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 …
Novel improved salp swarm algorithm: An application for feature selection
We live in a period when smart devices gather a large amount of data from a variety of
sensors and it is often the case that decisions are taken based on them in a more or less …
sensors and it is often the case that decisions are taken based on them in a more or less …
[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 …
Artificial neural networks hidden unit and weight connection optimization by quasi-refection-based learning artificial bee colony algorithm
Artificial neural networks are one of the most commonly used methods in machine learning.
Performance of network highly depends on the learning method. Traditional learning …
Performance of network highly depends on the learning method. Traditional learning …
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 …
Hunger games pattern search with elite opposite-based solution for solving complex engineering design problems
The hunger games search (HGS) algorithm is designed to tackle optimization problems,
however, issues such as local minimum stagnation and immature convergence hinder its …
however, issues such as local minimum stagnation and immature convergence hinder its …
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
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 …
[HTML][HTML] Decomposition aided attention-based recurrent neural networks for multistep ahead time-series forecasting of renewable power generation
Renewable energy plays an increasingly important role in our future. As fossil fuels become
more difficult to extract and effectively process, renewables offer a solution to the ever …
more difficult to extract and effectively process, renewables offer a solution to the ever …