Abstract: Transition P Systems are a parallel and distributed computational model based on the notion of the cellular membrane structure. Each membrane determines a region that encloses a multiset of objects and evolution rules. Transition P Systems evolve through transitions between two consecutive configurations that are determined by the membrane structure and multisets present inside membranes. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of active evolution rules subset inside each membrane of the P system. But, to establish the active evolution rules subset, it is required the previous calculation of useful and applicable rules. Hence, computation of applicable evolution rules subset is critical for the whole evolution process efficiency, because it is performed in parallel inside each membrane in every evolution step. The work presented here shows advantages of incorporating decision trees in the evolution rules applicability algorithm. In order to it, necessary formalizations will be presented to consider this as a classification problem, the method to obtain the necessary decision tree automatically generated and the new algorithm for applicability based on it.

Keywords: Decision Tree, ID3, Evolution Rules, Applicability, Transition P System.

ACM Classification Keywords: I.2.6 Learning – Decision Tree; D.1.m Miscellaneous – Natural Computing

Link:

DECISION TREES FOR APPLICABILITY OF EVOLUTION RULES IN TRANSITION P SYSTEMS

Luis Fernandez, Fernando Arroyo, Ivan Garcia, Gines Bravo

http://www.foibg.com/ijita/vol14/ijita14-3-p05.pdf

Abstract: We discuss several approaches to similarity preserving coding of symbol sequences and possible connections of their distributed versions to metric embeddings. Interpreting sequence representation methods with embeddings can help develop an approach to their analysis and may lead to discovering useful properties.

Keywords: sequence similarity, metric embeddings, distributed representations, neural networks

ACM Classification Keywords: I.2.6 Connectionism and neural nets, E.m Miscellaneous, G.2.3 Applications

Link:

APPROACHES TO SEQUENCE SIMILARITY REPRESENTATION

Artem Sokolov, Dmitri Rachkovskij

http://www.foibg.com/ijita/vol13/ijita13-3-p11.pdf

Abstract: Modern enterprises work in highly dynamic environment. Thus, the developing of company strategy is of crucial importance. It determines the surviving of the enterprise and its evolution. Adapting the desired management goal in accordance with the environment changes is a complex problem. In the present paper, an approach for solving this problem is suggested. It is based on predictive control philosophy. The enterprise is modelled as a cybernetic system and the future plant response is predicted by a neural network model. The predictions are passed to an optimization routine, which attempts to minimize the quadratic performance criterion.

Keywords: enterprise strategy, model predictive control, neural network, black-box modeling, business trends.

ACM Classification Keywords: I.2.6 Artificial Intelligence: Neural nets; I.6.3 Simulation and Modeling: Applications

Link:

NEURAL NETWORK BASED APPROACH FOR DEVELOPING THE ENTERPRISE STRATEGY

Todorka Kovacheva, Daniela Toshkova

http://www.foibg.com/ijita/vol13/ijita13-2-p06.pdf

Abstract: Methods of analogous reasoning and case-based reasoning for intelligent decision support systems are considered. Special attention is drawn to methods based on a structural analogy that take the context into account. This work was supported by RFBR (projects 02-07-90042, 05-07-90232).

ACM Classification Keywords: I.2.6 Artificial intelligence: Learning – analogies; I.2.4 Artificial intelligence: Knowledge Representation Formalisms and Methods – semantic networks.

Link:

ANALOGOUS REASONING AND CASE-BASED REASONING FOR INTELLIGENT DECISION SUPPORT SYSTEMS

Alexander Eremeev, Pavel Varshavsky

http://www.foibg.com/ijita/vol13/ijita13-4-p03.pdf

Abstract: Usually, data mining projects that are based on decision trees for classifying test cases will use the probabilities provided by these decision trees for ranking classified test cases. We have a need for a better method for ranking test cases that have already been classified by a binary decision tree because these probabilities are not always accurate and reliable enough. A reason for this is that the probability estimates computed by existing decision tree algorithms are always the same for all the different cases in a particular leaf of the decision tree. This is only one reason why the probability estimates given by decision tree algorithms can not be used as an accurate means of deciding if a test case has been correctly classified. Isabelle Alvarez has proposed a new method that could be used to rank the test cases that were classified by a binary decision tree Alvarez, 2004. In this paper we will give the results of a comparison of different ranking methods that are based on the probability estimate, the sensitivity of a particular case or both.

