Load forecasting is a pivotal part of the power utility companies. To provide load-shedding
free and uninterrupted power to the consumer, decision-makers in the utility sector must …

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

The tremendously growing problem of phishing e-mail, also known as spam including spear
phishing or spam borne malware, has demanded a need for reliable intelligent anti-spam e …

Novelty detection is the task of classifying test data that differ in some respect from the data
that are available during training. This may be seen as “one-class classification”, in which a …

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

In the statistics community, outlier detection for time series data has been studied for
decades. Recently, with advances in hardware and software technology, there has been a …

Anomaly detection is an important problem that has been researched within diverse
research areas and application domains. Many anomaly detection techniques have been …

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration
into the adaptive mechanisms that enable intelligent behaviour in complex and changing …

This survey attempts to provide a comprehensive and structured overview of the existing
research for the problem of detecting anomalies in discrete/symbolic sequences. The …