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Research Interests: Statistical Analysis, Design of Experiments, Fuzzy Systems, Knowledge Representation, Hybrid Intelligent Systems, and 8 moreUnsupervised Learning, adaptive neuro fuzzy inference system (ANFIS), Domain Knowledge, Design of experiment, Neuro Fuzzy, Fuzzy Inference System, Artificial Neural Network, and Hybrid Method
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Artificial neural networks (ANNs) are widely used in applications with complex decision boundaries. A large number of activation functions have been proposed in the literature to achieve better representations of the observed data.... more
Artificial neural networks (ANNs) are widely used in applications with complex decision boundaries. A large number of activation functions have been proposed in the literature to achieve better representations of the observed data. However, only a few works employ Tsallis statistics, which has successfully been applied to various other fields. This paper presents a random neural network (RNN) with q-Gaussian activation functions [q-generalized RNN (QRNN)] based on Tsallis statistics. The proposed method employs an additional parameter q (called the entropic index) which reflects the degree of nonextensivity. This approach has the flexibility to model complex decision boundaries of different shapes by varying the entropic index. We conduct numerical experiments to analyze the efficiency of QRNN compared with RNNs and several other classical methods. Statistical tests (Wilcoxon and Friedman) are used to validate our results and show that the QRNN performs significantly better than RNNs with different activation functions. In addition, we find that QRNN outperforms many of the compared classical methods, with the exception of support vector machines, in which case it still exhibits a substantial advantage in terms of implementation simplicity and speed.
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This paper presents a hybrid MLP-SVM method for cursive characters recognition. Specialized Support Vector Machines (SVMs) are introduced to significantly improve the performance of Multilayer Perceptron (MLP) in the local areas around... more
This paper presents a hybrid MLP-SVM method for cursive characters recognition. Specialized Support Vector Machines (SVMs) are introduced to significantly improve the performance of Multilayer Perceptron (MLP) in the local areas around the surfaces of separation between each pair of characters in the space of input patterns. This hybrid architecture is based on the observation that when using MLPs in the task of handwritten characters recognition, the correct class is almost always one of the two maximum outputs of the MLP. The second observation is that most of the errors consist of pairs of classes in which the characters have similarities (e.g. (U, V), (m, n), (O, Q), among others). Specialized local SVMs are introduced to detect the correct class among these two classification hypotheses. The hybrid MLP-SVM recognizer showed improvement, significant, in performance in terms of recognition rate compared with an MLP for a task of character recognition. Resumo. Este artigo apresent...
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Page 1. A neural architecture to identify courtesy amount delimiters1 Cleber Zanchettin, George DC Cavalcanti, Rodrigo C. Dória, Eduardo FA Silva, Juliano CB Rabelo and Byron LD Bezerra AbstractThis paper deals with automatic recognition... more
Page 1. A neural architecture to identify courtesy amount delimiters1 Cleber Zanchettin, George DC Cavalcanti, Rodrigo C. Dória, Eduardo FA Silva, Juliano CB Rabelo and Byron LD Bezerra AbstractThis paper deals with automatic recognition of real bank checks. ...
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The present work describes an application of Clonart (Clonal Adaptive Resonance Theory) for forecasting of amount of precipitation for the Brazilian Energy Distribution System. The effectiveness of the Brazilian electricity system... more
The present work describes an application of Clonart (Clonal Adaptive Resonance Theory) for forecasting of amount of precipitation for the Brazilian Energy Distribution System. The effectiveness of the Brazilian electricity system directly depends on the difference between hydroelectric energy production and consumer use. Production depends upon the volume of water stored in the reservoirs. A forecasting system for the amount
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ABSTRACT The handwritten signature is present in all important documents. In law, if the signature on a document is false, this document is also considered a fraud. This paper uses a neural network of radial basis function optimized by... more
ABSTRACT The handwritten signature is present in all important documents. In law, if the signature on a document is false, this document is also considered a fraud. This paper uses a neural network of radial basis function optimized by Differential Evolution Algorithm with features that best discriminates between a genuine signature of a simulated forgery. The experiments with this promising technique were made with a GPDS-300 gray images base and the results subjected to statistical tests with the performance of technical literature.