ACM Classification Keywords: I.2.6 Learning – induction, concept learning; I.5.2 Classifier design and Evaluation

Link:

USING SENSITIVITY AS A METHOD FOR RANKING THE TEST CASES CLASSIFIED BY BINARY DECISION TREES

Sabrina Noblesse, Koen Vanhoof

http://www.foibg.com/ijita/vol13/ijita13-1-p01.pdf

Abstract: An approach is proposed for inferring implicative logical rules from examples. The concept of a good diagnostic test for a given set of positive examples lies in the basis of this approach. The process of inferring good diagnostic tests is considered as a process of inductive common sense reasoning. The incremental approach to learning algorithms is implemented in an algorithm DIAGaRa for inferring implicative rules from examples.

Keywords: Incremental and non-incremental learning, learning from examples, machine learning, common sense reasoning, inductive inference, good diagnostic test, lattice theory.

ACM Classification Keywords: I.2.6 Artificial Intelligence: Learning; K.2.3. Concept Learning

Link:

DIAGARA: AN INCREMENTAL ALGORITHM FOR INFERRING IMPLICATIVE RULES FROM EXAMPLES

Xenia Naidenova

http://www.foibg.com/ijita/vol12/ijita12-2-p10.pdf

Abstract: As is well known, the Convergence Theorem for the Recurrent Neural Networks, is based in Lyapunov´s second method, which states that associated to any one given net state, there always exist a real number, in other words an element of the one dimensional Euclidean Space R, in such a way that when the state of the net changes then its associated real number decreases. In this paper we will introduce the two dimensional Euclidean space R2, as the space associated to the net, and we will define a pair of real numbers ( x, y) , associated to any one given state of the net. We will prove that when the net change its state, then the product x ⋅ y will decrease. All the states whose projection over the energy field are placed on the same hyperbolic surface, will be considered as points with the same energy level. On the other hand we will prove that if the states are classified attended to their distances to the zero vector, only one pattern in each one of the different classes may be at the same energy level. The retrieving procedure is analyzed trough the projection of the states on that plane. The geometrical properties of the synaptic matrix W may be used for classifying the n-dimensional statevector space in n classes. A pattern to be recognized is seen as a point belonging to one of these classes, and depending on the class the pattern to be retrieved belongs, different weight parameters are used. The capacity of the net is improved and the spurious states are reduced. In order to clarify and corroborate the theoretical results, together with the formal theory, an application is presented

Keywords: Learning Systems, Pattern Recognition, Graph Theory, Image Processing, Recurrent Neural Networks.

ACM Classification Keywords: I.2.6 Learning: Connectionism and neural nets; G.2.2. Graph Theory; I.4.0 Image processing software

Link:

A NEW APPROACH FOR ELIMINATING THE SPURIOUS STATES IN RECURRENT NEURAL NETWORKS

Víctor Giménez-Martínez?, Carmen Torres, José Joaquín Erviti Anaut, Mercedes Perez-Castellanos?

http://www.foibg.com/ijita/vol12/ijita12-2-p03.pdf

Abstract: The architecture of adaptive wavelet-neuro-fuzzy-network and its learning algorithm for the solving of nonstationary processes forecasting and emulation tasks are proposed. The learning algorithm is optimal on rateof convergence and allows tuning both the synaptic weights and dilations and translations parameters of waveletactivation functions. The simulation of developed wavelet-neuro-fuzzy network architecture and its learningalgorithm justifies the effectiveness of proposed approach.

