Data over the internet has been increasing everyday, and automatic mining of essential
information from an enormous amount of data has become a challenging task today for an …

This paper presents a comprehensive review of evolutionary algorithms that learn an
ensemble of predictive models for supervised machine learning (classification and …

For optimal utilization of power generation resources, load forecasting plays a vital role in
balancing the load flow in a power distribution network. There are several drawbacks …

Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage
of human-readable models allows them to explain the reasoning behind their predictions …

In the last years, multi-objective evolutionary algorithms (MOEAs) have been extensively
used to generate sets of fuzzy rule-based classifiers (FRBCs) with different trade-offs …

In this paper, we propose a novel Evolutionary Mamdani Fuzzy Rule-based System named
DECO 3 RUM (Differential Evolution based Cooperative and Competing learning of …

The significance and benefits of addressing classification tasks in Big Data applications is
beyond any doubt. To do so, learning algorithms must be scalable to cope with such a high …

Rapid growth in technology and information lead the human to witness the improved growth
in velocity, volume of data, and variety. The data in the business organizations demonstrate …

Studies in Evolutionary Fuzzy Systems (EFSs) began in the 90s and have experienced a fast
development since then, with applications to areas such as pattern recognition, curve‐fitting …

The significance of addressing Big Data applications is beyond all doubt. The current ability
of extracting interesting knowledge from large volumes of information provides great …