Hybrid CNN and XGBoost model tuned by modified arithmetic optimization algorithm for COVID-19 early diagnostics from X-ray images
Develo** countries have had numerous obstacles in diagnosing the COVID-19 worldwide
pandemic since its emergence. One of the most important ways to control the spread of this …
pandemic since its emergence. One of the most important ways to control the spread of this …
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 …
MBTFCN: A novel modular fully convolutional network for MRI brain tumor multi-classification
Brain tumors represent one of the most challenging tumors that affect the human body due to
the nonlinear characteristics of their morphological and textural appearance. Automated …
the nonlinear characteristics of their morphological and textural appearance. Automated …
Addressing feature selection and extreme learning machine tuning by diversity-oriented social network search: an application for phishing websites detection
Feature selection and hyper-parameters optimization (tuning) are two of the most important
and challenging tasks in machine learning. To achieve satisfying performance, every …
and challenging tasks in machine learning. To achieve satisfying performance, every …
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 …
Cloud computing load prediction by decomposition reinforced attention long short-term memory network optimized by modified particle swarm optimization algorithm
Computer resources provision over the internet resulted in the wide spread usage of cloud
computing paradigm. With the use of such resources come certain challenges that can …
computing paradigm. With the use of such resources come certain challenges that can …