Keywords: wavelet, adaptive wavelet-neuro-fuzzy network, recurrent learning algorithm, forecasting, emulation.

ACM Classification Keywords: I.2.6 Learning – Connectionism and neural nets

Link:

ADAPTIVE WAVELET-NEURO-FUZZY NETWORK IN THE FORECASTING AND EMULATION TASKS

Yevgeniy Bodyanskiy, Iryna Pliss, Olena Vynokurova

http://www.foibg.com/ijita/vol15/ijita15-1-p08.pdf

Abstract: The paper presents basic notions and scientific achievements in the field of program transformations, describes usage of these achievements both in the professional activity (when developing optimizing and unparallelizing compilers) and in the higher education. It also analyzes main problems in this area. The concept of control of program transformation information is introduced in the form of specialized knowledge bank on computer program transformations to support the scientific research, education and professional activity in the field. The tasks that are solved by the knowledge bank are formulated. The paper is intended for experts in the artificial intelligence, optimizing compilation, postgraduates and senior students of corresponding specialties; it may be also interesting for university lecturers and instructors.

Keywords: Knowledge bank; Ontology; Knowledge base; Ontology editor; Database editor; Knowledge processing; Program transformations; Optimizing compilation

ACM Classification Keywords: I.2.5 Artificial intelligence: programming languages and software

Link:

A WEB-SYSTEM FOR COMPUTER EXPERIMENTS IN THE FIELD OF PROGRAM TRANSFORMATIONS

Margarita Knyazeva, Alexander Kleshchev

http://www.foibg.com/ijita/vol13/ijita13-4-p05.pdf

Abstract: An approach for knowledge extraction from the information arriving to the knowledge base input and also new knowledge distribution over knowledge subsets already present in the knowledge base is developed. It is also necessary to realize the knowledge transform into parameters (data) of the model for the following decision-making on the given subset. It is assumed to realize the decision-making with the fuzzy sets’ apparatus.

ACM Classification Keywords: I.2.5 - Expert Systems; I.2.6 - Knowledge acquisition

Link:

METHODS OF ADAPTIVE EXTRACTION AND ANALYSIS OF KNOWLEDGEFOR KNOWLEDGE-BASE CONSTRUCTION AND FAST DECISION MAKING

Alexander Kuzemin, Darya Fastova, Igor Yanchevsky

http://www.foibg.com/ijita/vol12/ijita12-1-p13.pdf

Abstract: This paper presents an ontological model of the knowledge about Bulgarian iconographical artefacts. It also describes content-sensitive services for access, browse, search and group iconographical objects, based on the presented ontology that will be implemented in the multimedia digital library “Virtual encyclopedia of Bulgarian iconography”.

Keywords: Ontology, Bulgarian Iconography, Digital Libraries, Content-sensitive services.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, H.3.7 Digital Libraries – Collection, Dissemination, System issues.

Link:

TOWARDS CONTENT-SENSITIVE ACCESS TO THE ARTEFACTS OF THE BULGARIAN ICONOGRAPHY

Desislava Paneva, Lilia Pavlova-Draganova?, Lubomil Draganov

http://www.foibg.com/ijitk/ijitk-vol02/ijitk02-4-p03.pdf

Abstract: Preserving and presenting the Bulgarian folklore heritage is a long-term commitment of scholars and researchers working in many areas. This article presents ontological model of the Bulgarian folklore knowledge, exploring knowledge technologies for presenting the semantics of the phenomena of our traditional culture. This model is a step to the development of the digital library for the “Bulgarian Folklore Heritage” virtual exposition which is a part of the “Knowledge Technologies for Creation of Digital Presentation and Significant Repositories of Folklore Heritage” project.

Keywords: Knowledge Technologies, Ontology, Digital Libraries, Bulgarian Folklore, Ethnology.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, H.3.7 Digital Libraries – Collection, Dissemination, System issues.

