The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials
Antimicrobial resistance (AMR) has become more of a concern in recent decades,
particularly in infections associated with global public health threats. The development of …
particularly in infections associated with global public health threats. The development of …
Tuning machine learning models using a group search firefly algorithm for credit card fraud detection
Recent advances in online payment technologies combined with the impact of the COVID-
19 global pandemic has led to a significant escalation in the number of online transactions …
19 global pandemic has led to a significant escalation in the number of online transactions …
[HTML][HTML] Novel hybrid firefly algorithm: An application to enhance XGBoost tuning for intrusion detection classification
The research proposed in this article presents a novel improved version of the widely
adopted firefly algorithm and its application for tuning and optimising XGBoost classifier …
adopted firefly algorithm and its application for tuning and optimising XGBoost classifier …
Multi-swarm algorithm for extreme learning machine optimization
There are many machine learning approaches available and commonly used today,
however, the extreme learning machine is appraised as one of the fastest and, additionally …
however, the extreme learning machine is appraised as one of the fastest and, additionally …
The adaboost approach tuned by firefly metaheuristics for fraud detection
The use of powerful classifiers is broad and the problem of fraud detection tends to benefit
from similar solutions as well. The problem in the digital age cannot be disregarded as the …
from similar solutions as well. The problem in the digital age cannot be disregarded as the …
Xgboost hyperparameters tuning by fitness-dependent optimizer for network intrusion detection
Network intrusion detection systems are frequently utilized for attack detection and network
protection. However, one of the frequent issues intrusion detection systems face is the false …
protection. However, one of the frequent issues intrusion detection systems face is the false …
The xgboost model for network intrusion detection boosted by enhanced sine cosine algorithm
N AlHosni, L Jovanovic, M Antonijevic… - … Conference on Image …, 2022 - Springer
Network intrusion detection systems are created with the purpose of detecting and
identifying threats and vulnerabilities of a target network. One of the most cardinal challenge …
identifying threats and vulnerabilities of a target network. One of the most cardinal challenge …
An emperor penguin optimizer application for medical diagnostics
Extreme gradient boosting (XGBoost) is a broadly adopted machine learning approach often
applied to classification problems. It outperforms many contemporary methods with high …
applied to classification problems. It outperforms many contemporary methods with high …
Training logistic regression model by enhanced moth flame optimizer for spam email classification
Spam email is a massive issue that bothers and consumes receivers' time and effort.
Because of its effectiveness in identifying mail as wanted or unwanted, machine learning …
Because of its effectiveness in identifying mail as wanted or unwanted, machine learning …
A novel method for covid-19 pandemic information fake news detection based on the arithmetic optimization algorithm
The problem of fake news on the Internet is not new. However, in the case of a global
pandemic, this kind of misinformation can be dangerous, confusing, and costly in terms of …
pandemic, this kind of misinformation can be dangerous, confusing, and costly in terms of …