This paper presents the fault diagnostic method using neural network and fuzziness of sensor readings. Neural network trains the data of abnormal patterns are acquired from the fault tree. And sensor readings are processed by membership functions. In diagnosis, attaching factor is inputted in neural network, then the cause of process malfunction is inferred. A pilot plant is used to demonstrate the effectiveness of proposal method.
We study aspects of obtaining field theories with noncommuting time-space coordinates as limits of open-string theories in constant electric-field backgrounds. We find that, within the standard closed-string backgrounds, there is an obstruction to decoupling the time-space noncommutativity scale from that of the string fuzziness scale. We speculate that this censorship may be string-theory's way of protecting the causality and unitarity structure. We study the moduli space of the obstruction in terms of the open- and closed-string backgrounds. Cases of both zero and infinite brane tensions as well as zero string couplings are obtained. A decoupling can be achieved formally by considering complex values of the dilaton and inverting the role of space and time in the light cone. This is reminiscent of a black-hole horizon. We study the corresponding supergravity solution in the large-N limit and find that the geometry has a naked singularity at the physical scale of noncommutativity. (C) 2000 Elsevier Science B.V.
In an axiomatic way a divergence between fuzzy sets is introduced which extends the symmetric difference between crisp sets. Any fuzzy measure of the divergence between two fuzzy sets weighs their “distance”. The distance between a fuzzy set and the family of crisp sets is fuzziness measure.
The aim of this paper is to analyze the behavior of models which describe the population dynamics taking into account the subjectivity in the state variables or in the parameters. The models in this work have demographic and environmental fuzziness. The environmental fuzziness is presented using a life expectancy model where the fuzziness of parameters is considered. The demographic fuzziness is presented using the continuous Malthus and logistic discrete models. An outstanding result in this case is the emergence of new fixed points and bifurcation values to the discrete logistic model with subjective state variables in form of fuzzy sets. An interpretation is offered for this fact which differs from the deterministic one. (C) 2000 Elsevier Science B.V.
The aim of the paper is to identify optimal and near-optimal distillation sequences according to a particular objective function definition. The potential solutions are valuated from the point of view of practical considerations, rather than purely costing methods. Four rules of thumb addressing column sequencing, expressed in vague and imprecise terms, are implemented and quantified by the fuzzy set theory. The integer programming problem is solved by a Branch and Bound procedure, where the bounding and branching schemes are carried out from the four heuristic rules, with fuzzy quantification. Furthermore the fuzzy set theory is also implemented for modelling data uncertainties, particularly the partial molar flow rates. From the results obtained with the fuzzy branch and bound procedure involving fuzzy data, we conclude that fuzzy set theory can be considered as a promising tool for modelling uncertainty and vagueness, and may have many other applications in Process Systems Engineering. (C) 2000 Elsevier Science B.V. All rights reserved.
Vagueness of knowledge results from the imprecision and uncertainty of knowledge. In fuzzy theory, much attention has being paid to the measure of fuzziness of a fuzzy subset, while entropy, as a measure of uncertainty, plays a significant role in the field of information theory. The paper discusses, when there is or not a probability distribution on the non-empty definite universe U, the measure of fuzziness and entropy of a fuzzy subset and the conditional fuzzy entropy of a fuzzy subset, when there exists additional probability information and fuzzy information.