Link:

USE OF KNOWLEDGE TECHNOLOGIES FOR PRESENTATION OF BULGARIAN FOLKLORE HERITAGE SEMANTICS∗

Detelin Luchev, Desislava Paneva, Konstantin Rangochev

http://www.foibg.com/ijitk/ijitk-vol02/ijitk02-4-p02.pdf

Abstract: In this paper a new double-wavelet neuron architecture obtained by modification of standard wavelet neuron, and its learning algorithm are proposed. The offered architecture allows to improve the approximation properties of wavelet neuron. Double-wavelet neuron and its learning algorithm are examined for forecasting nonstationary chaotic time series.

Keywords: wavelet, double-wavelet neuron, recurrent learning algorithm, forecasting, emulation, analytical activation function.

ACM Classification Keywords: I.2.6 Learning – Connectionism and neural nets

Link:

DOUBLE-WAVELET NEURON BASED ON ANALYTICAL ACTIVATION FUNCTIONS

Yevgeniy Bodyanskiy, Nataliya Lamonova, Olena Vynokurova

http://www.foibg.com/ijita/vol14/ijita14-3-p14.pdf

Abstract: In this article the notion of a mathematical model of domain ontology is introduced. The mathematical apparatus (unenriched logical relationship systems) is essentially used. The representation of various elements of domain ontology in its model is considered. These elements are terms for situation description and situations themselves, knowledge and terms for knowledge description, mathematical terms and constructions, auxiliary terms and ontological agreements. The notion of a domain model is discussed. The notions of a precise ontology and precise conceptualization are introduced. The structures of situations and knowledge and also their properties are considered. Merits and demerits of various classes of the domain ontology models are discussed.

Keywords: Domain ontology, domain ontology model, ontology language specification, kernel of extendable language of applied logic, unenriched logical relationship systems, enriched logical relationship systems, enrichment of logical relationship system.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, F.4.1. Mathematical Logic

Link:

MATHEMATICAL MODELS OF DOMAIN ONTOLOGIES1

Alexander Kleshchev, Irene Artemjeva

http://www.foibg.com/ijita/vol14/ijita14-1-p05.pdf

Abstract: Basic types of information resources for the computer knowledge bank on medical diagnostics are presented. They are observation ontology and some examples of observations bases from various fields of medicine. By the observation ontology observation bases can be formed, checked and used in the computer knowledge bank.

Keywords: computer knowledge bank on medical diagnostics, information resources, observation ontology, observations bases, observation group, observation

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods; H.2.8 Database Applications

Link:

FORMING KNOWLEDGE BASES IN THE COMPUTER KNOWLEDGE BANK ON MEDICAL DIAGNOSTICS 1

Mary Chernyakhovskaya

http://www.foibg.com/ijita/vol13/ijita13-4-p11.pdf

Abstract. An ontological representation of buyer interests’ knowledge in process of e-commerce is proposed to use. It makes it more efficient to make a search of the most appropriate sellers via multiagent systems. An algorithm of a comparison of buyer ontology with one of e-shops (the taxonomies) and an e-commerce multiagent system are realised using ontology of information retrieval in distributed environment.

Keywords: ontology, e-commerce, multiagent system.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods

Link:

ONTOLOGICAL APPROACH TO DOMAIN KNOWLEDGE REPRESENTATION FOR INFORMATION RETRIEVAL IN MULTIAGENT SYSTEMS

Anatoly Gladun, Julia Rogushina, Victor Shtonda+

http://www.foibg.com/ijita/vol13/ijita13-4-p10.pdf

Abstract: Building domain ontologies and applying them to different objectives, researchers faced the fact that many ontologies are associated with one another by one or another relations. Therefore, the problem arose to study relations among different ontologies of the same domains as well as of different ones. A formalization of a relation among domain ontologies is the analogous mathematical relation among mathematical models of these ontologies. The article considers the case when domain ontology model is represented by logical relationship system. Relations among domain ontologies give a possibility to reuse one ontology model when another ontology models are worked out and when new intellectual computer system for same or different domain is worked out.

