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In recent years, several attempts to improve the efficiency of the Canonical Genetic Algorithm have been presented. The advantage of the elitist non-homogeneous genetic algorithm is that variation of the mutation probabilities permits the algorithm to broaden its search space at the start and restrict it later on, however the way in which the mutation probabilities vary is defined before the algorithm...
This paper presents a new optimization algorithm based on quantum-inspired evolutionary techniques that simultaneously incorporates two important features: (i) the treatment of multiple objectives and (ii) the treatment of related categorical attributes, applicable to a specific form of combinatorial optimization. The proposed optimization algorithm is applied to the development of fuzzy inference...
Subgroup Discovery (SD) is a data mining technique whose main objective is the search for descriptions of subgroups of data that are statistically unusual with respect to a property of interest. General rules describing as many instances as possible are preferred in SD, but this can lead to less accurate descriptions that incorrectly describe some instances. These negative examples can be grouped...
Obstructive sleep apnea (OSA) is a common sleep disorder, especially in middle-aged and obese patients. OSA only occurs during sleep, and is a condition that may go unnoticed for years. OSA is associated with increased risk for hypertension, congestive heart failure and coronary artery disease. Furthermore, patients with OSA have higher risk during and after anesthesia. While undiagnosed OSA is a...
The objective of this work is to present an improved version of a method to learn fuzzy classification rules from data by means of a multi-objective evolutionary algorithm and the iterative approach. The work presented here derives from a preliminary version previously proposed by the authors. In the previous version, the trade-off between accuracy and interpretability during the rule generation process...
Participatory evolution is a learning paradigm recently introduced in the realm of fuzzy system modeling and system optimization. The paradigm benefits from the concept of participatory learning, genetic algorithms and differential evolution. In this paper we address two distinct participatory evolutionary learning algorithms. The first combines participatory learning and the processing steps of differential...
The product bundling problem is a challenging task in the e-Commerce domain. We propose a generative engine in order to find the bundle of products that best satisfies user requirements and, at the same time, seller needs such as the minimization of the dead stocks and the maximization of net income. The proposed system named Intelligent Bundle Suggestion and Generation (IBSAG) is designed in order...
An economic activity analysis carried out by employing the fuzzy dimensional size reduction is proposed in this paper. The need for economic impact monitoring is important to measure the economic growth and the effectiveness of worldwide or locally economic policy or activity. The fuzzy dimensional size reduction is employed in synergy with the fuzzy social computing, which is used to describe and...
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