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A modified grey wolf optimization algorithm for an intrusion detection system
Cyber-attacks and unauthorized application usage have increased due to the extensive use
of Internet services and applications over computer networks, posing a threat to the service's …
of Internet services and applications over computer networks, posing a threat to the service's …
Multi-objective optimal scheduling of automated construction equipment using non-dominated sorting genetic algorithm (NSGA-III)
Y Liu, K You, Y Jiang, Z Wu, Z Liu, G Peng… - Automation in …, 2022 - Elsevier
Unstructured and variable construction sites bring challenges that can be addressed with
the adoption of the flexible earthwork scheduling problem (FESP), which requires …
the adoption of the flexible earthwork scheduling problem (FESP), which requires …
[HTML][HTML] COVID-19 diagnosis and classification using radiological imaging and deep learning techniques: a comparative study
In December 2019, the novel coronavirus disease 2019 (COVID-19) appeared. Being highly
contagious and with no effective treatment available, the only solution was to detect and …
contagious and with no effective treatment available, the only solution was to detect and …
On the interest of artificial intelligence approaches in solving the IoT coverage problem
This survey deals with the 3D indoor deployment in IoT collection networks to identify the
right locations of the IoT connected objects and, subsequently, to manage the coverage …
right locations of the IoT connected objects and, subsequently, to manage the coverage …
Smart city urban planning using an evolutionary deep learning model
Following the evolution of big data collection, storage, and manipulation techniques, deep
learning has drawn the attention of numerous recent studies proposing solutions for smart …
learning has drawn the attention of numerous recent studies proposing solutions for smart …
IoT networks 3D deployment using hybrid many-objective optimization algorithms
When resolving many-objective problems, multi-objective optimization algorithms encounter
several difficulties degrading their performances. These difficulties may concern the …
several difficulties degrading their performances. These difficulties may concern the …
Magnetic force classifier: A novel method for big data classification
There are a plethora of invented classifiers in Machine learning literature, however, there is
no optimal classifier in terms of accuracy and time taken to build the trained model …
no optimal classifier in terms of accuracy and time taken to build the trained model …
Metaheuristic algorithms based on compromise programming for the multi-objective urban shipment problem
The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially
logistics. In this study, we introduced an adaptive method to a complex VRP. It combines …
logistics. In this study, we introduced an adaptive method to a complex VRP. It combines …
From a pareto front to pareto regions: A novel standpoint for multiobjective optimization
This work presents a novel approach for multiobjective optimization problems, extending the
concept of a Pareto front to a new idea of the Pareto region. This new concept provides all …
concept of a Pareto front to a new idea of the Pareto region. This new concept provides all …
Energy-efficient IoT routing based on a new optimizer
Several difficulties are generally encountered when solving many-objective problems (fitted
with three or more conflictual objectives) by applying multi-objective algorithms (resolving …
with three or more conflictual objectives) by applying multi-objective algorithms (resolving …