In this paper, we develop a methodology to evaluate public risk with n misfortune levels. Public risk is assumed to be evaluated by three attributes such as the number of people suffering each misfortune level, ex-post equity and ex-ante equity. A utility function for each attribute is proposed and a multiattribute utility function, which is assumed to be additive for these three attributes, is constructed. As a numerical example, we apply the methodology to a noise pollution problem of Kansai International Airport. In view of public risk in Osaka Bay area, two alternatives are compared according to launching/landing conditions of airplanes.
This paper presents a method for concept formation of the surfaces of a two-dimensional multimodal function. We use the concepts 'TOP', 'SIDE' and 'BOTTOM' of a mountain as basic concepts for representation of those surfaces. These basic concepts for each point on surfaces are defined by 'IF-THEN' rules. The concepts formation of the surfaces are made based on those basic concepts and the results can be compared with concepts of the surfaces formed by human subjects. And then the similarity between them can be confirmed. The proposed method is useful in making a machine-oriented concept formation of surfaces such as topographic maps.
A dynamic simulation method to estimate vibration and positioning error of industrial manipulators is proposed. This method has the merit that it needs only the same amount of calculation time as simulation methods ignoring elasticity, although it considers joint deformation. By some simulation experiments, the following facts are found : (1) The proposed method can calculate vibration, positioning error and actuator torques at the stage of off-line teaching. (2) The positioning error which cannot be measured by angular position sensors fixed at actuators can be large. (3) By the effect of flexibility of joints, actuator torques of manipulators can be larger than the calculation results ignoring elasticity of joints. (4) Selection of gears is important because backlashes at joints affect the characteristics of vibration and positioning error. The proposed method would be useful in the stages of the off-line teaching and the design of manipulators.
In this paper, the set-cover theoretical diagnosis model proposed by Reggia et al. is extended to allow a fuzzy occurrence of symptoms. In the Reggia's model, each disorder has the set of possible manifestations which is represented by the possible causal relations, and this relation represents the knowledge that disorder ci may cause manifestation ej. In addition to this relation, we introduce the necessary causal relation which represents the knowledge that disorder ci always causes manifestation ej. By this relation, the information that manifestation ej doesn't occur in the patient can be available for the diagnosis process. In order to diagnose the fuzzy symptoms, we propose the method for constructing the belief function on the frame of diagnosis hypotheses. The upper and lower probabilities of each diagnosis hypothesis and each disorder are obtained from this belief function.
A method is presented to deal with the eigenvalue problem for symbolic matrices on the basis of rational operations. From difficulties in solving higher order algebraic equations with symbolic coefficients, it is impossible to obtain the Jordan normal form of a higher order symbolic matrix in a usual sense. Jordan decomposition on the field of rational expressions is considered, which can be performed by symbolic manipulation. The semisimple and the nilpotent components are obtained by substitution of the matrix into polynomials with coefficients of rational expressions. The polynomials are calculated from the characteristic polynomial by rational operations such as irreducible factor decomposition, partial fractional decomposition and multiple reduction. The method for operations of linear subspaces by symbolic manipulation proposed by the authors are applicable to derivations of the generalized eigenspaces and the Jordan normal forms for the eigenvalues in rational expressions.