Abstract: Complex information technology for communications gesture and mimicry modeling and visualization is created.

Keywords: modeling, sign language, computer system, visual-speech synthesis and analysis.

ACM Classification Keywords: I.2.8 Problem Solving, And Search H.1.1 Systems and Information

Link:

CONSTRUCTION OF A REALISTIC MOVEMENT ON THE 3D HUMAN MODEL FOR STUDYING AND LEARNING SIGN LANGUAGE

Iurii Kryvonos, Iurii Krak, Anton Ternov

http://foibg.com/ijita/vol18/ijita18-4-p06.pdf

Abstract: In the paper the programmable logic array (PLA) topological optimization problem is dealt with using folding techniques. A PLA folding algorithm based on the method of simulated annealing is presented. A simulated-annealing PLA folding algorithm is presented for multiple unconstrained folding. Then, the algorithm is extended to handle constrained folding. In this way, simple folding is considered as a case of multiple constrained folding. Some experimental results of computer investigation of the suggested algorithms are given.

Keywords: design automation, area optimization, VLSI structure folding, simulated annealing.

ACM Classification Keywords: B.6.3 Logic Design: Design Aids – Optimization; B.7.2 Integrated circuits: Design Aids –Layout.

Link:

OPTIMIZING PROGRAMMABLE LOGIC ARRAYS USING THE SIMULATED ANNEALING ALGORITHM

Liudmila Cheremisinova, Irina Loginova

http://foibg.com/ijita/vol18/ijita18-4-p05.pdf

Abstract:This paper deals with finding low autocorrelation binary sequences which is a hard combinatorial optimization problem. Recent developments in this area analyzed, in order to understand characteristics of a problem. Emphasis is put on effective energy recomputation operators. Different types of these operators are tested to achieve full picture of LABS solvers development process. It is shown that latest state-of-the-art metaheuristics in fact all based on simplest Tabu Search framework, achieving performance boost by means of energy recomputation operators’ optimization. In this paper we construct variation of memetic algorithmincorporating latest developments to reach higher performance than it’s original. Comparison to a state-of-the-art TSv7 approach completed on instances with known optimums as well as on some unsolved larger ones. It is concluded that these approaches shows similar performance as they both have the same built-in heuristic. As further research proposed a comparison of different metaheuristic frameworks applied to this problem.

Keywords: combinatorial optimization, low autocorrelation binary sequences, memetic algorithm,stochastic local search, tabu search.

ACM Classification Keywords: G. 1. 6. Mathematics of Computing, Numerical Analysis, Optimization.

Link:

EFFECTIVE ENERGY RECOMPUTATION FOR LOW AUTOCORRELATION BINARY SEQUENCE PROBLEM

Leonid Hulianytskyi, Vladyslav Sokol

http://foibg.com/ijita/vol18/ijita18-4-p04.pdf

Abstract: In the paper new hybrid cascade wavelet-neural network and its learning algorithm in batch and on-line mode are proposed. Such architecture can be used for solving prediction and emulation non-stationary non-linear time series under current and a-priori uncertenity. The computational experiments confirm the effectiveness of developed approach.

Keywords: cascade neural network, wavelet-neuron, learning algorithm, prediction, emulation.

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

Link:

