Transformations of fuzzy graphs specified by <Emphasis Type="Italic">FD</Emphasis>-grammars

The categorical approach is proposed to formalize transformations of FD-graphs that consist of networks of distributed components whose nodes are specified by fuzzy graphs. Necessary and sufficient conditions are formally defined for FD-graph transformations that do not violate structure integrity and can be constructed componentwise. FD-grammars that generalize fuzzy graph grammars are proposed to describe the admissible transformations of FD-graphs. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 129–147, March–April 2007.     

Transformational approach to the development of software architectures on the basis of fuzzy graph models

An approach to the creation of software architectures is examined that is based on the model-oriented paradigm that opens up the way to the implementation of transformational evolution of software systems. The emphasis is on the formalization of fuzzy graphs, fuzzy graph models, and rules of their transformation. A theoretical categorical representation of fuzzy software architectures is developed, which allows one to manage the process of their transformations on the basis of making decisions in a fuzzy modeling space on the functionality of the target platform-specific system. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 139–150, September–October 2008.     

Adaptive diagnostic system based on fuzzy relations

Causes (diagnoses) are retrieved and identified using observed effects (symptoms) based on fuzzy relations and Zadeh’s compositional rule of inference. An approach to designing adaptive fuzzy diagnostic systems is proposed. It allows solving fuzzy logic equations and designing and adjusting fuzzy relations using expert and experimental information. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 135–150, July–August 2009.     

Inventory control as an identification problem based on fuzzy logic

An approach is proposed to solving inventory control problems using information available on current demand and stock. The approach is based on identification of nonlinear dependences using fuzzy knowledge bases. By tuning a fuzzy model against a learning sample, model control actions can be made very close to an expert’s decision. This approach can further be developed by creating adaptive (neuro-fuzzy) inventory control models for enterprises and trading companies. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 123–133, May–June 2006.     

Fuzzy model tuning based on a training set with fuzzy model output values

The paper considers the training of a fuzzy model with the help of a training set with fuzzy model output values. Two ways are proposed for constructing fuzzy rule-based multifactor models that produce fuzzy numbers at their outputs. The problem of tuning such fuzzy models on the basis of a fuzzy training set is formulated, methods of its solution are considered, and relevant examples are presented. Computational experiments showed that training based on fuzzy data improves the modeling accuracy for both crisp and fuzzy test sets. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 26–32, May–June 2007.     

Linear interpolation in a fuzzy information space

An approach to solving a linear interpolation problem in a fuzzy information space is proposed. Two different schemes of interpolation are outlined: a heuristic one, based on the geometrical interpretation of operations, and an optimization one, based on the expansion principle. The results obtained allow performing fuzzy linear prediction. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 55–68, March–April 2006.     

Constrained fuzzy arithmetic: Basic questions and some answers

 The purpose of this paper is to critically examine the use of fuzzy arithmetic in dealing with fuzzy systems. It is argued that the well-known overestimation and other questionable results of standard fuzzy arithmetic have one common cause: constraints regarding linguistic variables involved are not taken into account. A general formulation of constrained fuzzy arithmetic – a nonstandard fuzzy arithmetic that takes into account these constraints – is presented and its basic characteristics are examined. More specific characteristics of constrained fuzzy arithmetic are then investigated for some common types of constraints.     

Event-driven grammars: relating abstract and concrete levels of visual languages

In this work we introduce event-driven grammars, a kind of graph grammars that are especially suited for visual modelling environments generated by meta-modelling. Rules in these grammars may be triggered by user actions (such as creating, editing or connecting elements) and in their turn may trigger other user-interface events. Their combination with triple graph transformation systems allows constructing and checking the consistency of the abstract syntax graph while the user is building the concrete syntax model, as well as managing the layout of the concrete syntax representation. As an example of these concepts, we show the definition of a modelling environment for UML sequence diagrams. A discussion is also presented of methodological aspects for the generation of environments for visual languages with multiple views, its connection with triple graph grammars, the formalization of the latter in the double pushout approach and its extension with an inheritance concept. This is a revised and extended version of a paper presented at the ICGT’04 conference, see [21].     

