Adversarial machine learning for network intrusion detection systems: A comprehensive survey
Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …
network attacks that compromise the security of the data, systems, and networks. In recent …
Metaheuristic research: a comprehensive survey
Because of successful implementations and high intensity, metaheuristic research has been
extensively reported in literature, which covers algorithms, applications, comparisons, and …
extensively reported in literature, which covers algorithms, applications, comparisons, and …
[HTML][HTML] An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm
EH Houssein, MM Emam, AA Ali - Neural Computing and Applications, 2022 - Springer
Breast cancer is the second leading cause of death in women; therefore, effective early
detection of this cancer can reduce its mortality rate. Breast cancer detection and …
detection of this cancer can reduce its mortality rate. Breast cancer detection and …
EEDTO: An energy-efficient dynamic task offloading algorithm for blockchain-enabled IoT-edge-cloud orchestrated computing
With the proliferation of compute-intensive and delay-sensitive mobile applications, large
amounts of computational resources with stringent latency requirements are required on …
amounts of computational resources with stringent latency requirements are required on …
An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation
EH Houssein, K Hussain, L Abualigah… - Knowledge-based …, 2021 - Elsevier
A recent meta-heuristic algorithm called Marine Predators Algorithm (MPA) is enhanced
using Opposition-Based Learning (OBL) termed MPA-OBL to improve their search efficiency …
using Opposition-Based Learning (OBL) termed MPA-OBL to improve their search efficiency …
Review of job shop scheduling research and its new perspectives under Industry 4.0
Traditional job shop scheduling is concentrated on centralized scheduling or semi-
distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and …
distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and …
An efficient multilevel thresholding segmentation method for thermography breast cancer imaging based on improved chimp optimization algorithm
EH Houssein, MM Emam, AA Ali - Expert Systems with Applications, 2021 - Elsevier
Thermography images are a helpful screening tool that can detect breast cancer by showing
the body parts that indicate an abnormal change in temperature. Various segmentation …
the body parts that indicate an abnormal change in temperature. Various segmentation …
Learning to delegate for large-scale vehicle routing
Vehicle routing problems (VRPs) form a class of combinatorial problems with wide practical
applications. While previous heuristic or learning-based works achieve decent solutions on …
applications. While previous heuristic or learning-based works achieve decent solutions on …
Combinatorial optimization by graph pointer networks and hierarchical reinforcement learning
In this work, we introduce Graph Pointer Networks (GPNs) trained using reinforcement
learning (RL) for tackling the traveling salesman problem (TSP). GPNs build upon Pointer …
learning (RL) for tackling the traveling salesman problem (TSP). GPNs build upon Pointer …
The electric vehicle-routing problem with time windows and recharging stations
M Schneider, A Stenger, D Goeke - Transportation science, 2014 - pubsonline.informs.org
Driven by new laws and regulations concerning the emission of greenhouse gases, carriers
are starting to use electric vehicles for last-mile deliveries. The limited battery capacities of …
are starting to use electric vehicles for last-mile deliveries. The limited battery capacities of …