Buscar
Mostrando ítems 1-10 de 12
Fuzzy Logic Models for Non-Programmed Decision-Making in Personnel Selection Processes Based on Gamification
(Informática, 2018)
Non-programmed decision-making is an activity that requires a number of methods to try to capture the rational behaviour of an aspirant in situations of uncertainty. Thus, there is a varied list of attributes, methods, and ...
A recommender system based on implicit feedback for selective dissemination of ebooks
(Information Sciences, 2018-10)
In this study, we describe a recommendation system for electronic books. The approach is based on implicit feedback derived from user's interaction with electronic content. User's behavior is tracked through several ...
Dealing with group decision-making environments that have a high amount of alternatives using card-sorting techniques
(Expert Systems with Applications, 2019-08-01)
Due to the appearance of Web 2.0 technologies and smartphones, the amount of information available to carry out group decision-making processes has increased dramatically. Therefore, there is a need for group decision-making ...
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, ...
Fast single image haze removal method for inhomogeneous environment using variable scattering coefficient
(CMES - Computer Modeling in Engineering and Sciences, 2020)
The images capture in a bad environment usually loses its fidelity and contrast. As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the ...
Fuzzy logic expert system for selecting robotic hands using kinematic parameters
(Journal of Ambient Intelligence and Humanized Computing, 2020-04-01)
Industry 4.0 is the current industrial revolution and robotics is an important factor for carrying out high dexterity manipulations. However, mechatronic systems are far from human capabilities and sophisticated robotic ...
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 ...
Multilayer Framework for Botnet Detection Using Machine Learning Algorithms
(IEEE Access, 2021)
A botnet is a malware program that a hacker remotely controls called a botmaster. Botnet can perform massive cyber-attacks such as DDOS, SPAM, click-fraud, information, and identity stealing. The botnet also can avoid being ...
A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak
(Applied intelligence, 2021)
Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 ...
Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink
(Physical biology, 2021)
In this paper, we demonstrate the application of MATLAB to develop a pandemic prediction system based on Simulink. The susceptible-exposed-asymptomatic but infectious-symptomatic and infectious (severe infected population ...