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The present work proposes an integration of clonal adaptive resonance theory framework (Clonart) with radial basis function (RBF) called ClonalRBF. This framework was already used in a handwritten digit classification problem, a... more
The present work proposes an integration of clonal adaptive resonance theory framework (Clonart) with radial basis function (RBF) called ClonalRBF. This framework was already used in a handwritten digit classification problem, a forecasting for the Brazilian energy distribution system and now a time series analysis in gas furnace and Mackey-Glass databases. In Clonart, the population memory was organized using an
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... Byron LD Bezerra Polytechnic School of Pernambuco University of Pernambuco Recife, PE, Brazil Email: byronleite@ecomp.poli.br ... These characteristics makes harder the separation of the background and the objects of the interest area... more
... Byron LD Bezerra Polytechnic School of Pernambuco University of Pernambuco Recife, PE, Brazil Email: byronleite@ecomp.poli.br ... These characteristics makes harder the separation of the background and the objects of the interest area [10], [13]. ...
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An approach is proposed for detecting and eliminat- ing invasion in courtesy amount fields. This is a important step toward automatizing the bank check process. In a real database, 18% of handwritten courtesy amount fields ex- hibited... more
An approach is proposed for detecting and eliminat- ing invasion in courtesy amount fields. This is a important step toward automatizing the bank check process. In a real database, 18% of handwritten courtesy amount fields ex- hibited invasions in the legal amount and signature fields. Experimental results have shown that the proposed ap- proach is robust and efficient for improving
ABSTRACT This paper presents a hybrid KNN-SVM method for cursive character recognition. Specialized Support Vector Machines (SVMs) are introduced to significantly improve the performance of KNN in handwrite recognition. This hybrid... more
ABSTRACT This paper presents a hybrid KNN-SVM method for cursive character recognition. Specialized Support Vector Machines (SVMs) are introduced to significantly improve the performance of KNN in handwrite recognition. This hybrid approach is based on the observation that when using KNN in the task of handwritten characters recognition, the correct class is almost always one of the two nearest neighbors of the KNN. Specialized local SVMs are introduced to detect the correct class among these two different classification hypotheses. The hybrid KNN-SVM recognizer showed significant improvement in terms of recognition rate compared with MLP, KNN and a hybrid MLP-SVM approach for a task of character recognition.
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This work examines the use of Hybrid Intelligent Systems in the pattern recognition system of an artificial nose. The connectionist approaches Multi-Layer Perceptron and Time Delay Neural Networks, and the hybrid approaches... more
This work examines the use of Hybrid Intelligent Systems in the pattern recognition system of an artificial nose. The connectionist approaches Multi-Layer Perceptron and Time Delay Neural Networks, and the hybrid approaches Feature-Weighted Detector and Evolving Neural Fuzzy Networks were investigated. A Wavelet Filter is evaluated as a preprocessing method for odor signals. The signals generated by an artificial nose were composed by an array of conducting polymer sensors and exposed to two different odor databases.
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This work presents a new methodology that integrates the heuristics Tabu search, simulated annealing, genetic algorithms and backpropagation in a pruning and constructive way. The approach obtained promising results in the simultaneous... more
This work presents a new methodology that integrates the heuristics Tabu search, simulated annealing, genetic algorithms and backpropagation in a pruning and constructive way. The approach obtained promising results in the simultaneous optimization of artificial neural network architecture and weights. The experiments were performed in four classification and one prediction problem.
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ABSTRACT This paper presents a system consisting of physical sensors and intelligent software for the automatic identification of the concentration of natural gas odorants and details the development of the sensor and pattern recognition... more
ABSTRACT This paper presents a system consisting of physical sensors and intelligent software for the automatic identification of the concentration of natural gas odorants and details the development of the sensor and pattern recognition systems. The sensor system uses spectroscopic technology and the pattern recognition system uses wavelet and artificial neural network technology. The aim is to determine the concentration of a natural gas odorant in the environment and associate this concentration with the benchmark index, which measures the degree of human perception to the presence of gas in the environment. Experiments were conducted comparing the performance of the system with human performance, which is normally used to deal with this problem. The proposed system demonstrated promising results.
