Anomaly-based intrusion detection system for IoT application

M Bhavsar, K Roy, J Kelly, O Olusola - Discover Internet of things, 2023 - Springer
Abstract Internet-of-Things (IoT) connects various physical objects through the Internet and it
has a wide application, such as in transportation, military, healthcare, agriculture, and many …

Lung cancer prediction and classification based on correlation selection method using machine learning techniques

DM Abdullah, AM Abdulazeez… - Qubahan Academic …, 2021 - journal.qubahan.com
Lung cancer is one of the leading causes of mortality in every country, affecting both men
and women. Lung cancer has a low prognosis, resulting in a high death rate. The computing …

Energy consumption of electric vehicles: Analysis of selected parameters based on created database

M Mądziel, T Campisi - Energies, 2023 - mdpi.com
Electric vehicles in a short time will make up the majority of the fleet of vehicles used in
general. This state of affairs will generate huge sets of data, which can be further …

Network intrusion detection using oversampling technique and machine learning algorithms

HA Ahmed, A Hameed, NZ Bawany - PeerJ Computer Science, 2022 - peerj.com
The expeditious growth of the World Wide Web and the rampant flow of network traffic have
resulted in a continuous increase of network security threats. Cyber attackers seek to exploit …

Double handed dynamic Turkish Sign Language recognition using Leap Motion with meta learning approach

Z Katılmış, C Karakuzu - Expert Systems with Applications, 2023 - Elsevier
Sign language is one of the most important communication tools for hearing impaired
people. In this study, the recognition of two-handed dynamic words in Turkish Sign …

[PDF][PDF] Energy Consumption of Electric Vehicles: Analysis of Selected Parameters Based on Created Database. Energies 2023, 16, 1437

M Mądziel, T Campisi - 2023 - academia.edu
Electric vehicles in a short time will make up the majority of the fleet of vehicles used in
general. This state of affairs will generate huge sets of data, which can be further …

Studying the effects of feature scaling in machine learning

H Alshaher - 2021 - search.proquest.com
Feature scaling in machine learning is an important step during the pre-processing of data.
Feature scaling in machine learning transforms numeric features of a dataset to improve the …

Feature Selection Correlation-Based pada Prediksi Nasabah Bank Telemarketing untuk Deposito

AN Puteri, A Arizal, AD Achmad - MATRIK: Jurnal …, 2021 - journal.universitasbumigora.ac.id
Pre-processing merupakan tahap yang penting dalam melakukan klasifikasi data. Pre-
processing berguna untuk mempersiapkan data sehingga teknik klasifikasi yang diterapkan …

Earthquake prediction in california using feature selection techniques

J Roiz-Pagador, A Chacon-Maldonado, R Ruiz… - … Conference on Soft …, 2022 - Springer
Predicting the magnitude of earthquakes is of vital importance and, at the same time, of
extreme complexity, where each attribute contributes differently in the process, even …

Impacts of Data Preprocessing and Hyperparameter Optimization on the Performance of Machine Learning Models Applied to Intrusion Detection Systems

MG Lima, A Carvalho, JG Álvares, CE Chagas… - arXiv preprint arXiv …, 2024 - arxiv.org
In the context of cybersecurity of modern communications networks, Intrusion Detection
Systems (IDS) have been continuously improved, many of them incorporating machine …