Keywords: Mathematical model of domain ontology, ontologies representing the same conceptualisation, resemblance between ontologies, simplification of ontologies, composition of ontologies, intellectual task solver.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, F4.1. Mathematical Logic

Link:

AN ANALYSIS OF SOME RELATIONS AMONG DOMAIN ONTOLOGIES1

Alexander Kleshchev, Irene Artemjeva

http://www.foibg.com/ijita/vol12/ijita12-1-p12.pdf

Abstract: An effective mathematical method of new knowledge obtaining on the structure of complex objects with required properties is developed. The method comprehensively takes into account information on the properties and relations of primary objects, composing the complex objects. It is based on measurement of distances between the predicate groups with some interpretation of them. The optimal measure for measurement of these distances with the maximal discernibleness of different groups of predicates is constructed. The method is tested on solution of the problem of obtaining of new compound with electro-optical properties.

Keywords: New knowledge, Predicates, Complex objects, Primary objects, Maximal discernibleness.

ACM Classification Keywords: I.2.4 Artificial Intelligence: knowledge representation formalisms and methods.

Link:

NEW KNOWLEDGE OBTAINING IN STRUCTURAL-PREDICATE MODELS OF KNOWLEDGE

Valeriy Koval, Yuriy Kuk

http://www.foibg.com/ijita/vol12/ijita12-1-p10.pdf

Abstract: A mathematical apparatus for domain ontology simulation is described in the series of articles. This article is the second one of the series. It describes a few specialized extensions of the extendable languages of applied logic that was described in the first article of the series. A few examples of some ideas related to domain ontologies and formalization of these ideas using the language are presented.

Keywords: Extendable language of applied logic, ontology language specification, specialized extensions of the extendable language of applied logic.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, F4.1. Mathematical Logic

Link:

A MATHEMATICAL APPARATUS FOR ONTOLOGY SIMULATION. SPECIALIZED EXTENSIONS OF THE EXTENDABLE LANGUAGE OF APPLIED LOGIC1

Alexander Kleshchev, Irene Artemjeva

http://www.foibg.com/ijita/vol12/ijita12-3-p10.pdf

Abstract: A mathematical apparatus for domain ontology simulation will be described in the series of the articles. This article is the first one of the series. The paper is devoted to means for representation of domain models and domain ontology models, so here a logical language is used only as a means for formalizing ideas. The chief requirement to such a language is that it must have such a semantic basis that would allow us to determine the most exact approximation of a set of intended interpretation functions as often as possible. Another requirement closely connected with the foregoing one is that the awkwardness of expressing ideas in such a language must not considerably exceed the complexity of their expressing in natural language. There are two ways to meet the requirements. The first one is to define and fix a wide semantic basis of the language. In this case the semantic basis nonetheless can be insufficient for some applications of the language. Extending applications of the language can lead from time to time to the necessity of further extending its semantic basis, i.e. to the necessity of defining new and new versions of the language. The second way is to make the kernel of the language being as nearer to the semantic basis of the classical language as possible and to allow us to make necessary extensions of the kernel for particular applications. In this article the second way is used to define the extendable language of applied logic. The goal of this article is to define the kernel of the extendable language of applied logic and its standard extension. The standard extension of the language defines elements of the semantic basis that are supposed to be useful practically in all the applications.

Keywords: Extendable language of applied logic, ontology language specification, kernel of extendable language of applied logic, the standard extension of the language of applied logic.

ACM Classification Keywords :I.2.4 Knowledge Representation Formalisms and Methods, F4.1. Mathematical Logic

Link:

A MATHEMATICAL APPARATUS FOR DOMAIN ONTOLOGY SIMULATION. AN EXTENDABLE LANGUAGE OF APPLIED LOGIC1

Alexander Kleshchev, Irene Artemjeva

http://www.foibg.com/ijita/vol12/ijita12-2-p07.pdf

Abstract: A mathematical apparatus for domain ontology simulation will be described in the series of the articles The goal of this article is to define unenriched and enriched logical relationship systems that can be considered as mathematical models for domain ontologies. The extendable language of applied logic described in the previous articles of the series is used as the language of representation of these systems.

