This paper thoroughly presents a comprehensive review of the so-called moth–flame
optimization (MFO) and analyzes its main characteristics. MFO is considered one of the …

The Moth flame optimization (MFO) algorithm belongs to the swarm intelligence family and is
applied to solve complex real-world optimization problems in numerous domains. MFO and …

Bio-inspired computing represents the umbrella of different studies of computer science,
mathematics, and biology in the last years. Bio-inspired computing optimization algorithms is …

Abstract The Artificial Neural Network (ANN) is an important machine learning tool used in
medical data classification for disease diagnosis. The learning algorithm in ANN training …

Due to the complexity of their working conditions, historical rolling bearing datasets are
mostly limited and imbalanced. The fault data may be composed of multiple subclusters; that …

This paper provides an alternative method for creating an optimal subset from features
which in turn represent the whole features through improving the moth-flame optimization …

The smart grid is a revolutionary, intelligent, next-generation power system. Due to its cyber
infrastructure nature, it must be able to accurately and detect potential cyber-attacks and …

Mobile crowdsensing is a recent model in which a group of mobile users uses their smart
devices such as smartphones or wearable devices to cooperatively perform a large-scale …

Biomass resources have the potential to become a viable renewable technology and play a
key role within the future renewable energy paradigm. Since CO 2 generated in bio-energy …

Although the multi-layer perceptron (MLP) neural networks provide a lot of flexibility and
have proven useful and reliable in a wide range of classification and regression problems …