HYBRID CASCADE NEURAL NETWORK BASED ON WAVELET-NEURON

Yevgeniy Bodyanskiy, Oleksandra Kharchenko, Olena Vynokurova

http://foibg.com/ijita/vol18/ijita18-4-p03.pdf

Abstract: The revue of results obtained by the author this year in the area of disturbance of statistical stability of physical quantities and processes is presented. Two new sensitive parameters characterizing their statistical instability in finite observation interval are proposed. For known and new parameters of statistical instability unit measures that give possibility to characterize the level of disturbance are introduced. It is shown by modeling that STD corridors of unit measures weakly depend from the type of the distribution. It is confirmed that important role in disturbance of statistical stability plays specific fluctuation of expectation of the process that generates changes of average expectation. Dependence of parameters of statistical instability from normalized sample variance of expectation average is found. It is shown by modeling that positive correlation calls increasing of statistical instability and negative correlation – decreasing of it. Under any type correlation increasing of sample size calls increasing of statistical stability and the process trends to statistically stable state. It is found that changes of variance influence to statistical stability of the process. Under some relations of parameters unpredictable component of the process fades-out and under other ones – fades-in. It is demonstrated high sensitivity of new parameter of statistical instability. It is shown that fluctuations of maximum day temperature and minimum day temperature in two cities (Moscow and Kiev) are instable and fluctuation of day precipitation is near stable. Disturbance of statistical stability of temperature begins from some observation weeks.

Keywords: statistical instability, theory of hyper-random phenomena, uncertainty, probability.

ACM Classification Keywords: G.3 Probability and Statistics

Link:

DISTURBANCE OF STATISTICAL STABILITY (PART II)

Igor Gorban

http://foibg.com/ijita/vol18/ijita18-4-p02.pdf

Abstract: Number of Disciplines and Theories changed their status from status of Natural Science discipline to Mathematics. The Theory of Probability is the classical example of that kind. The main privilege of the new, Math, status is the conception of Math truth, which distinguish Math from other theories. Some disciplines, used in Applications, pretended to be Math, not being such. It’s entirely true for Fuzzy Subsets Theory with its pretension to be Math and to be exclusive tools in uncertainty handling. Fundamental pretensions of classical Fuzzy subset theory including pretension to be math is discussed as well as the some gaps of the theory are discussed in the article. Statistical interpretation of membership functions is proposed. It is proved, that such the interpretation take place for practically all supporters with minimal constraint on it. Namely, a supporter must be the space with a measure. The interpretation proposed makes it clear the modifying of the classical fuzzy object to correct the gaps. It becomes possible to say about observations of fuzzy subset within the conception of modification and to extend Likelihood method on the new area. Fuzzy likelihood equation adduced as example of new possibilities within approach proposed. One more interpretation for the Fuzzy subset theory is proposed to discuss: multiset theory one.

Keywords: f Uncertainty, Plural model of uncertainty, Fuzzy subsets Theory, statistical interpretation of the membership function, modification of Fuzzy subsets, Fuzzy likelihood equation, Multiset theory.

ACM Classification Keywords: G.2.m. Discrete mathematics: miscellaneous,G.2.1 Combinatorics. G.3 Probability and statistics, G.1.6. Numerical analysis I.5.1.Pattern Recognition: Models Fuzzy sets; H.1.m. Models and Principles: miscellaneous:

Link:

FUZZY SETS AS A MEAN FOR UNCERTAINTY HANDLING: MATH, APPLIED MATH, HEURISTICS

Volodymyr Donchenko

http://foibg.com/ijita/vol18/ijita18-4-p01.pdf

Abstract: The article presents the characteristic of surfaces having functional properties. It discusses the parameters used to describe the roughness of this type of surfaces. It proposed the method of constructing software which calculates probability parameters.

Keywords: two-process surfaces, roughness parameters.

ACM Classification Keywords: Algorithm, Measurement.

Link:

