The monarch butterfly optimization algorithm for solving feature selection problems
Feature selection (FS) is considered to be a hard optimization problem in data mining and
some artificial intelligence fields. It is a process where rather than studying all of the features …
some artificial intelligence fields. It is a process where rather than studying all of the features …
Develo** resilient cyber-physical systems: a review of state-of-the-art malware detection approaches, gaps, and future directions
Cyber-physical systems (CPSes) are rapidly evolving in critical infrastructure (CI) domains
such as smart grid, healthcare, the military, and telecommunication. These systems are …
such as smart grid, healthcare, the military, and telecommunication. These systems are …
Coronavirus herd immunity optimizer with greedy crossover for feature selection in medical diagnosis
The importance of medical data and the crucial nature of the decisions that are based on
such data, as well as the large increase in its volume, has encouraged researchers to …
such data, as well as the large increase in its volume, has encouraged researchers to …
A hybrid mine blast algorithm for feature selection problems
Feature selection (FS) is the process of finding the least possible number of features that are
able to describe a dataset in the same way as the original features. Feature selection is a …
able to describe a dataset in the same way as the original features. Feature selection is a …
Hybrid black widow optimization with iterated greedy algorithm for gene selection problems
Gene Selection (GS) is a strategy method targeted at reducing redundancy, limited
expressiveness, and low informativeness in gene expression datasets obtained by DNA …
expressiveness, and low informativeness in gene expression datasets obtained by DNA …
Intrusion detection for the internet of things (IoT) based on the emperor penguin colony optimization algorithm
Abstract In the Internet of Things (IoT), the data that are sent via devices are sometimes
unrelated, duplicated, or erroneous, which makes it difficult to perform the required tasks …
unrelated, duplicated, or erroneous, which makes it difficult to perform the required tasks …
Bio-inspired machine learning approach to Type 2 Diabetes Detection
Type 2 diabetes is a common life-changing disease that has been growing rapidly in recent
years. According to the World Health Organization, approximately 90% of patients with …
years. According to the World Health Organization, approximately 90% of patients with …
[HTML][HTML] A new deep-learning with swarm based feature selection for intelligent intrusion detection for the Internet of things
Humanity can benefit from the Internet of Things (IoT) paradigm in many different ways. IoT
devices are nonetheless susceptible to different cyber-attacks launched by the attacker …
devices are nonetheless susceptible to different cyber-attacks launched by the attacker …
A modified multi-objective particle swarm optimizer-based Lévy flight: An approach toward intrusion detection in Internet of Things
The emerging of the Internet of things (IoT), and more, the advent of the Internet of
everything have revolutionized the computer networks industry. The high diversity of IoT …
everything have revolutionized the computer networks industry. The high diversity of IoT …
Vehicle routing problems based on Harris Hawks optimization
The vehicle routing problem (VRP) is one of the challenging problems in optimization and
can be described as combinatorial optimization and NP-hard problem. Researchers have …
can be described as combinatorial optimization and NP-hard problem. Researchers have …