Identification of a nonlinear dependence by a fuzzy knowledgebase in the case of a fuzzy training set

This paper generalizes the method of identification of nonlinear dependences by a fuzzy knowledgebase to the case of fuzzy training sets. In such a set, terms are used to estimate inputs. The computer experiments performed showed that the fuzziness of experimental data is no obstacle to identification. The use of fuzzy training sets allows one to apply the proposed method to the identification of "input-output" dependences in medicine, economics, sociology, politics, and other areas in which experimental data are based on expert judgments. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 17–24, March–April 2006. An erratum to this article is available at .     

Unfolding semantics of graph transformation

Several attempts have been made of extending to graph grammars the unfolding semantics originally developed by Winskel for (safe) Petri nets, but only partial results were obtained. In this paper, we fully extend Winskel’s approach to single-pushout grammars providing them with a categorical concurrent semantics expressed as a coreflection between the category of (semi-weighted) graph grammars and the category of prime algebraic domains, which factorises through the category of occurrence grammars and the category of asymmetric event structures. For general, possibly nonsemi-weighted single-pushout grammars, we define an analogous functorial concurrent semantics, which, however, is not characterised as an adjunction. Similar results can be obtained for double-pushout graph grammars, under the assumptions that nodes are never deleted.     

Adaptive sampling in measuring traffic parameters in a computer network using a fuzzy regulator and a neural network

Adaptive sampling using a neural network and a fuzzy regulator is described as applied to computer network traffics. The objective of this approach is to maximally reduce the amount of data to be processed with preservation of acceptable measurement accuracy. The results of experimental verification of sampling efficiency are also presented that are based on the traffic data archive of a real computer network. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 46–54, May–June 2008.     

Probability propagation in fuzzy Bayesian belief networks with nondeterministic states

The conceptual basis of fuzzy Bayesian belief networks with nondeterministic states is considered. The concept of a fuzzy probability estimate as a fuzzy relation of special type is introduced and its geometrical interpretation is given. Functional transformations of fuzzy probability estimates are defined and a multidimensional linear interpolation procedure is developed. Fundamental aspects of information distribution in fuzzy Bayesian belief networks with nondeterministic states are considered. Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 153–169, November–December 2008.     

Fuzzy configuration of matching runtime implementation strategies

 With applications currently growing in complexity and range, increasing numbers of configuration problems are arising in compilers. Already many software systems offer multiple specialized implementation strategies and substrategies, differing in terms of applicability and/or cost, depending on the application context. Configurations then have to be created from the different strategies available in accordance with the application characteristics, the global optimization objective, and potential constraints on the strategies' combinability. In many cases, this results in a combinatorial, i.e., discrete, optimization problem. Proper solutions for automating the configuration while limiting the complexity of the solution search are still being sought. We address here the field of parallel/distributed processing and the configuration of runtime implementation strategies, such as for communication or dynamic load balancing. We present a rule-based approach, integrating fuzzy methodologies for the classification of application characteristics and for gradual selection preference in rules. In this way we exploit available knowledge about the correlation of the problem and solution space, and apply soft computing methods to obtain an approximate, rather than perfect, solution approach, thus helping to limit the configuration complexity. Our approach extends standard fuzzy inference by a multistage organization, and – with proper organization of rules, characteristics and strategies – performs hierarchical fuzzy inference. The approach is demonstrated on concrete configuration examples in parallel compilers.     

Deep open-source machine translation

This paper summarizes ongoing efforts to provide software infrastructure (and methodology) for open-source machine translation that combines a deep semantic transfer approach with advanced stochastic models. The resulting infrastructure combines precise grammars for parsing and generation, a semantic-transfer based translation engine and stochastic controllers. We provide both a qualitative and quantitative experience report from instantiating our general architecture for Japanese–English MT using only open-source components, including HPSG-based grammars of English and Japanese.     