DESCRIPTION OF SURFACES HAVING STRATIFIED FUNCTIONAL PROPERTIES

Wiesław Graboń

http://foibg.com/ibs_isc/ibs-23/ibs-23-p24.pdf

Abstract: This study explores and compares predictive abilities of six types of neural networks used as tools for computer-aided breast cancer diagnosis, namely, multilayer perceptron, cascade-correlation neural network, and four ART-based neural networks. Our experimental dataset consists of 803 patterns of 39 BI-RADS, mammographic, sonographic, and other descriptors. Using such a combination of features is not traditional in the field and we find it is better than traditional ones. The study also focuses on exploring how various feature selection techniques influence predictive abilities of the models. We found that certain feature subsets show themselves as top candidates for all the models, but each model performs differently with them. We estimated models performance by ROC analysis and metrics, such as max accuracy, area under the ROC curve, area under the convex hull, partial area under the ROC curve with sensitivity above 90%, and specificity at 98% sensitivity. We paid particular attention to the metrics with higher specificity as it reduces false positive predictions, which would allow decreasing unnecessary benign breast biopsies while minimizing the number of delayed breast cancer diagnoses. In order to validate our experiments we used 5-fold cross validation. In conclusion, out results show that among the neural networks considered here, best overall performer is the Default ARTMAP neural network.

Keywords: data mining, neural networks, heterogeneous data; breast cancer diagnosis, computer aided diagnosis.

ACM Classification Keywords: I.5.1- Computing Methodologies - Pattern Recognition – Models - Neural Nets

Link:

PERFORMANCE OF COMPUTER-AIDED DIAGNOSIS TECHNIQUES IN INTERPRETATION OF BREAST LESION DATA

Anatoli Nachev, Mairead Hogan, Borislav Stoyanov

http://foibg.com/ibs_isc/ibs-23/ibs-23-p23.pdf

Abstract. This article deals with the issue of Business Intelligence (BI), especially its next generation - Business Discovery(BD). This tool can help to fill the gap between traditional solutions we get from BI and standalone office productivity applications. Its users are able to forget new paths and make new discoveries. Here we want to present BD as being thoroughly complementary to traditional ERP, CRM, BI, and data warehousing systems. BD brings a whole new level of analysis, insight and value to the information stored within these systems. What is more, its users are not burdened with interfaces which are difficult to use and configure.

Keywords: Business Intelligence, Business Discovery, information, analysis, Qlickview

ACM Classification Keywords: K.6 Management of Computing and Information Systems - K.6.0 General Economics

Link:

BUSINESS DISCOVERY – A NEW DIMENSION OF BUSINESS INTELLIGENCE

Justyna Stasieńko

http://foibg.com/ibs_isc/ibs-23/ibs-23-p22.pdf

Abstract: An important application of the information technology (IT), which is the creation and improvement of Information Systems for Metrology (ISM) is discussed. These systems initially had a form of Metrological Database (MD) and Metrological Knowledge Bases (MKB). At present, the advanced versions of these systems have a form of the Metrological Expert Systems (MES) using artificial intelligence methods. Two selected examples of Information Systems for Metrology and their practical use are described. An actual state of the ISM ("CAMPV System") designed and developed in the Department of Metrology and Diagnostic Systems, Faculty of Electrical and Computer Engineering at Rzeszow University of Technology, is presented. The system consist of the portal for communication with the system via the Internet and the Metrological Database (MD) collecting the data on the specification of measurement equipment as well as the data obtained in the process of equipment calibration. It has been planned that the system will be expanded by adding the Analytical Metrological Database (AMD) and Metrological Knowledge Base (MKB). A full version of "CAMPV-Expert System" will be dedicated to the computer-aided design of electrical and electronic measurement channels as well as the computer-aided validation of measurement processes, which include such channels.

Keywords: information systems for metrology, metrological databases, metrological knowledge bases, metrological expert systems.

ACM Classification Keywords: A.0 General Literature - Conference proceedings

Link:

INFORMATION SYSTEMS FOR METROLOGY

Roman A. Tabisz, Łukasz Walus

http://foibg.com/ibs_isc/ibs-23/ibs-23-p21.pdf

Abstract: A simulation is reliable when the simulation time is much longer than the relaxation time of the quantities in question. The aim of this work is to address the question when Molecular Dynamics (MD) simulation is reliable and how it depends on the integration algorithms and optimal time step. There were certain problems related to the choice of integration algorithms on Molecular Dynamics simulations. The effect of time step on convergence to equilibrium in Molecular Dynamics simulation has been studied.

