Binary Horse herd optimization algorithm with crossover operators for feature selection
This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …
An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …
IoT data analytics in dynamic environments: From an automated machine learning perspective
With the wide spread of sensors and smart devices in recent years, the data generation
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …
Boolean Particle Swarm Optimization with various Evolutionary Population Dynamics approaches for feature selection problems
In the feature selection process, reaching the best subset of features is considered a difficult
task. To deal with the complexity associated with this problem, a sophisticated and robust …
task. To deal with the complexity associated with this problem, a sophisticated and robust …
An enhanced binary artificial rabbits optimization for feature selection in medical diagnosis
This paper proposes binary versions of artificial rabbits optimization (ARO) for feature
selection (FS) with medical diagnosis data. ARO is a recent swarm-based optimization …
selection (FS) with medical diagnosis data. ARO is a recent swarm-based optimization …
BHHO-TVS: A binary harris hawks optimizer with time-varying scheme for solving data classification problems
Data classification is a challenging problem. Data classification is very sensitive to the noise
and high dimensionality of the data. Being able to reduce the model complexity can help to …
and high dimensionality of the data. Being able to reduce the model complexity can help to …
Diagnosis of obstructive sleep apnea using feature selection, classification methods, and data grouping based age, sex, and race
Obstructive sleep apnea (OSA) is a prevalent sleep disorder that affects approximately 3–
7% of males and 2–5% of females. In the United States alone, 50–70 million adults suffer …
7% of males and 2–5% of females. In the United States alone, 50–70 million adults suffer …
Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis
Zero-Touch Networks (ZTNs) represent a state-of-the-art paradigm shift towards fully
automated and intelligent network management, enabling the automation and intelligence …
automated and intelligent network management, enabling the automation and intelligence …
An enhanced evolutionary student performance prediction model using whale optimization algorithm boosted with sine-cosine mechanism
The students' performance prediction (SPP) problem is a challenging problem that
managers face at any institution. Collecting educational quantitative and qualitative data …
managers face at any institution. Collecting educational quantitative and qualitative data …
[PDF][PDF] Diving Into Zero-Touch Network Security: Use-Case Driven Analysis
Zero-Touch Networks (ZTNs) represent a state-ofthe-art paradigm shift towards fully
automated and intelligent network management, enabling the automation and intelligence …
automated and intelligent network management, enabling the automation and intelligence …