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Geração genética multiobjetivo de sistemas fuzzy usando a abordagem iterativa
(Universidade Federal de São CarlosBRUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCC, 2011-06-28)
The goal of this work is to study, expand and evaluate the use of multiobjective genetic algorithms and the iterative rule learning approach in fuzzy system generation, especially, in fuzzy rule-based systems, both in ...
Uncertainty Propagation in Fuzzy Grey Cognitive Maps With Hebbian-Like Learning Algorithms
This paper is focused on an innovative fuzzy cognitive maps extension called fuzzy grey cognitive maps (FGCMs). FGCMs are a mixture of fuzzy cognitive maps and grey systems theory. These have become a useful framework for ...
Convolutional neural networks ensembles through single-iteration optimization
(2022-01-01)
Convolutional Neural Networks have been widely employed in a diverse range of computer vision-based applications, including image classification, object recognition, and object segmentation. Nevertheless, one weakness of ...
A framework for adaptive open-pit mining planning under geological uncertainty
(Springer, 2020)
Mine planning optimization aims at maximizing the profit obtained from extracting valuable ore. Beyond its theoretical complexity-the open-pit mining problem with capacity constraints reduces to a knapsack problem with ...
A new boosting design of Support Vector Machine classifiers
(Elsevier, 2015)
Boosting algorithms pay attention to the particular structure of the training data when learning, by means of iteratively emphasizing the importance of the training samples according to their difficulty for being correctly ...
Aprendizado ativo em modo batch ordenado
(Universidade Federal de Minas GeraisUFMG, 2012-07-04)
With the large amount of information generated every day on the internet, it is getting harder, if not impossible, to manually administrate and process such data. In order to overcome this problem, Machine Learning algorithms ...
Automatic object extraction from high resolution aerial imagery with simple linear iterative clustering and convolutional neural networks
(2019-09-17)
Recent advances in machine learning techniques for image classification have led to the development of robust approaches to both object detection and extraction. Traditional CNN architectures, such as LeNet, AlexNet and ...