Bio-inspired optimization algorithms have been successfully used to solve many problems in
engineering, science, and economics. In computer science bio-inspired optimization has …

On account of the strong time series feature of smart grid load data, this paper presents a
data cleaning method based on similarity measurement of time series, which detects the …

Metaheuristics are probabilistic optimization algorithms which are applicable to a wide
range of optimization problems. Bio-inspired, also called nature-inspired, optimization …

Multi-objective optimization (MOO) is a class of optimization problems where several
objective functions must be simultaneously optimized. Traditional search methods are …

Bio-inspired optimization algorithms have been successfully applied to solve many
problems in engineering, science, and economics. In computer science bio-inspired …

In a previous work we presented the Σ-gram distance that computes the similarity between
two sequences. This distance includes parameters that we calculated by means of an …

Financial time series behave similarly to a data stream, that is, a set of input elements that
arrive continuously and sequentially over time. So, a time series may present concept drifts …

Clustering is one of the main data mining tasks. It can be performed on a fuzzy or a crisp
basis. Fuzzy clustering is widely-applied with microarray gene expression data as these …

The representation of nonuniform, multi-modal, time-limited time series data is complex and
explored through the use of discrete representation, dimensionality reduction with …