Encyclopedia of Complexity and Systems Science

Living Edition
| Editors: Robert A. Meyers

Advanced Evolutionary Algorithms in Data Mining

  • Janez Brest
Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27737-5_650-1

Definition of the Subject

Evolutionary algorithms (EAs) are stochastic population-based methods inspired by nature. A population consists of several individuals usually encoded as vectors. During an evolutionary process, a population is transformed into a new population. After some such transformations, the algorithm stops and returns a best found individual as solution.

Differential Evolution (DE) is an evolutionary algorithm for global optimization over continuous spaces as well as for optimization over discrete spaces. Nowadays, it is used as a powerful global optimization method within a wide range of research areas.

As a plethora of data are generated in every possible means and data dimensionality increases on a large scale, it is imperative to increase power of methods in data mining, knowledge discovery, as well as in optimization methods that are dealing with high-dimensional massive data, uncertainty environments, and dynamic systems.

Introduction

(Das and Suganthan 2011): To...

Keywords

Evolutionary Algorithm Differential Evolution Memetic Algorithm Differential Evolution Algorithm Artificial Immune System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering and Computer Science, Institute of Computer ScienceUniversity of MariborMariborSlovenia