A5008307290- Fuzzy Logic and Control Systems
- Multi-Criteria Decision Making
- Rough Sets and Fuzzy Logic
- Fuzzy Systems and Optimization
- Imbalanced Data Classification Techniques
- Data Mining Algorithms and Applications
- Neural Networks and Applications
- Advanced Algebra and Logic
- Fault Detection and Control Systems
- Advanced Statistical Process Monitoring
- Machine Learning and Data Classification
- Trauma and Emergency Care Studies
- Scientific Measurement and Uncertainty Evaluation
- EEG and Brain-Computer Interfaces
- Fuzzy and Soft Set Theory
- Advanced Statistical Methods and Models
- Face and Expression Recognition
- Data Management and Algorithms
- Image Retrieval and Classification Techniques
- Statistical Methods in Epidemiology
- Adhesion, Friction, and Surface Interactions
- Emergency and Acute Care Studies
- Metaheuristic Optimization Algorithms Research
- Data Stream Mining Techniques
- Surface Roughness and Optical Measurements
Universidad de Navarra
1995-2024
John Wiley & Sons (United States)
2017-2023
John Wiley & Sons (United Kingdom)
2021-2023
Interface (United Kingdom)
2017-2023
Universidad Publica de Navarra
2013-2022
University of East Asia
2020-2021
Hudson Institute
2019
Merck Institute for Science Education
2019
University of Technology Sydney
2019
Complejo Hospitalario de Navarra
2018
In this paper, we introduce the notion of preaggregation function. Such a function satisfies same boundary conditions as an aggregation function, but, instead requiring monotonicity, only monotonicity along some fixed direction (directional monotonicity) is required. We present examples such functions. propose three different methods to build experimentally show that in fuzzy rule-based classification systems, when use one these methods, namely, based on Choquet integral replacing product by...
The current financial crisis has stressed the need to obtain more accurate prediction models in order decrease risk when investing money on economic opportunities. In addition, transparency of process followed make decisions applications is becoming an important issue. Furthermore, there a handle real-world imbalanced datasets without using sampling techniques that might introduce noise used data. this paper, we present compact evolutionary interval-valued fuzzy rule-based classification...
There are many real-world classification problems involving multiple classes, e.g., in bioinformatics, computer vision, or medicine. These generally more difficult than their binary counterparts. In this scenario, decomposition strategies usually improve the performance of classifiers. Hence, paper, we aim to behavior fuzzy association rule-based model for high-dimensional (FARC-HD) classifier multiclass using strategies, and specifically One-versus-One (OVO) One-versus-All (OVA) strategies....
Interval-valued fuzzy sets have been shown to be a useful tool deal with the ignorance related definition of linguistic labels. Specifically, they successfully applied solve classification problems, performing simple modifications on reasoning method work this representation and making based single number. In paper, we present IVTURS, which is new rule-based completely interval-valued method. This inference process uses restricted equivalence functions increase relevance rules in interval...
A key component of fuzzy rule-based classification systems (FRBCS) is the reasoning method (FRM) since it infers class predicted for new examples. crucial stage in any FRM way which information given by fired rules during inference process aggregated. widely used winning rule, applies maximum to accomplish this aggregation. The an averaging operator, means that its result within range delimited minimum and aggregated values. Recently, operators based on generalizations Choquet integral have...
Brain-computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain external devices. Motor imagery-based brain-computer interfaces popular because they avoid unnecessary stimuli. Although feature extraction have been illustrated in several machine intelligent systems studies, performance remains unsatisfactory. There is increasing interest use fuzzy integrals, Choquet Sugeno that appropriate for...
Brain-computer interface (BCI) technologies are popular methods of communication between the human brain and external devices. One most approaches to BCI is motor imagery (MI). In applications, electroencephalography (EEG) a very measurement for dynamics because its noninvasive nature. Although there high interest in topic, performance existing systems still far from ideal, due difficulty performing pattern recognition tasks EEG signals. This lies selection correct channels, signal-to-noise...
In this paper we present a new fuzzy reasoning method in which the Choquet integral is used as aggregation function. manner, can take into account interaction among rules of system. For reason, consider several measures, since it key point on subsequent success integral, and apply with same measure for all classes. However, relationship set each class be different therefore best change depending class. Consequently, propose learning by means genetic algorithm most suitable computed. From...
Overlap functions are a type of aggregation that not required to be associative, generally used indicate the overlapping degree between two values. They have been successfully as conjunction operator in several practical problems, such fuzzy-rule-based classification systems (FRBCSs) and image processing. Some extensions overlap were recently proposed, general and, interval-valued context, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i>...
Imbalanced classification problems are attracting the attention of research community because they prevalent in real-world and impose extra difficulties for learning methods. Fuzzy rule-based systems have been applied to cope with these problems, mostly together sampling techniques. In this paper, we define a new fuzzy association classifier, named FARCI, tackle directly imbalanced problems. Our proposal belongs algorithm modification category, since it is constructed on basis...