Paraconsistência em informática e inteligência artificial

Costa, Newton C. A. da; Abe, Jair Minoro

doi:10.1590/s0103-40142000000200012

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…Paraconsistent logic (PL) is a non-classical logic that is capable to deal with contradictions in a discriminating way. The foundations of PL allow contradictory signals to be equated without weakening the logical conclusions (Da Costa & Abe, 2000).…”

Section: Paraconsistent Annotated Logic -Palmentioning

confidence: 99%

Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures

Correa

Machado

Filho

et al. 2022

RSD

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In this study, we introduced an expert system (ESvbrPAL2v), responsible for monitoring assets based on vibration signature analysis through a set of algorithms based on the Paraconsistent Annotated Logic – PAL. Being a non-classical logic, the main feature of the PAL is to support contradictory inputs in its foundation. It is therefore suitable for building algorithmic models capable of performing out appropriate treatment for complex signals, such as those coming from vibration. The ESvbrPAL2v was built on an ATMega2560 microcontroller, where vibration signals were captured from the mechanical structures of the machines by sensors and, after receiving special treatment through the Discrete Fourier Transform (DFT), then properly modeled to paraconsistent logic signals and vibration patterns. Using the PAL fundamentals, vibration signature patterns were built for possible and known vibration issues stored in ESvbrPAL2v and continuously compared through configurations composed by a network of paraconsistent algorithms that detects anomalies and generate signals that will report on the current risk status of the machine in real time. The tests to confirm the efficiency of ESvbrPAL2v were performed in analyses initially carried out on small prototypes and, after the initial adjustments, tests were carried out on bearings of a group of medium-power motor generators built specifically for this study. The results are shown at the end of this study and have a high index of signature identification and risk of failure detection. These results justifies the method used and future applications considering that ESvbrPAL2v is still in its first version.

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Section: Paraconsistent Annotated Logic -Palmentioning

confidence: 99%

Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures

Correa

Machado

Filho

et al. 2022

RSD

View full text Add to dashboard Cite

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“…A Lógica Paraconsistente (LP), pertence a uma categoria de lógicas não clássicas e sua principal característica, é a revogação do princípio da não contradição (Da Costa & Abe, 2000) (Abe et al, 2018).…”

Section: Lógica Paraconsistente Anotada (Lpa)unclassified

Configuração de uma Rede Neural Artificial Paraconsistente para o Método de Aprendizado por Demonstração aplicado à um Braço Robótico

Gomes

Fernandes

Filho

et al. 2022

RSD

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A Lógica Paraconsistente Anotada – LPA é uma lógica não clássica, baseada em conceitos que permitem, sob certas condições, aceitar a contradição em seus fundamentos, sem invalidar as conclusões. Interpretações matemáticas em seu reticulado associado, possibilitam a obtenção de equações e construções de algoritmos, que formam redes de análise paraconsistentes eficientes, em tratar sinais simulando aprendizagem. O algoritmo utilizado nesta pesquisa, é denominado de Célula Neural Artificial Paraconsistente de aprendizagem (CNAPap), e foi criado a partir das equações baseadas em LPA. Com sinais padronizados repetidamente aplicados à sua entrada, a CNAPap é capaz de armazenar gradativamente estas informações, aumentando ou diminuindo seu nível de resposta na saída com variação assintótica, controlado por um Fator de Aprendizagem (FA). Para executar os testes, um conjunto de cinco CNAPaps formando uma Rede Neural Artificial Paraconsistente de aprendizagem (RNAPap), foi implementado em um microcontrolador ATMEGA 328p e vários ensaios foram realizados para validar o seu funcionamento, atuando no aprendizado por demonstração (LfD) em um Robô Manipulador. Considerando a frágil estrutura mecânica do Robô Manipulador, e dos dispositivos sensores adaptados para responder aos padrões, os resultados laboratoriais obtidos nos diversos testes apresentados foram satisfatórios, e o Sistema microprocessado construído respondeu de modo eficiente, onde os níveis de acertos, corresponderam entre 75% a 90%, em todas as etapas do método de LfD. Os resultados de estudos comparativos, mostraram que a RNAPap possui propriedades dinâmicas com capacidade de atuar, tanto no método de aprendizagem por demonstração, como no método de imitação.

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“…However, inconsistencies arise naturally when using real data (da Costa and Abe, 2000). Similarly, Xindong and Zhu (2008) stated that data obtained from real-world problems are never perfect and undergo changes that may hinder the system's performance.…”

Section: Introductionmentioning

confidence: 99%

Impact of an Extra Layer on the Stacking Algorithm for Classification Problems

Lorbieski

Nassar

2018

Journal of Computer Science

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Classifying and making decisions are tasks performed by any human being in their daily lives. Learning algorithms have been widely studied as tools to aid information management, with an objective to maximize the generalization capacity. Learning algorithms can be used individually or as a committee of machines (ensembles). An ensemble uses the solutions provided by several machines, making different combinations with them to reach a final decision, such as multi-layer algorithm stacking. When combining combination methods, one arrives at a three-layered architecture, which is the focus of this article. The objective of this work was to evaluate the influence of adding one more layer in the stacking metalearning algorithm in other to obtain accuracy, area under ROC and time in relation to the lower layers, under the influence of the experiment, database and level factors. It was possible to conclude that, statistically, classifiers of the extra layer presented, in a general way, better performance in terms of accuracy and area. However, time grew sharply at each top layer added.

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Paraconsistência em informática e inteligência artificial

Cited by 6 publications

References 12 publications

Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures

Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures

Configuração de uma Rede Neural Artificial Paraconsistente para o Método de Aprendizado por Demonstração aplicado à um Braço Robótico

Impact of an Extra Layer on the Stacking Algorithm for Classification Problems

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