analyzed …

ANN prediction of performance and emissions of CI engine using biogas flow variation

A Mandal, H Cho, BS Chauhan - Energies, 2021 - mdpi.com
Compression ignition (CI) engines are popular in the transport sector because of their high
compression ratio. However, in recent years, it has become a major concern from an …

Classification and regression trees for epidemiologic research: an air pollution example

K Gass, M Klein, HH Chang, WD Flanders… - Environmental …, 2014 - Springer
Background Identifying and characterizing how mixtures of exposures are associated with
health endpoints is challenging. We demonstrate how classification and regression trees …

Multi-time scale optimal dispatch for the wind power integrated system with demand response of data centers based on neural network-based model predictive control

O Han, T Ding, C Mu, Y Huang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Data centers (DCs) are energy consumers with high electricity demand. Due to their Spatio-
temporal demand response (DR) capabilities, DCs are crucial DR participants. In view of the …

Fast and robust learning in spiking feed-forward neural networks based on intrinsic plasticity mechanism

A Zhang, H Zhou, X Li, W Zhu - Neurocomputing, 2019 - Elsevier
In this paper, the computational performance of a Spiking Feed-forward Neural Network
(SFNN) is investigated based on a brain-inspired Intrinsic Plasticity (IP) mechanism, which is …

Prediction of benzo[a]pyrene content of smoked sausage using back‐propagation artificial neural network

Y Chen, K Cai, Z Tu, W Nie, T Ji, B Hu… - Journal of the …, 2018 - Wiley Online Library
BACKGROUND Benzo [a] pyrene (BaP), a potent mutagen and carcinogen, is reported to be
present in processed meat products and, in particular, in smoked meat. However, few …

Modeling and inverse controller design for an unmanned aerial vehicle based on the self-organizing map

J Cho, JC Principe, D Erdogmus… - IEEE Transactions on …, 2006 - ieeexplore.ieee.org
The next generation of aircraft will have dynamics that vary considerably over the operating
regime. A single controller will have difficulty to meet the design specifications. In this paper …