Keywords: Molecular Dynamics, computer simulations, integration algorithms

ACM Classification Keywords: A.0 General Literature - Conference proceedings

Link:

STUDY OF INTEGRATION ALGORITHM AND TIME STEP ON MOLECULAR DYNAMIC SIMULATION

Janusz Bytnar, Anna Kucaba-Piętal?

http://foibg.com/ibs_isc/ibs-23/ibs-23-p20.pdf

Abstract: The paper presents the structure of a database and a knowledge base which are the integral part of the Intelligent Decision Support System, being developed for a manufacturing company operating in the glass industry. Both modules will be used in the advisory system, whose functions will be classification of defects of products (here: glass packaging, e.g. bottles, jars) and selection of an appropriate (the most beneficial) method of elimination of defects arising in the manufacturing process.

Keywords: intelligent decision support systems, knowledge base, knowledge representation, reasoning process.

ACM Classification Keywords: I. Computing Methodologies, I.2.1 Applications and Expert Systems, J. Computer Applications

Link:

DATABASE AND KNOWLEDGE BASE AS INTEGRAL PART OF THE INTELLIGENT DECISION SUPPORT SYSTEM, CREATED FOR MANUFACTURING COMPANIES

Monika Piróg-Mazur?, Galina Setlak

http://foibg.com/ibs_isc/ibs-23/ibs-23-p19.pdf

Abstract: The article presents the neural network constructed in order to use it for monitoring. Its role is to recognize the events in alarm situations (theft, burglary etc.). The film presenting a real break-in into the car was used while testing this network. The main task of monitoring system based on the neural network is to compile such a network which shows the alarm situations as soon as possible using the available equipment.

Keywords: neutral network, monitoring system, neuron.

ACM Classification Keywords: I.2 Artificial Intelligence – I.2.6. Learning

Link:

ARTIFICIAL INTELLIGENCE IN MONITORING SYSTEM

Lucjan Pelc, Artur Smaroń, Justyna Stasieńko

http://foibg.com/ibs_isc/ibs-23/ibs-23-p18.pdf

Abstract: The paper summarizes the authors methodology for solving the intractable combinatorial problems in physical design of electronic devices: VLSI, SOC, PCB and other. The Optimal Circuit Reduction (OCR) method has proved to be an efficient and effective tool to identify the hierarchical clusters’ circuit structure. The authors review the applicability of this method for solving of some problems, including hierarchical clustering, partitioning, packaging, and placement. Developed approach based on multilevel decomposition with the recursive use of global and local optimization algorithms at it every level for unique, not very large size subproblems. At every step we receive some initial solutions which are improved by optimization algorithms. Experiments confirm the efficiency of developed approaches. For some well-known test cases the optimal results were achieved for the first time, while for many other cases improved results were obtained.

Keywords: VLSI, SOC and PCB physical design, hierarchical clustering, partitioning, packaging, placement

ACM Classification Keywords: B.7.2 Design Aids

Link:

MACROMODELING FOR VLSI PHYSICAL DESIGN AUTOMATION PROBLEMS

Roman Bazylevych, Marek Pałasiński, Lubov Bazylevych

http://foibg.com/ibs_isc/ibs-23/ibs-23-p17.pdf

Abstract: With steadily evolving new paradigms for technology enhanced learning, educational word games such as quizzes, puzzles and quests raise new appeal and motivation for students in following game based educational processes. Traditional word games may be applied more successfully to game based learning in given scientific domain provided they are highly oriented to the content and problems of that domain. Such games may be more efficient if they include artificial agents simulating opponents, advisors or collaborators of the player. Authors present a semantic structuring model of learning content for logic and word games serving for educational purposes and, next, show the place of artificial agents within the game construction and possible ways of agent’s realization. There are given results from practical experiments with playing a memory game using the semantic content model, without and with agents integrated into the game.

Keywords: Agents, quiz, word game, e-learning, game based learning.

