Buscar
Mostrando ítems 1-8 de 8
Managing multi-criteria group decision making environments with high number of alternatives using fuzzy ontologies
(Frontiers in Artificial Intelligence and Applications, 2018)
The high amount of information that modern multi-criteria group decision making environments must handle requires the development of novel methods. These methods should be able to work with high amounts of alternatives ...
The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they ...
Analysis of the COVID19 Pandemic Behaviour Based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
A significant number of people infected by COVID19 do not get sick immediately but become carriers of the disease. These patients might have a certain incubation period. However, the classical compartmental model, SEIR, ...
The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in ...
Probabilistic Forecasting Model for the COVID-19 Pandemic Based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of ...
Classification of Breast Thermal Images into Healthy/Cancer Group Using Pre-Trained Deep Learning Schemes
(Procedia Computer Science, 2022)
In the women's community, Breast Cancer (BC) is a severe disease. The World Health Organization reported in 2020 that 2.26 million deaths occur due to BC. BC is curable if detected early. Since thermal imaging is non-invasive ...
Automatic detection of lung nodule in CT scan slices using CNN segmentation schemes: A study
(Procedia Computer Science, 2022)
The lung is one of the prime respiratory organs in human physiology, and its abnormality will severely disrupt the respiratory system. Lung Nodule (LN) is one of the abnormalities, and early screening and treatment are ...
Deep and handcrafted feature supported diabetic retinopathy detection: A study
(Procedia Computer Science, 2022)
The eye is the prime sensory organ in physiology, and the abnormality in the eye severely influences the vision system. Therefore, eye irregularity is commonly assessed using imaging schemes, and Fundus Retinal Image (FRI) ...
