Buscar
Mostrando ítems 11-20 de 22
Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction
(Applied Soft Computing Journal, 2020-08)
In the advent of the novel coronavirus epidemic since December 2019, governments and authorities have been struggling to make critical decisions under high uncertainty at their best efforts. In computer science, this ...
Analyzing the Scientific Evolution of Social Work Using Science Mapping
(Research on Social Work Practice, 2015-03)
Objectives: This article reports the first science mapping analysis of the social work field, which shows its conceptual structure
and scientific evolution. Methods: Science Mapping Analysis Software Tool, a bibliometric ...
Improving supervised learning classification methods using multi-granular linguistic modelling and fuzzy entropy
(IEEE Transactions on Fuzzy Systems, 2017-10)
Obtaining good classification results using supervised learning methods is critical if we want to obtain a high level of precision in the classification processes. The training data used for the learning process plays a ...
Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods
(Knowledge-Based Systems, 2017-12)
Classic multi-criteria group decision making models that have a high amount of alternatives are unmanageable for the experts. This is because they have to provide one value per each alternative and criteria. In this paper, ...
Characterizing highly cited papers in Social Work through H-Classics
(Scientometrics, 2015-02)
Highly cited papers are an important reference point in a research field. H-Classics is a new identification method of highly cited papers that is based on the H-index and is sensitive to the own characteristics of any ...
H-Classics: characterizing the concept of citation classics through H-index
(Scientometrics, 2014-03)
Citation classics identify those highly cited papers which are an important reference point in a research field. To identify a paper as a citation classic we have to fix a citation threshold value. Usually, this threshold ...
Enhancing big data feature selection using a hybrid correlation-based feature selection
(2021)
This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based feature selection (CFS), best first search ...
Alzheimer's Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes
(Institute of Electrical and Electronics Engineers Inc., 2021)
There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 s. Alzheimer's disease (AD) is a progressive neurodegenerative disease and various machine ...
Social IoT Approach to Cyber Defense of a Deep-Learning-Based Recognition System in front of Media Clones Generated by Model Inversion Attack
(IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023)
Model inversion attack (MIA) is a cyber threat with an increasing alert even for deep-learning-based recognition systems (DLRSs). By targeting a DLRS under a scenario of attacker access to the model structure and parameters, ...
Customer churn prediction for web browsers
(Expert Systems with Applications, 2022)
In the competitive web browser market, identifying potential churners is critical to decreasing the loss of existing customers. Churn prediction based on customer behaviors plays a vital role in customer retention strategies. ...