Link:

SEMANTICALLY RICH EDUCATIONAL WORD GAMES ENHANCED BY SOFTWARE AGENTS

Boyan Bontchev, Sergey Varbanov, Dessislava Vassileva

http://foibg.com/ibs_isc/ibs-23/ibs-23-p16.pdf

Abstract: Excellence in Supply Chain Management depends on timely and effective translation of market demand into material and products control decisions across Supply Chain. As has been observed many times, this task may be complicated by several technical and business related constraints. Effective decision making processes are essential to execute Supply Chain in such a way that products will be made at lowest possible cost and delivered on time. In most cases, software support has to be used. Supply Chain related decisions are usually poorly structured and therefore only reasonable way to support them is to use simulation tools. The main aim of the paper is to show how Supply Chain Management process can be supported with Agent Oriented Simulation Platform. The case study presented describes in detail the decision situation that is analyzed from scratch, by simulating different scenarios for suggested problem solutions. Finally the paper shows how the analysis of simulation results may lead to final decision solving the problems encountered.

Keywords: Agent-based Models, Agent oriented Supply Chain Management, Agent-Based? Simulation and Modeling, Agent-orientation as Modeling Paradigm

ACM Classification Keywords: I. Computing Methodologies; I.2 Artificial Intelligence; I.2.11 Distributed Artificial Intelligence; Multi-Agent? Systems

Link:

TACTICAL MANAGEMENT OF SUPPLY CHAIN WITH AGENT BASED MODELING AND SIMULATION

Jacek Jakieła, Paweł Litwin, Marcin Olech

http://foibg.com/ibs_isc/ibs-23/ibs-23-p15.pdf

Abstract: In this paper we propose a modelling technique for the control of computational processes. The Petri Net model, particularly a Timed Event Graph (TEG) can be used for analyzing. The proposed model enables the determination of state equations. The max-plus algebra represents linear algebraic form of discrete systems and supplies new tools to their modelling. We develop a linear mathematical model under constraints in the Max-plus algebra. When using max-plus algebra with TEG, the arc weights are kept equal to one in order to be able to resolve the state equations. Structure of max-plus algebra is equipped with maximization and addition operations over of the real numbers and minus infinity. It can be used appropriately to determine marking times within a given Petri net and a vector filled with marking state at the beginning. Tools of max-plus algebra are useful to investigate properties of network models. Finally, numerical examples show the use of this model.

Keywords: Max-Plus-Linear? Systems, Petri Nets, Discrete Systems, Modelling Technique

ACM Classification Keywords: H. Information Systems, H.1 MODELS AND PRINCIPLES, H.1.1 Systems and Information Theory; D. Software D.4, OPERATING SYSTEMS, D.4.1 Process Management, Multiprocessing/multiprogramming/multitasking, Synchronization.

Link:

MODELLING AND CONTROL OF COMPUTATIONAL PROCESSES USING MAX-PLUS ALGEBRA

Jerzy Raszka, Lech Jamro

http://foibg.com/ibs_isc/ibs-23/ibs-23-p14.pdf

Abstract: This paper describes two analytical models of the process of an analysis of XML-formatted formulae of algorithms represented in a special editor created for the algebra of algorithms. For identification and storage of types and orientation of selected operations and uniterms, two XML-formatted model algorithms are developed. The ability is shown for transformation of formulae of algorithms that results in 5-time reduction of a number of uniterms while maintaining the functionality of the algorithm.

Keywords: Algebra of algorithms, algorithm formulae editor, transformation of algorithms.

Link:

MODELS OF THE PROCESS OF AN ANALYSIS OF XML-FORMATTED FORMULAE OF ALGORITHMS

Volodymyr Ovsyak, Krzystof Latawiec, Aleksandr Ovsyak

http://foibg.com/ibs_isc/ibs-23/ibs-23-p13.pdf

Abstract: The paper is a limited review of publications (1995-2010) related to the problem of classification of clinical records presented in a free text form. The techniques of indexing and methods of classification are considered. We also pay special attention to the description of document sets used in the mentioned research. Finally, we conclude about the perspective research directions related with the topic.

