Abstract: Notions of a successful system and an ecologically acceptable successful system are proposed. These notions are convenient for formalization of a received inventive problem solution idea by means of TRIZ. This name was proposed by G.S. Altshuller 1 as abbreviation of the Theory of Inventive Problem Solution. Such a formalization is useful for training a creator of a successful system or an ecologically acceptable successful system for the intensification of his creative efforts.

Keywords: inventive graph-scheme idea,system, sub-system, ,graph, algorithmic heuristic, TRIZ.

ACM Classification Keywords: H.1.1 MODELS AND PRINCIPLES Systems and Information Theory – General systems theory; I.6.1 SIMULATION AND MODELING Simulation Theory – Systems theory

Link:

SHORT GRAPH-SCHEME OF A SUCCESSFUL SYSTEM IDEA

Nikolay Kosovskiy

http://www.foibg.com/ijima/vol02/ijima02-02-p05.pdf

Abstract: A new approach for constructing an algorithmic basis for polynomial based recognition method is considered. On the contrary to the previously used technical approach based on polynomial power minimization the new one deals with information value of the items. The approaches are compared in AVO-polynomial framework over a same set of recognition tasks.

Keywords: estimates calculating algorithm, information value, algebraic approach, pattern recognition.

ACM Classification Keywords: I.5 Pattern Recognition — I.5.0 General.

Link:

USE OF INFORMATION VALUE IN AVO-POLYNOMIAL METHOD TRAINING

Alexander Dokukin

http://www.foibg.com/ijima/vol02/ijima02-02-p04.pdf

Abstract: This paper presents first results of the use of optical and synthetic-aperture radar (SAR) satellite images to crop classification in Ukraine. The study aims at optimizing SAR parameters to provide timely and economically efficient crop maps/area estimates for Ukrainian landscape. Integration of EO-1 and RADARSAT-2 is done for crop classification using support vector machine (SVM). Classification is carried out per-field. The results on using SAR data for summer crops classification look very promising enabling classification of major summer crops with 10-15% of commission and omission errors under a typical Ukrainian landscape.

Keywords: crop classification, SVM, satellite images, SAR multipolarization.

ACM Classification Keywords: I.4.8 Image Processing and Computer Vision Scene Analysis - Sensor Fusion.

Link:

CROP CLASSIFICATION IN UKRAINE USING SATELLITE OPTICAL AND SAR IMAGES

Nataliia Kussul, Sergii Skakun, Andrii Shelestov, Oleksii Kravchenko, Olga Kussul

http://www.foibg.com/ijima/vol02/ijima02-02-p03.pdf

Abstract: in the paper new recurrent adaptive algorithm for fuzzy clustering of data with missing values is proposed. This algorithm is based on fuzzy probabilistic clustering procedures and self-learning Kohonen’s rule using principle “Winner-Takes-More” with Cauchy neighborhood function. Using proposed approach it’s possible to solve clustering task in on-line mode in situation when the amount of missing values in data is too big.

Keywords: fuzzy clustering, Kohonen self-organizing network, learning rule, incomplete data with missing values.

ACM Classification Keywords: 1.2.6 Artificial Intelligence: Learning – Connectionism and neural nets; 1.2.8 Artificial Intelligence: Problem Solving, Control Methods, and Search – Control theory; 1.5.1 Pattern Recognition: Clustering – Algorithms.

Link:

ADAPTIVE FUZZY PROBABILISTIC CLUSTERING OF INCOMPLETE DATA

Yevgeniy Bodyanskiy, Alina Shafronenko, Valentyna Volkova

http://www.foibg.com/ijima/vol02/ijima02-02-p02.pdf

Abstract: We consider an improved model of the empirical risk minimization problem and its continuous relaxation. The continuous relaxation of the formulated problem is compared with the mathematical model used in the support vectors method. The results of numerical experiments comparing different models for problems with linearly inseparable sets are presented.

