A key aspect of the design of evolutionary and swarm intelligence algorithms is studying their performance. Statistical comparisons are also a crucial part which allows for reliable conclusions to be drawn. In the present paper we gather and examine the approaches taken from different perspectives to summarise the assumptions made by these statistical tests, the conclusions reached and the steps followed to perform them correctly. In this paper, we conduct a survey on the current trends of the proposals of statistical analyses for the comparison of algorithms of computational intelligence and include a description of the statistical background of these tests. We illustrate the use of the most common tests in the context of the Competition o...
Swarm Intelligence, of late, has gradually become an exciting area of research interest to many rese...
AbstractTypically, the performance of swarm and evolutionary methods is assessed by comparing their ...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
This paper proposes a statistical methodology for comparing the performance of evolutionary computat...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
The experimental analysis on the performance of a proposed method is a crucial and nec-essary task t...
Evolutionary computation (EC) is a relatively new discipline in computer science (Eiben & Smith, 200...
Success rate is a commonly adopted performance criterion for evaluating Evolutionary Algorithms due ...
Computational intelligence methods have gained importance in several real-world domains such as proc...
<p>Supplementary material of the paper published in International Journal “Information Theories and ...
Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programmi...
Optimization techniques inspired by swarm intelligence have become increasingly popular during the l...
Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a growing r...
Genetski algoritam i optimizacija rojem čestica su metaheuristički optimizacijski alati. Genetski al...
Regression testing is a technique which is carried out to ascertain that the changes that were done ...
Swarm Intelligence, of late, has gradually become an exciting area of research interest to many rese...
AbstractTypically, the performance of swarm and evolutionary methods is assessed by comparing their ...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...
This paper proposes a statistical methodology for comparing the performance of evolutionary computat...
Despite the continuous advancement of Evolutionary Algorithms (EAs) and their numerous successful ap...
The experimental analysis on the performance of a proposed method is a crucial and nec-essary task t...
Evolutionary computation (EC) is a relatively new discipline in computer science (Eiben & Smith, 200...
Success rate is a commonly adopted performance criterion for evaluating Evolutionary Algorithms due ...
Computational intelligence methods have gained importance in several real-world domains such as proc...
<p>Supplementary material of the paper published in International Journal “Information Theories and ...
Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programmi...
Optimization techniques inspired by swarm intelligence have become increasingly popular during the l...
Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a growing r...
Genetski algoritam i optimizacija rojem čestica su metaheuristički optimizacijski alati. Genetski al...
Regression testing is a technique which is carried out to ascertain that the changes that were done ...
Swarm Intelligence, of late, has gradually become an exciting area of research interest to many rese...
AbstractTypically, the performance of swarm and evolutionary methods is assessed by comparing their ...
Evolutionary algorithms (EAs) have emerged as an efficient alternative to deal with real-world appli...