artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. this paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. for this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. the sugg...

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...

In this work several approaches to prediction of natural gas consumption with neural and fuzzy neural systems are analyzed and tested. The data covers daily natural gas load in two different regions of Poland. Prediction strategies tested in the paper include: single neural net module approach, combination of three neural modules, temperature context based method, and application of fuzzy neura...

A Petri net is an abstract formal model of the behavior of a system and information flow. The properties, concepts, and techniques of Petri net are so as to present it as a simple and strong method for describing and analyzing information flow and systems control. Fuzzy Petri Net (FPN) is an appropriate powerful model to emulate knowledge base systems using fuzzy rules. Yet, FPN model does not ...

This paper describes an intelligent assembly algorithm for part mating in an in-line continuous transfer system by integrating neural net work and fuzzy set theory. The fuzzy set theory copes with the imprecision and vagueness associated with actual assembly task, while the neural net theory copes with limitation of fixed fuzzy rule by learning. The assembly performance of the intelligent algor...