Keywords: Extendable language of applied logic, ontology language specification, kernel of extendable language of applied logic, unenriched logical relationship systems, enriched logical relationship systems, enrichment of logical relationship system.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, F4.1. Mathematical Logic

Link:

A MATHEMATICAL APPARATUS FOR DOMAIN ONTOLOGY SIMULATION. LOGICAL RELATIONSHIP SYSTEMS1

Alexander Kleshchev, Irene Artemjeva

http://www.foibg.com/ijita/vol12/ijita12-4-p07.pdf

Abstract: The article defines the class of domains with complicated structures, gives the definition of multilevel ontologies and determines the method for developing such ontologies.

Keywords: Domains with complicated structures, multilevel ontologies

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods, F4.1. Mathematical Logic

Link:

DOMAINS WITH COMPLICATED STRUCTURES AND THEIR ONTOLOGIES1

Irene Artemieva

http://www.foibg.com/ijita/vol15/ijita15-4-p04.pdf

Abstract: The paper is related with the problem of developing autonomous intelligent robots for complex environments. In details it outlines a knowledge-based robot control architecture that combines several techniques in order to supply an ability to adapt and act autonomously in complex environments. The described architecture has been implemented as a robotic system that demonstrates its operation in dynamic environment. Although the robotic system demonstrates a certain level of autonomy, the experiments show that there are situation, in which the developed base architecture should be complemented with additional modules. The last few chapters of the paper describe the experimentation results and the current state of further research towards the developed architecture.

Keywords: Intelligent robots, autonomous intelligent systems, autonomous robots. Artificial intelligence.

ACM Keywords: I.2.4.J – Representations, I.2.6.A – Analogies, I.2.6.E – Induction, I.2.8.G – Plan execution, formation, and generation, I.2.9.A – Autonomous Vehicles

Link:

KNOWLEDGE-BASED ROBOT CONTROL

Agris Nikitenko

http://www.foibg.com/ijita/vol15/ijita15-2-p05.pdf

Abstract: In different fields a conception of granules is applied both as a group of elements defined by internal properties and as something inseparable whole reflecting external properties. Granular computing may be interpreted in terms of abstraction, generalization, clustering, levels of abstraction, levels of detail, and so on. We have proposed to use multialgebraic systems as a mathematical tool for synthesis and analysis of granules and granule structures. The theorem of necessary and sufficient conditions for multialgebraic systems existence has been proved.

Keywords: granular computing, multirelations, multioperations.

ACM Classification Keywords: I.2.4 Knowledge representation formalisms and methods: relation systems.

Link:

MULTIALGEBRAIC SYSTEMS IN INFORMATION GRANULATION

Alexander Kagramanyan, Vladimir Mashtalir, Vladislav Shlyakhov

http://www.foibg.com/ijita/vol15/ijita15-1-p09.pdf

Abstract: The problems of constructing the selfsrtucturized systems of memory of intelligence information processing tools, allowing formation of associative links in the memory, hierarchical organization and classification, generating concepts in the process of the information input, are discussed. The principles and methods for realization of selfstructurized systems on basis of hierarchic network structures of some special class – growing pyramidal network are studied. The algorithms for building, learning and recognition on basis of such type network structures are proposed. The examples of practical application are demonstrated.

Keywords: knowledge discovery, classification, prediction, growing pyramidal networks, concept formation.

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods - Semantic networks, F.1.1 Models of Computation - Self-modifying machines (e.g., neural networks)

Link:

SELFSTRUCTURIZED SYSTEMS

Victor Gladun, Vitalii Velychko, Yurii Ivaskiv

http://www.foibg.com/ijita/vol15/ijita15-1-p01.pdf