This paper proposes the salp swarm algorithm (SSA) combined with a backpropagation
neural network (BPNN) to solve the software fault prediction (SFP) problem. The SFP …

University electronic learning (e-learning) has witnessed phenomenal growth, especially in
2020, due to the COVID-19 pandemic. This type of education is significant because it …

Meta-heuristic algorithms become common approaches in finding sufficiently good solutions
for optimization problems. This study proposed and compared three novel hybrid methods …

In recent years, significant advancements have been made in artificial neural network
models and they have been applied to a variety of real-world problems. However, one of the …

Naturally, cells in human body grow and divide in a controlled way to produce more cells to
maintain health. Cancer affects human body when abnormal cells divide without control and …

Training multi-layer neural networks (MLNNs), a challenging task, involves finding
appropriate weights and biases. MLNN training is important since the performance of …

The performance of feed-forward neural networks (FFNN) is directly dependant on the
training algorithm. Conventional training algorithms such as gradient-based approaches are …

Despite the effectiveness of deep neural networks, feed-forward neural networks (FFNNs)
continue to play a crucial role in many applications, especially when dealing with limited …

Artificial neural networks (ANNs) are one of the most widely used techniques for
generalization, classification, and optimization. ANNs are inspired from the human brain and …

Phishing is a sort of cyberattack that refers to the practice of fabricating fake websites that
imitate authentic websites in order to trick users into disclosing private information …