Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

With the advent of the fourth industrial revolution, the application of artificial intelligence in
the manufacturing domain is becoming prevalent. Maintenance is one of the important …

This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …

Emotion recognition has gained prominence in diverse applications ranging from safe
driving and e-commerce to healthcare. Traditional approaches have often relied on single …

Feature selection is imperative in machine learning and data mining when we have high-
dimensional datasets with redundant, nosy and irrelevant features. The area of feature …

Nowadays, analyzing and interpreting emotions through human speech communication
have drawn a great attention in the field of human-computer interaction. Therefore, many …

Feature selection plays an important role to build a successful speech emotion recognition
system. In this paper, a feature selection approach which modifies the initial population …

Feature selection or dimensionality reduction can be considered as a multi-objective
minimization problem with two objectives: minimizing the number of features and minimizing …

With the rapid development of telecommunication networks, the predictability of network
traffic is of significant interest in network analysis and optimization, bandwidth allocation …