A QoS classifier based on machine learning for next-generation optical communication
Code classification is essential nowadays, as determining the transmission code at the
receiver side is a challenge. A novel algorithm for fixed right shift (FRS) code may be …
receiver side is a challenge. A novel algorithm for fixed right shift (FRS) code may be …
Wireless Communication Channel Scenarios: Machine-learning-based identification and performance enhancement
Wireless communication channel scenario classification is crucial for new modern wireless
technologies. Reducing the time consumed by the data preprocessing phase for such …
technologies. Reducing the time consumed by the data preprocessing phase for such …
5G and beyond: Channel classification enhancement using VIF-driven preprocessing and machine learning
The classification of wireless communication channel scenarios is vital for modern wireless
technologies. Efficient data preprocessing for identification, especially starting from 5G and …
technologies. Efficient data preprocessing for identification, especially starting from 5G and …
Second-order fused lasso algorithm for radio tomographic imaging
Radio tomographic imaging (RTI) is one of the device-free localization (DFL) approaches
used to identify obstacles in a wireless network by using the attenuation information of radio …
used to identify obstacles in a wireless network by using the attenuation information of radio …
ERDeR: The combination of statistical shrinkage methods and ensemble approaches to improve the performance of deep regression
Ensembling is a powerful technique to obtain the most accurate results. In some cases, the
large number of learners in ensemble learning mostly increases both computational load …
large number of learners in ensemble learning mostly increases both computational load …
Harnessing the power of ML for robust SISO and MIMO FSO communication systems in fog weather
Abstract This study examines Free Space Optical (FSO) communication's performance in
different fog conditions, focusing on Single-Input Single-Output (SISO) and Multiple-Input …
different fog conditions, focusing on Single-Input Single-Output (SISO) and Multiple-Input …
[PDF][PDF] Wireless Communication Channel Scenarios: Machine-Learning-Based Identification and Performance Enhancement. Electronics 2022, 11, 3253
Wireless communication channel scenario classification is crucial for new modern wireless
technologies. Reducing the time consumed by the data preprocessing phase for such …
technologies. Reducing the time consumed by the data preprocessing phase for such …
[PDF][PDF] Deep Autoencoder Learning Features for Classifying Peptides Data as Recombinant Bacterial Material Using PTVPSO-Deep ELM Algorithm
Codon codes directly in the form of vector or 3D molecular to support feature learning often
impede machine learning reading for the epitope classification process in extracting feature …
impede machine learning reading for the epitope classification process in extracting feature …
Enhanced Weak Signal Detection Using SVM Based Correlation Algorithm
SL Kramer - 2024 - vtechworks.lib.vt.edu
Traditional signal detection algorithms are often robust and are typically sufficient for high
SNR data. However, the assumptions behind these methods begin to fall apart when signal …
SNR data. However, the assumptions behind these methods begin to fall apart when signal …
[PDF][PDF] Enhancing Hydroponic Farming with Machine Learning: Growth Prediction and Anomaly Detection
A Métwalli, O Shalash, A Elhefnya, N Rezka… - researchgate.net
Artificial Intelligence has revolutionized precision agriculture, particularly in optimizing
hydroponic farming. Our study targets Batavia lettuce cultivation, utilizing environmental and …
hydroponic farming. Our study targets Batavia lettuce cultivation, utilizing environmental and …