Experiments with nontraditional hybrid control technique of biped locomotion robots

By using the previously established zero-moment point theory and the semi-inverse approach [1–4] for solving the artificial gait synthesis based on the prescribed dynamics to part of the active mechanism, in this new approach to dynamic control of legged locomotion robots, the conventional control synthesis, based on complete dynamic robot model, is abandoned. The paper describes the simulation experiments of biped control with a hybrid approach that combines the traditional model-based and fuzzy logic-based control techniques. The combined method is developed by extending a model-based decentralized control scheme by fuzzy logic-based tuners for modifying parameters of joint servo controllers. The simulation experiments performed on a simplified two-legged mechanism demonstrate the suitability of fuzzy logic-based methods for improving the performance of the robot control system.     

Mathematical methods of geoinformatics. III. Fuzzy comparisons and recognition of anomalies in time series

The search for anomalies in time series by methods of fuzzy logic is further explored. The algorithms DRAS and FLARS underlying these methods are further developed in the form of the algorithm FCARS that is completely based on fuzzy comparisons. Parts 1 and 2 were published in Cybernetics and Systems Analysis, No. 2, 2002 and No. 4, 2003. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 3–18, May–June 2008.     

Football Predictions Based on a Fuzzy Model with Genetic and Neural Tuning

A model is proposed for predicting the result of a football match from the previous results of both teams. This model underlies the method of identifying nonlinear dependencies by fuzzy knowledge bases. Acceptable simulation results can be obtained by tuning fuzzy rules using tournament data. The tuning procedure implies choosing the parameters of fuzzy-term membership functions and rule weights by a combination of genetic and neural optimization techniques. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 171–184, July–August 2005.     

Simplification of a fuzzy mechanism with rule combination

 In this paper, a systematic approach to reduce the complexity of a fuzzy controller with the rule combination of a fuzzy rule base is presented. The complexity of a fuzzy controller is defined to be the computation load in this work. The proposed rule combination approach can be applied to the fuzzy mechanisms with product–sum and min–max inferences. With the input membership functions indexed in sequence for each input variable, the n-dimensional fuzzy rule table is represented as vectors so that the combination of the fuzzy rule base is realizable. Then the adjacent fuzzy rules with the same output consequent are combined to have smaller size of fuzzy rule base. The fuzzy mechanism with the combined rule table is shown to have the same output with the original fuzzy mechanism (without rule combination). Thus, in many applications, the rule combination approach presented in this paper can be used to reduce the complexity of the fuzzy mechanism without degrading the performances. Moreover, the Don't Care fuzzy rules are defined and it is indicated that the number of the necessary fuzzy rules might be decreased when the Don't Care fuzzy rules are taken into consideration. Further, the properties of the simplification approach for the fuzzy rule base of the fuzzy mechanism are discussed.     

Second-Order Abstract Categorial Grammars as Hyperedge Replacement Grammars

Second-order abstract categorial grammars (de Groote in Association for computational linguistics, 39th annual meeting and 10th conference of the European chapter, proceedings of the conference, pp. 148–155, 2001) and hyperedge replacement grammars (Bauderon and Courcelle in Math Syst Theory 20:83–127, 1987; Habel and Kreowski in STACS 87: 4th Annual symposium on theoretical aspects of computer science. Lecture notes in computer science, vol 247, Springer, Berlin, pp 207–219, 1987) are two natural ways of generalizing “context-free” grammar formalisms for string and tree languages. It is known that the string generating power of both formalisms is equivalent to (non-erasing) multiple context-free grammars (Seki et al. in Theor Comput Sci 88:191–229, 1991) or linear context-free rewriting systems (Weir in Characterizing mildly context-sensitive grammar formalisms, University of Pennsylvania, 1988). In this paper, we give a simple, direct proof of the fact that second-order ACGs are simulated by hyperedge replacement grammars, which implies that the string and tree generating power of the former is included in that of the latter. The normal form for tree-generating hyperedge replacement grammars given by Engelfriet and Maneth (Graph transformation. Lecture notes in computer science, vol 1764. Springer, Berlin, pp 15–29, 2000) can then be used to show that the tree generating power of second-order ACGs is exactly the same as that of hyperedge replacement grammars.