Keywords: cluster, decision rule, discriminant function, linear and nonlinear programming, nonsmooth optimization

ACM Classification Keywords: G.1.6 Optimization - Gradient methods, I.5 Pattern Recognition; I.5.2 Design Methodology - Classifier design and evaluation

Link:

A COMPARISON OF SOME APPROACHES TO THE RECOGNITION PROBLEMS IN CASE OF TWO CLASSES

Yurii I. Zhuravlev, Yuryi Laptin, Alexander Vinogradov, Aleksey Likhovid

http://www.foibg.com/ijima/vol02/ijima02-02-p01.pdf

Abstract. The individual educational trajectory (IET) is a medium-term didactic complex that provides optimal opportunities for developing the creative potential of the learner by taking into account his/her personality. It includes: 1) developing an individual informational environment; 2) tuning the didactical resources; 3) personalization of the interim goals; 4) planning personal learning and research activities; 5) considering the selforganization. In the paper we submit a model of IET called DMT. In contrast to the cognition trajectory developed by Kolyagin and Ganchev the DMT has no linear structure. The IET in our model consists of sections due to the interim goals and each section of it could be perceived as a beam whose spectrum consists of the listed above 5 components. So the architecture of DMT could be associated with the one of the skyscraper Taipei 101 (the abbreviation DMT stands for Didactic Model Taipei). The educational process in any section in the IET could be conducted in different manner that allows different didactic approaches to be applied with respect to the individualities of the learner. The particular didactic approaches we had applied in a case study held in 2011/2012 academic year are strongly influenced by some cybernetic ones in the Consequence Driven Systems (CDS) theory.

Keywords: didactical models, individual educational trajectory, elliptic arbelos, Socratic style teaching.

ACM Classification Keywords: D.4.8 Performance (Modeling and prediction), I.6.5 Model Development (Modeling methodologies), J.1 ADMINISTRATIVE DATA PROCESSING (Education)

Link:

APPLICATION OF SOME CYBERNETIC MODELS IN BUILDING INDIVIDUAL EDUCATIONAL TRAJECTORY

Borislav Lazarov

http://www.foibg.com/ijima/vol02/ijima02-01-p09.pdf

Abstract: Algorithms for soling artificial intelligence problems allowing to formalize by means of predicate language are presented in the paper. These algorithms use the modified Maslov’s inverse method. One of these algorithms is directly based on the inverse method, and the second one uses the inverse method and Ant algorithm’s tactics. The model example using the described algorithms is shown.

Keywords: artificial intelligence, pattern recognition, predicate calculus, inverse method of S.Yu.Maslov, complexity theory, Ant algorithms.

ACM Classification Keywords: I.2.4 ARTIFICIAL INTELLIGENCE Knowledge Representation Formalisms and Methods – Predicate logic, I.5.1 PATTERN RECOGNITION Models – Deterministic, F.2.2 Nonnumerical Algorithms and Problems – Complexity of proof procedures.

Link:

THE INVERSE MASLOV METHOD AND ANT TACTICS FOR EXHAUSTIVE SEARCH DECREASING

Tatiana Kosovskaya, Nina Petukhova

http://www.foibg.com/ijima/vol02/ijima02-01-p08.pdf

Abstract: This paper focuses on the problem of validation and verification of computer network simulation models. Authors propose to use special linguistic and program tools of CAD system TriadNS in this case. First of all it should be noted that TRiadNS is a computer system which was developed for computer network design. Simulation is the main method for investigation of designed computer networks. But it is very important to have a credible simulation result. It is necessary for target users to have sufficient confidence that results generated by a simulation run reflect real world operation to a large degree. Authors observe the specifications of the simulation model in TriadNS.Net, consider the program tools for simulation model analysis (information procedures and conditions of simulation) and propose to use them for simulation model validation and verification, debugging and testing. Besides, the authors suggest program tools including the intellectual agents and ontology for localization of mistakes determined during verification and validation processes. Moreover the authors show how the specific features of hierarchical simulation models in TRIADNS make the process of testing and debugging of simulation models flexible.

Keywords: simulation model, debugging, testing, computer networks, validation, verification.

ACM Classification Keywords: I.6 SIMULATION AND MODELING: I.6.8 Types of Simulation – Distributed. I.2 ARTIFICIAL INTELLIGENCE: I.2.5 Programming Languages and Software – Expert system tools and techniques.

