João Inácio da Silva Filho

Paraconsistent Algorithm Extractor of Contradiction Effects - Paraextrctr ctr

Nowadays networks of analyses based in non-classic logics are used with success in the treatment of uncertainties. The characteristic of accepting the contradiction in his structure is the main cause of the methodologies based in Paraconsistent Logic is ideals for applications in systems of analyses and decision making. In this work we presented an algorithm based in Paraconsistent logic capable to extract in a gradual way the effects of the contradiction in originated signals of information of uncertain knowledge database. The Algorithm Paraconsistent Extractor of Contradiction effects - Paraextrctrctr is formed with base in fundamental concepts of the Paraconsistent Annotated Logic with annotation of two values (PAL2v) it can be applied in filters of networks of analyses of signal information where uncertain and contradictory signals can be present. The process of extraction of the effect of the contradiction is always begun by the largest inconsistency degree among two signals that belong to the group that is in analysis. In the end of the analysis it is found a consensus value. In this work we presented numeric example and one example of application of the Paraextrctrctr in Load Profile Forecast used in support to decision of the operation in an Electric Power System, but his application potentiality is demonstrated in several fields of the Artificial Intelligence.

A sensing system for an autonomous mobile robot based on the paraconsistent artificial neural network

This paper shows a sensing system for an autonomous mobile robot. The Sensing System is based on the Paraconsistent Neural Network. The type of artificial neural network used in this work is based on the Paraconsistent Evidential Logic - Eτ. The objective of the Sensing System is to inform the other robot components the position where there is an obstacle. The reached results have been satisfactory.

Autonomous Mobile Robot Emmy III

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic Eτ. A discussion on navigation system is presented.

Application of Paraconsistent Artificial Neural Network in Statistical Process Control acting on voltage level monitoring in Electrical Power Systems

In this paper, we present an application of the Paraconsistent Artificial Neural Network (PANnet) in a Statistical Process Control to trigger alarms in an electrical power System. The PANnet is based on Paraconsistent Annotated Logic (PAL) which is a non-classical logic with properties of accepting contradictions in their fundamentals. In this work, we make a joint application technique of Paraconsistent Annotated logic, in the form of PANnet, with the concepts of Statistical Process Control (SPC). The Statistical Process Control Paraconsistent (SCP-PAL) is used in this paper to make a dynamic monitoring of the conditions of the electrical voltage in an electrical power system. To test and validate the functioning of SPC-PAL Controller we use data obtained by random computational processes and we also use a database with actual values generated by a power electrical System of a company installed in Brazil. The SPC-PAL Controller, due to the use of the algorithms of PAL in its construction, has some features that does afford optimized electrical voltage monitoring. The result of the analysis made with the SPC-PAL Controller provides three types of alarms: (1) rapid Variation in the voltage; (2) Imbalance of Mean in the Voltage data; (3) High dispersion index in the voltage data. Based on these three types of alarms we can obtain a better understanding about the operating state of the electrical power system. In the various tests performed, the SPC-PAL Controller presented a good performance and detected changes in Mean and in the variation of tension, as well as sudden changes in voltage data.

Analysis and Diagnosis of Cardiovascular Diseases through the Paraconsistent Annotated Logic

All over the world cardiovascular diseases are responsible for a great number of clinical problems that result in death. Arterial Hypertension is considered one of the main agents of such diseases and, for that reason, the correct detection of Hypertension symptoms is very important for the medical area. In this work we use the Paraconsistent Logic (PL) as a method of treatment of uncertainties to help health professionals that act in this medical area. With base in the concepts of the Paraconsistent Logic we created a Expert System for the help in the analysis and diagnosis in cardiovascular diseases. This computational system is called “ParaHyper Analyzer” and it uses Algorithms of the Paraconsistent Logic, a non-classical kind of logic, for the treatment of contradictory information. The algorithms are obtained through the interpretation of the representative Lattice of Paraconsistent Annotated Logic with annotation of two values (PAL2v), where the certainty degree (DC) and the contradiction degree (Dct) are calculated, according to the logical methodology. The PAL2v algorithms are called Paraconsistent Analysis Nodes (PAN). The PAN allows the analysis of propositions which are related to changes in the blood pressure, so that the patient can be classified in a certain risk group. The ParaHyper Analyzer studies this information and presents a result which shows the possibility of developing a serious cardiovascular disease.

The Importance of Paraconsistency and Paracompleteness in Intelligent Systems

Nowadays, paraconsistent logic and paracomplete logic have established a distinctive position in a variety of fields of knowledge. The last systems are among the most original and imaginative systems of non-classical logic developed in the last and present century. Annotated logics are a kind of paraconsistent, paracomplete, and non-alethic logic.

The sensing system for the autonomous mobile robot Emmy III

This paper shows the results of the sensing system which was designed for the autonomous mobile robot Emmy III. The proposed Sensing System has as its mean part the Paraconsistent Neural Network. This artificial neural network is based on the Paraconsistent Evidential Logics — Et. The objective of the Sensing System is to inform the other robot components about the obstacle position. The reached results have been satisfactory.

Results of a sensing system for an autonomous mobile robot based on the paraconsistent artificial neural network

This paper shows the results of a sensing system for an autonomous mobile robot. The sensing system is based on the paraconsistent neural network. The type of artificial neural network used in this work is based on the paraconsistent evidential logic (Eτ). The objective of the sensing system is to inform the other robot components the obstacle position. The reached results have been satisfactory.

Some Aspects on Complementarity and Heterodoxy in Non-Classical Logics

Abstract In this work we discuss complementarity and heterodoxy in non-classical logics, exemplifying with the paraconsistent Cn systems introduced and studied mainly by Costa.

Paraconsistent Artificial Neural Network for Structuring Statistical Process Control in Electrical Engineering

In this study, we present an algorithmic structure based on paraconsistent annotated logic (PAL) that can simulate the calculi of average values present in a dataset and detect the variations of the average using only PAL concepts. We call the structure as paraconsistent artificial neural network for extraction of moving average (PANnet\(_\mathrm{{MovAVG}})\). As an example of its application, we use PANnet\(_\mathrm{{MovAVG}}\) to assist in the analysis of a final product quality index related to electrical engineering. To obtain the final result, we applied PANnet\(_\mathrm{{MovAVG}}\) to simulate the statistical behavior of the Statistical Process Control (SPC) by comparing values obtained with a ranking that establishes quality index standards based on electrical power distribution. First, tests were conducted using data with random values to verify the behavior of PANnet\(_\mathrm{{MovAVG}}\) and to set the optimum number of algorithms to form an optimized computational structure. Then, we used a database with actual electric voltage values generated by an electrical power system of an electrical power utility grid in Brazil. In the various tests, PANnet\(_\mathrm{{MovAVG}}\) appropriately detected changes and identified variations of electric voltage in 220-V transmission lines. The results show that PANnet\(_\mathrm{{MovAVG}}\) can be used to construct an efficient architecture for determining and monitoring quality scores with applications in various areas of engineering, especially for detecting quality index in an electricity distribution network.