In recent decades, researches on optimizing the parameter of the artificial neural network
(ANN) model has attracted significant attention from researchers. Hybridization of superior …

There are several meta-heuristic optimization algorithms developed on inspiration from
nature. Artificial neural network proves to be efficient among other machine learning …

The major aim of the education institute is to provide the high-quality education to students.
The way to attain the high quality in the education system is to determine the knowledge …

Many optimization algorithms and metaheuristics have been inspired by nature. These
algorithms often permit solving a wide range of optimization problems. Most of them were …

Developing trustworthy rainfall-runoff (RR) models can offer serviceable information for
planning and managing water resources. Use of artificial neural network (ANN) in adopting …

Training of feed-forward neural-networks (FNN) is a challenging nonlinear task in
supervised learning systems. Further, derivative learning-based methods are frequently …

This work proposes a new evolutionary multilayer perceptron neural networks using the
recently proposed Bird Swarm Algorithm. The problem of finding the optimal connection …

Artificial neural networks (ANNs) are one of the artificial intelligence techniques used in real-
world problems and applications encountered in almost all industries such as education …

Training of feed-forward neural networks is a well-known and important hard optimization
problem, frequently used for classification purpose. Swarm intelligence metaheuristics have …

The early diagnosis of sepsis reduces the risk of the patient's death. Gradient-based
algorithms are applied to the neural network models used in the estimation of sepsis in the …