Keywords: Natural language processing, medical corpus, medical diagnostics, automatic medical classification

ACM Classification Keywords: I.2.7 Natural Language Processing

Link:

CLASSIFICATION OF FREE TEXT CLINICAL NARRATIVES (SHORT REVIEW)

Olga Kaurova, Mikhail Alexandrov, Xavier Blanco

http://foibg.com/ibs_isc/ibs-23/ibs-23-p12.pdf

Abstract: RICHE (Research Inventory of Child Health in Europe) is a platform developed and funded under the Health domain of 7th European Framework Program. The platform search engine is expected to use the multilingual taxonomy of terms for processing and classifying large volumes of documents of the RICHE repository. So far the experts participating in this project have produced the initial version of expert based taxonomy of terms relating to child health (based on existing taxonomies). In the paper we propose a simple man-machine technique for continuous support and development of the existing term list, which consists of three steps: 1) construction of various keyword lists extracted from a topic oriented document set using various levels of word specificity 2) selection of the most useful keyword lists using subjective criteria as a precision of selection and a number of new words 3) manual selection of new terms. Experimental material was represented by documents uploaded from three organizations active in child health improvement policies: World Bank, World Health Organization (WHO), and DG SANCO of European Commission (EC). The selection was performed in order to assess terms used in these documents that may be absent in the RICHE taxonomy. Presented work should be considered as a pilot (feasibility) study. The objective of the RICHE platform is to identify gaps in European child health research, so extensive mapping exercise has been started. Classification of identified studies is essential and cannot be based only on traditional terms of existing taxonomies. Emergent terms (such as for example “cyberbullying”) need to be identified and included into existing taxonomies. In our future work we focus on developing techniques related to multilevel and multiword term selection

Keywords: Child health, natural language processing, taxonomy, term selection

ACM Classification Keywords: I.2.7 Natural Language Processing

Link:

FOLKSONOMY - SUPPLEMENTING RICHE EXPERT BASED TAXONOMY BY TERMS FROM ONLINE DOCUMENTS (Pilot Study)

Aleš Bourek, Mikhail Alexandrov, Roque Lopez

http://foibg.com/ibs_isc/ibs-23/ibs-23-p11.pdf

Abstract: In this paper, we show how to represent to our formal reasoning and to model social context as knowledge using network models to aggregate heterogeneous information. We show how social context can be efficiently used for well understood tasks in natural language processing (such as context-dependent automated, large scale semantic annotation, term disambiguation, search of similar documents), as well as for novel applications such as social recommender systems which aim to alleviate information overload for social media users by presenting the most attractive and relevant content. We present the algorithms and the architecture of a hybrid recommender system in the activity centric environment Nepomuk-Simple? (EU 6th Framework Project NEPOMUK): recommendations are computed on the fly by network flow methods performing in the unified multidimensional network of concepts from the personal information management ontology augmented with concepts extracted from the documents pertaining to the activity in question.

Keywords: multidimensional networks, graph-based methods, network flow methods, data mining, natural language processing, recommender systems.

ACM Classification Keywords: H.3.4 Information Storage and Retrieval: Systems and Software – information networks; H.3.5 Information Storage and Retrieval: Online Information Services – data sharing.

Link:

SOCIAL CONTEXT AS MACHINE-PROCESSABLE KNOWLEDGE

Alexander Troussov, John Judge, Mikhail Alexandrov, Eugene Levner

http://foibg.com/ibs_isc/ibs-23/ibs-23-p10.pdf

Abstract: In this paper an example of multi-variant clustering is presented. The problems to be solved are described and multi-variant clustering based on pyramidal multi-layer multi-dimensional structures is outlined. The conclusion is that the multi-variant clustering combined with pyramidal generalization and pruning gives reliable results.