... To evaluate the performance of the EFuNN in the odor classification, its results will be compared with results for the Time-Delay Neural Networks, which have displayed excellent results in the odor patterns classification. This paper... more
... To evaluate the performance of the EFuNN in the odor classification, its results will be compared with results for the Time-Delay Neural Networks, which have displayed excellent results in the odor patterns classification. This paper is divided into five sections. ...
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This paper presents a hybrid MLP-SVM method for cursive characters recognition. Specialized Support Vector Machines (SVMs) are introduced to significantly improve the performance of Multilayer Perceptron (MLP) in the local areas around... more
This paper presents a hybrid MLP-SVM method for cursive characters recognition. Specialized Support Vector Machines (SVMs) are introduced to significantly improve the performance of Multilayer Perceptron (MLP) in the local areas around the surfaces of separation between each pair of characters in the space of input patterns. This hybrid architecture is based on the observation that when using MLPs in
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ABSTRACT This work presents an evaluation of the effect of different cost functions in a methodology that integrates heuristic tabu search, simulated annealing, genetic algorithms and backpropagation. We investigated four cost function... more
ABSTRACT This work presents an evaluation of the effect of different cost functions in a methodology that integrates heuristic tabu search, simulated annealing, genetic algorithms and backpropagation. We investigated four cost function approaches: average method, weight-decay, multi-objective optimization, combined multi-objective and weight-decay. The weight-decay approach presented promising results in the simultaneous optimization of artificial neural network architecture and weights. The experiments were performed in four classifications and one prediction problem.
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... A compression option can be added when data are to be transmitted over the internet. ... 6. References [1] M. Seredinsky and P. Bouvry, Block encryption using reversible cellularautomata, ACRI 2004 The Netherlands - Amsterdam, LNCS... more
... A compression option can be added when data are to be transmitted over the internet. ... 6. References [1] M. Seredinsky and P. Bouvry, Block encryption using reversible cellularautomata, ACRI 2004 The Netherlands - Amsterdam, LNCS 3305, pp. ...
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Abstract The present work describes an evolution of the hybrid immune approach called Clonart (Clonal Adaptive Resonance Theory) using ECOS (Evolving Connectionist Systems) architectures. Some improvements were developed to allow the... more
Abstract The present work describes an evolution of the hybrid immune approach called Clonart (Clonal Adaptive Resonance Theory) using ECOS (Evolving Connectionist Systems) architectures. Some improvements were developed to allow the control of the growth of ...
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ABSTRACT The present work proposes the architecture Clonart (Clonal Adaptive Resonance Theory) that employs many different techniques like intelligent operators, clonal selection principle, local search, memory antibodies and ART... more
ABSTRACT The present work proposes the architecture Clonart (Clonal Adaptive Resonance Theory) that employs many different techniques like intelligent operators, clonal selection principle, local search, memory antibodies and ART clusterization in order to increase the performance of the algorithm. The approach uses a mechanism similar to the ART 1 network for storing a population of memory antibodies that will be responsible for the acquired knowledge of the algorithm. This characteristic allows the algorithm a self-organization of the antibodies in accordance with the complexity of the database used.
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ABSTRACT This paper presents an efficient method for handwritten digit recognition. The proposed method makes use of Support Vector Machines (SVM), benefitting from its generalization power. The method presents improved recognition rates... more
ABSTRACT This paper presents an efficient method for handwritten digit recognition. The proposed method makes use of Support Vector Machines (SVM), benefitting from its generalization power. The method presents improved recognition rates when compared to Multi-Layer Perceptron (MLP) classifiers, other SVM classifiers and hybrid classifiers. Experiments and comparisons were done using a digit set extracted from the NIST SD19 digit database. The proposed SVM method achieved higher recognition rates and it outperformed other methods. It is also shown that although using solely SVMs for the task, the new method does not suffer when considering processing time.
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ABSTRACT This paper presents a recurrent neural networks applied to handwriting character recognition. The method Multi-dimensional Recurrent Neural Network is evaluated against classical techniques. To improve the model performance we... more
ABSTRACT This paper presents a recurrent neural networks applied to handwriting character recognition. The method Multi-dimensional Recurrent Neural Network is evaluated against classical techniques. To improve the model performance we propose the use of specialized Support Vector Machine combined whit the original Multi-dimensional Recurrent Neural Network in cases of confusion letters. The experiments were performed in the C-Cube database and compared with different classifiers. The hierarchical combination presented promising results.
