Fuzzy Bigraphs: An Exercise in Fuzzy Communicating Agents

Bigraphs and their algebra is a model of concurrency. Fuzzy bigraphs are a generalization of birgraphs intended to be a model of concurrency that incorporates vagueness. More specifically, this model assumes that agents are similar, communication is not perfect, and, in general, everything is or happens to some degree.Comment: 11 pages, 3 figure

Modelling of Metallurgical Processes Using Chaos Theory and Hybrid Computational Intelligence

The main objective of the present work is to develop a framework for modelling and controlling of a real world multi-input and multi-output (MIMO) continuously drifting metallurgical process, which is shown to be a complex system. A small change in the properties of the charge composition may lead to entirely different outcome of the process. The newly emerging paradigm of soft-computing or Hybrid Computational Intelligence Systems approach which is based on neural networks, fuzzy sets, genetic algorithms and chaos theory has been applied to tackle this problem In this framework first a feed-forward neuro-model has been developed based on the data collected from a working Submerged Arc Furnace (SAF). Then the process is analysed for the existence of the chaos with the chaos theory (calculating indices like embedding dimension, Lyapunov exponent etc). After that an effort is made to evolve a fuzzy logic controller for the dynamical process using combination of genetic algorithms and the neural networks based forward model to predict the system’s behaviour or conditions in advance and to further suggest modifications to be made to achieve the desired results

Multi-criteria analysis of fuzzy symptoms of electrical faults in power systems

The paper considers a possible method of technical diagnostics of electrical equipment of power supply systems and electrical substations based on the fuzzy sets and fuzzy logic. It is shown that, based on the matrix of fuzzy relationships, one can make a plausible enough prediction about possible malfunctions and causes of failures. The prerequisites for this analysis are the current condition (state) of the electrical equipment and expert assessments of diagnostic signs. The paper shows the comparison made using the features scale of Saaty, in accordance with nine degrees of preference. At the core of fuzzy expert assessments is an attempt to formalize linguistic information, namely linguistic variables whose meanings can be words or phrases. The paper presents a complete range of preconditioned defects consisting of m factors and their corresponding space conclusions as to the causes of these malfunctions (defects) of n symptoms. Fuzzy causal relations in the space of underlying factors are established between the assumptions and conclusions of the experts. The resulting system of equations is solved by the method based on the composition of fuzzy conclusions. Possible failures are ranked according to the experts’ preference, which reveals the most significant symptoms of malfunctioning and allows arriving at the conclusion as to the future operation of the facility. The validity of the provisions of the method presented is confirmed by appropriate calculations, which demonstrates the correct behavior of the model concerning the transformer equipment. It is shown that in case of the fuzzy symptoms occurrence and evaluation of these features by a scale of preferences, it is possible to conclude about the further operation of electrical equipment or its withdrawal for repair. Thus, the mathematical model based on the fuzzy relations of symptoms selected using the experts’ estimations contains elements of predicting the possible failures of power systems electrical equipment