Abstract The No Free Lunch Theorem states that, averaged over all optimisation problems,
all non-resampling optimisation algorithms perform equally well. In order to explain the …

There has been intensive research from academics and practitioners regarding models for
predicting bankruptcy and default events, for credit risk management. Seminal academic …

Provides an in-depth and even treatment of the three pillars of computational intelligence
and how they relate to one another This book covers the three fundamental topics that form …

Optimization algorithms are widely employed for finding optimal solutions in many
applications. Stochastic optimization algorithms including nature-inspired optimization …

Analyzing Evolutionary Algorithms: The Computer Science Perspective | SpringerLink Skip to
main content Advertisement SpringerLink Log in Menu Find a journal Publish with us Search …

With the recent financial crisis and European debt crisis, corporate bankruptcy prediction
has become an increasingly important issue for financial institutions. Many statistical and …

The analysis of the performance of different approaches is a staple concern in the design of
Computational Intelligence experiments. Any proper analysis of evolutionary optimization …

This paper proposes different classification algorithms—logistic regression, support vector
machine, K-nearest neighbors, and random forest—in order to identify which candidates are …

Differential Evolution (DE) is arguably one of the most powerful stochastic optimization
algorithms for different optimization applications, however, even the state-of-the-art DE …

Abstract The No Free Lunch (NFL) theorem for search and optimisation states that averaged
across all possible objective functions on a fixed search space, all search algorithms …