ABSTRACT This paper presents an approach to handwriting character recognition using recurrent neural networks. The method Multi-dimensional Recurrent Neural Network is evaluated against the classical techniques. To improve the model... more
ABSTRACT This paper presents an approach to handwriting character recognition using recurrent neural networks. The method Multi-dimensional Recurrent Neural Network is evaluated against the classical techniques. To improve the model performance we propose the use of specialized Support Vector Machine combined with the original MDRNN in cases of confusion letters to avoid misclassifications. The performance of the method is verified in the C-Cube database and compared with different classifiers. The hierarchical combination presented promising results.
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ABSTRACT In recent years, the Extreme Learning Machine (ELM) has been hybridized with the Particle Swarm Optimization (PSO) and such hybridization is called PSO-ELM. In most of these hybridizations, the PSO uses the Global topology.... more
ABSTRACT In recent years, the Extreme Learning Machine (ELM) has been hybridized with the Particle Swarm Optimization (PSO) and such hybridization is called PSO-ELM. In most of these hybridizations, the PSO uses the Global topology. However, other topologies ...
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Interest in hybrid methods that combine artificial neural networks and fuzzy inference systems has grown in recent years. These systems are robust solutions that search for representations of domain knowledge, reasoning on uncertainty,... more
Interest in hybrid methods that combine artificial neural networks and fuzzy inference systems has grown in recent years. These systems are robust solutions that search for representations of domain knowledge, reasoning on uncertainty, automatic learning and adaptation. However, the design and definition of the parameter effectiveness of such systems is still a hard task. In the present work, we perform a statistical analysis to verify interactions and interrelations between parameters in the design of neuro-fuzzy systems. The analysis is carried out using a powerful statistical tool, namely, Design of Experiments (DOE), in two neuro-fuzzy models — Adaptive Neuro Fuzzy Inference System (ANFIS) and Evolving Fuzzy Neural Networks (EFuNN). The results show that, for ANFIS, input MFs number and output MFs shape are usually the factors with the largest influence on the system's RMSE. For EFFuNN, the MF shape and the interaction between MF shape and number usually have the largest eff...
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Research Interests: Genetic Algorithms, Public Domain, Tabu Search, Simulated Annealing, Multidisciplinary, and 13 moreGenetic Algorithm, Feature Selection, Algorithm Design, Multilayer Perceptron, Local minima, OPTIMIZATION TECHNIQUE, Hybrid Approach, Empirical Evaluation, Backpropagation, Construction Process, Cost Function, Artificial Neural Network, and Neural nets
Research Interests: Information Systems, Applied Mathematics, Data Compression, Neural Network, Artificial Neural Networks, and 8 moreWavelet Analysis, Hybrid Intelligent Systems, Conducting Polymer, Wavelet Transform, Noise reduction, Time delay neural network TDN, Artificial Neural Network, and multi layer perceptron
Adriano Lorena Oliveira, Federal Rural University of Pernambuco, Brazil Adrião Duarte Dória Neto, Federal University of Rio Grande do Norte, Brazil Alexandre Evsukoff, Federal University of Rio de Janeiro, Brazil Ana Bazzan, UFRGS, Brazil... more
Adriano Lorena Oliveira, Federal Rural University of Pernambuco, Brazil Adrião Duarte Dória Neto, Federal University of Rio Grande do Norte, Brazil Alexandre Evsukoff, Federal University of Rio de Janeiro, Brazil Ana Bazzan, UFRGS, Brazil Ana Carolina Lorena, UFABC, Brazil André Ponce de Leon F de Carvalho, ICMC-USP/S.Carlos, Brazil Anne Canuto, Federal University of Rio Grande do Norte, Brazil Antônio Braga, Federal University of Minas Gerais, Brazil Antonio Carlos da Rocha Costa, UCPEL, Brazil Artur Garcez, City University, UK Aurora Pozo, ...