A generalized approach to fuzzy optimization

A new approach to fuzzy optimization based on the generalization of Bellman-Zadeh's (BZ) concept is proposed in this article. It consists of a parametric generalization of intersection of fuzzy sets and a generalized defuzzification method. This approach allows the solving of a fuzzy mathematical programming (FMP) problem without transformation to a crisp one. It takes into account all possible fuzzy decisions and allows the degree of conjunction of criteria and constraints to vary. BZ method can be considered a special case of the approach proposed here. A simple algorithm for noniterative solving FMP problem is proposed whereas well-known Zimmermann's approach uses numerical methods. an illustrative example is presented. © 1994 John Wiley & Sons, Inc.     

Proprietes magnetiques d'echantillons polycristallins de CrWO4

The study of the temperature dependence of EPR and Mössbauer spectra on polycristalline samples of CrWO₄, pure and doped with small quantities of ⁵⁷Fe, shows the presence of an antiferro-paramagnetic transition between 40 and 45 K. The magnetic susceptibility displays a broad maxium at a higher temperature ($\text{T}{}_{\max }\text{? 100}\text{K}$). The crystal structure suggests a monodimensional magnetic system but a simple model of linear chains with Heisenberg exchange does not fit the experimental data. Non-negligible interchain exchange and/or some anisotropy in the intrachain magnetic interactions could be responsible for this discrepancy.     

Propagation of transient SH-waves in a dipping structure by finite- and boundary element methods

Summary The boundary and the finite element formulations for the equations of elasticity are presented and applied to the problem of propagation of transient SH-waves in dipping layers overlying a half-space. When the finite element formulation is used, appropriate boundary conditions are imposed on the additional boundary dividing the half-space into a finite and an infinite region. These conditions ensure the transmission of waves across this boundary. When the boundary element method is applied, it is necessary to satisfy the radiation conditions. Theoretical seismograms for the displacement on the surface of the half-space are presented. They show that, for a specific case, the agreement between the two methods is satisfactory. The results can be compared with those found by the exact method of generalized rays in order to check the validity of the finite and the boundary element methods for the specific problem studied in this paper.     

Structure and properties of thermoluminescent calcium fluoride glass-ceramic materials

New types of material for use inγ-dosimetry described here are glass-ceramics and silicate glass-ceramic enamels with thermoluminescent properties containing up to 30 wt% CaF₂ doped with MnO₂ and rare earth oxides. The structure and thermoluminescent properties of these materials have been investigated by applying a variety of complementary methods: X-ray analysis, electron microscopy, differential thermal analysis, electron paramagnetic resonance measurements and volume dilatometry. Thermal history, i.e. phase composition and degree of crystallinity, largely determines the thermoluminescent properties of the vitro-crystalline materials investigated. Optimal heat treatment favouring appropriate crystallization leads to a maximum in thermoluminescent intensity. Completely amorphous materials containing 20 to 30 wt% CaF₂ in the form of a glassy solution are devoid of any thermoluminescence. The thermoluminescent properties of natural fluorite are compared with those of synthetic materials.     

Identification of evolving fuzzy rule-based models

An approach to identification of evolving fuzzy rule-based (eR) models is proposed. eR models implement a method for the noniterative update of both the rule-base structure and parameters by incremental unsupervised learning. The rule-base evolves by adding more informative rules than those that previously formed the model. In addition, existing rules can be replaced with new rules based on ranking using the informative potential of the data. In this way, the rule-base structure is inherited and updated when new informative data become available, rather than being completely retrained. The adaptive nature of these evolving rule-based models, in combination with the highly transparent and compact form of fuzzy rules, makes them a promising candidate for modeling and control of complex processes, competitive to neural networks. The approach has been tested on a benchmark problem and on an air-conditioning component modeling application using data from an installation serving a real building. The results illustrate the viability and efficiency of the approach.     

A framework for analysis and design of software reference architectures

Context

A software reference architecture is a generic architecture for a class of systems that is used as a foundation for the design of concrete architectures from this class. The generic nature of reference architectures leads to a less defined architecture design and application contexts, which makes the architecture goal definition and architecture design non-trivial steps, rooted in uncertainty.

Objective

The paper presents a structured and comprehensive study on the congruence between context, goals, and design of software reference architectures. It proposes a tool for the design of congruent reference architectures and for the analysis of the level of congruence of existing reference architectures.

Method

We define a framework for congruent reference architectures. The framework is based on state of the art results from literature and practice. We validate our framework and its quality as analytical tool by applying it for the analysis of 24 reference architectures. The conclusions from our analysis are compared to the opinions of experts on these reference architectures documented in literature and dedicated communication.

Results

Our framework consists of a multi-dimensional classification space and of five types of reference architectures that are formed by combining specific values from the multi-dimensional classification space. Reference architectures that can be classified in one of these types have better chances to become a success. The validation of our framework confirms its quality as a tool for the analysis of the congruence of software reference architectures.

Conclusion

This paper facilitates software architects and scientists in the inception, design, and application of congruent software reference architectures. The application of the tool improves the chance for success of a reference architecture.     

ESR study of CuO-doped cordierite

The reactivity of cordierite precursor with CuO powder was studied by means of X-ray diffraction measurements and electron spin resonance spectroscopy. Two concentrations of CuO were used: 10 and 20 mol %. An ESR signal was detected after heating the mixture of cordierite precursor-CuO at 500°C showing that CuO begins to dissolve with the cordierite precursor. The reactivity strongly increased between 700 and 800°C, in relation to the transition amorphous -cordierite. However, the crystallization of -cordierite prevented the dissolution. Cu²⁺ was located in the amorphous phase and characterized byg=2.35 andg=2.08.     

An approach to online identification of Takagi-Sugeno fuzzy models.

An approach to the online learning of Takagi-Sugeno (TS) type models is proposed in the paper. It is based on a novel learning algorithm that recursively updates TS model structure and parameters by combining supervised and unsupervised learning. The rule-base and parameters of the TS model continually evolve by adding new rules with more summarization power and by modifying existing rules and parameters. In this way, the rule-base structure is inherited and up-dated when new data become available. By applying this learning concept to the TS model we arrive at a new type adaptive model called the Evolving Takagi-Sugeno model (ETS). The adaptive nature of these evolving TS models in combination with the highly transparent and compact form of fuzzy rules makes them a promising candidate for online modeling and control of complex processes, competitive to neural networks. The approach has been tested on data from an air-conditioning installation serving a real building. The results illustrate the viability and efficiency of the approach. The proposed concept, however, has significantly wider implications in a number of fields, including adaptive nonlinear control, fault detection and diagnostics, performance analysis, forecasting, knowledge extraction, robotics, behavior modeling.