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[HTML][HTML] Choosing mutation and crossover ratios for genetic algorithms—a review with a new dynamic approach
Genetic algorithm (GA) is an artificial intelligence search method that uses the process of
evolution and natural selection theory and is under the umbrella of evolutionary computing …
evolution and natural selection theory and is under the umbrella of evolutionary computing …
A survey of machine learning techniques applied to self-organizing cellular networks
In this paper, a survey of the literature of the past 15 years involving machine learning (ML)
algorithms applied to self-organizing cellular networks is performed. In order for future …
algorithms applied to self-organizing cellular networks is performed. In order for future …
Snow ablation optimizer: A novel metaheuristic technique for numerical optimization and engineering design
This paper develops a novel nature-inspired metaheuristic technique named snow ablation
optimizer (SAO) for numerical optimization and engineering design. The SAO algorithm …
optimizer (SAO) for numerical optimization and engineering design. The SAO algorithm …
A survey on new generation metaheuristic algorithms
Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …
the solution of intractable optimization problems. Major advances have been made since the …
FOX: a FOX-inspired optimization algorithm
This paper proposes a novel nature-inspired optimization algorithm called the Fox optimizer
(FOX) which mimics the foraging behavior of foxes in nature when hunting preys. The …
(FOX) which mimics the foraging behavior of foxes in nature when hunting preys. The …
Genetic algorithm
Genetic Algorithm (GA) is one of the first population-based stochastic algorithm proposed in
the history. Similar to other EAs, the main operators of GA are selection, crossover, and …
the history. Similar to other EAs, the main operators of GA are selection, crossover, and …
Automatically designing CNN architectures using the genetic algorithm for image classification
Convolutional neural networks (CNNs) have gained remarkable success on many image
classification tasks in recent years. However, the performance of CNNs highly relies upon …
classification tasks in recent years. However, the performance of CNNs highly relies upon …
Systems biology informed deep learning for inferring parameters and hidden dynamics
Mathematical models of biological reactions at the system-level lead to a set of ordinary
differential equations with many unknown parameters that need to be inferred using …
differential equations with many unknown parameters that need to be inferred using …
Multifactorial evolution: Toward evolutionary multitasking
The design of evolutionary algorithms has typically been focused on efficiently solving a
single optimization problem at a time. Despite the implicit parallelism of population-based …
single optimization problem at a time. Despite the implicit parallelism of population-based …
Information gain directed genetic algorithm wrapper feature selection for credit rating
Financial credit scoring is one of the most crucial processes in the finance industry sector to
be able to assess the credit-worthiness of individuals and enterprises. Various statistics …
be able to assess the credit-worthiness of individuals and enterprises. Various statistics …