Keywords: Data mining, multi-variant clustering, pyramidal multi-layer multi-dimensional structures.

ACM Classification Keywords: H.2.8 Database Applications, Data mining; I.5.3 Clustering.

Link:

ABOUT MULTI-VARIANT CLUSTERING AND ANALYSIS HIGH-DIMENSIONAL DATA

Krassimira Ivanova, Vitalii Velychko, Krassimir Markov, Iliya Mitov

http://foibg.com/ibs_isc/ibs-23/ibs-23-p09.pdf

Abstract: The paper presents results of efforts of increasing predicting events accuracy by increasing a set of attributes describing the present moment by information included in past data. There are described two experiments verifying such an approach. The experiments were carried on by the use of the RSES system, which is based on the rough sets theory. The data analyzed in the first experiment, concerning the weather, were reported at the meteorological station in Jasionka near Rzeszów from 1 April 2004 to 30 september 2005. The second experiment deals with exchange rates based on the money.pl news bulletin data (http://www.money.pl).

Keywords: rough sets, prediction, temporal data.

Link:

ROUGH SET METHODS IN ANALYSIS OF CHRONOLOGICALLY ARRANGED DATA

Piotr Romanowski

http://foibg.com/ibs_isc/ibs-23/ibs-23-p08.pdf

Abstract: Number of Disciplines and Theories changed their status from status of Natural Science discipline to Mathematics. The Theory of Probability is the classical example of that kind. The main privilege of the new Math status is the conception of Math truth, which distinguishes Math from other theories. Some disciplines used in Applications pretended to be Math not really being it. It is entirely true of Fuzzy Subsets Theory with its pretension to be Math and to be exclusive tools in uncertainty handling. Fundamental pretensions of classical Fuzzy subset theory including pretension to be math as well as some gaps in the theory are discussed in the article. Statistical interpretation of membership functions is proposed. It is proved that such interpretation takes place for practically all supporters with minimal constraints on it. Namely, a supporter must be a space with a measure. Proposed interpretation explains modification of classical fuzzy objects to fill the gaps. It is then possible to talk about observations of fuzzy subset within the conception of modification and to extend likelihood method to the new area. Fuzzy likelihood equation is adduced as an example of new possibilities within the proposed approach. One more interpretation for the Fuzzy subset theory is proposed for a discussion: multiset theory.

Keywords: f Uncertainty, Plural model of uncertainty, Fuzzy subsets Theory, statistical interpretation of the membership function, modification of Fuzzy subsets, Fuzzy likelihood equation, Multiset theory.

ACM Classification Keywords: G.2.m. Discrete mathematics: miscellaneous,G.2.1 Combinatorics. G.3 Probability and statistics, G.1.6. Numerical analysis I.5.1.Pattern Recognition: Models Fuzzy sets; H.1.m. Models and Principles: miscellaneous:

Link:

FUZZY SETS: MATH, APPLIED MATH, HEURISTICS? PROBLEMS AND INTERPRETATIONS

Volodymyr Donchenko

http://foibg.com/ibs_isc/ibs-23/ibs-23-p07.pdf

Abstract: In presented work the further development of Box-Jenkins? technique for models constructing and improvement of themselves ARIMA models is produced. A novel autoregressive – spectral integrated moving average (ARSIMA) model founded on joint use of the Box-Jenkins? method (ARIMA models) and "Caterpillar"-SSA method with model trained on competitive base is developed.

Keywords: modeling, filtering, forecasting, control, "Caterpillar»-SSA method, ARIMA model, "Caterpillar»-SSA – ARIMA – SIGARCH method, ARSIMA model, ARSIMA – SIGARCH model, heteroskedasticity, Levenberg- Marquardt method.

Link:

ARSIMA MODEL

Vitalii Shchelkalin

http://foibg.com/ibs_isc/ibs-23/ibs-23-p06.pdf