Link:

LINGUISTIC AND PROGRAM TOOLS FOR DEBUGGING AND TESTING OF SIMULATION MODELS OF COMPUTER NETWORKS

Elena Zamyatina, Alexander Mikov, Roman Mikheev

http://www.foibg.com/ijima/vol02/ijima02-01-p07.pdf

Abstract: We study the problem of testing composite hypotheses versus composite alternatives when there is a slight deviation between the model and the real distribution. The used approach, which we called sub-optimal testing, implies an extension of the initial model and a modification of a sequential statistically significant test for the new model. The sub-optimal test is proposed and a non-asymptotic border for the loss function is obtained. Also we investigate correlation between the sub-optimal test and the sequential probability ratio test for the initial model.

Keywords: statistics, robustness, sequential analysis.

ACM Classification Keywords: G.3 PROBABILITY AND STATISTICS - Nonparametric statistics

Link:

SUB-OPTIMAL NONPARAMETRIC HYPOTHESES DISCRIMINATING WITH GUARANTEED DECISION

Fedor Tsitovich, Ivan Tsitovich

http://www.foibg.com/ijima/vol02/ijima02-01-p06.pdf

Abstract: This paper is devoted to studying the interrelations between most widely used scientometric indicators (in particular, Hirsch’s h-, Egghe’s g- and Zhang’s e- indexes) for several more or less realistic citation-paper rank distributions. The analysis is provided for both continuous and discrete representations and is illustrated further on with examples for simultaneous time evolution (during a scientific career) of these indicators, computed by using real life scientometric data. The aim of the study is to illuminate specific properties of the indicators, the pros and cons of their use in various situations (citation-paper rank distributions) and (hopefully) to contribute for a fair and better scientific assessment.

Keywords: citation-paper rank distributions, scientometric indicators, h-index, g-index, e-index, approximate relations, data analysis

ACM Classification Keywords: H. Information Systems, H.2. Database Management, H.2.8. Database applications, subject: Scientific databases; I. Computing methodologies, I.6 Simulation and Modeling, I.6.4. Model Validation and Analysis

Link:

CITATION-PAPER RANK DISTRIBUTIONS AND ASSOCIATED SCIENTOMETRIC INDICATORS – A SURVEY

Vladimir Atanassov, Ekaterina Detcheva

http://www.foibg.com/ijima/vol02/ijima02-01-p05.pdf

Abstract: We discuss the problem of connectivity within large-scale dynamic distributed information systems. Ad hoc system can adapt themselves through resource management or reconfiguration to achieve specific goals, such as functions, performance, energy budget and reliability. One of the mostly important goals is to keep a possibility of routing for any two nodes of the distributed system. Structure of the system can be described by a time-graph. In some moments of the time the structure of a network changes: new nodes can be included into the network and old nodes can be deleted. Thus the connectivity property of the time-graph is a logical function of time. A cause of disconnection may be technical (hardware failures, low energy, server overloading etc) or organizational (information secure, regular breaks or random interruptions). To improve the quality of service we have to control the distributed information system structure. The first step of a self-management (autonomic) system design is to describe permissible structures and forbidden structures. We propose to use the well-known method of graph grammars for this purpose. A finite set of graph grammar rules defines an infinite (but countable) set of permissible structures. An inference process allows us to get some permissible graph after doing of a finite sequence of steps. In this work we solve the problem of a set of graph grammar rules description for such property of graphs as connectivity. A detailed description of the rule set is used for rewriting of any graph (connected or disconnected) to a connected graph. Also we discuss a second step of a self-aware system design: including of the graph grammar into a feedback control cycle. An autonomic system has the property of selfawareness, i.e. the system contains its model and manages itself using this model. During a life-time cycle the current model can be compared with the permissible set described by graph grammar. If the current model isn’t belong to the permissible set then the distributed system turns a connectivity renewal process on. Some problems of graph grammar algorithms complexity are discussed.

Keywords: time-graph, grammar, autonomic system, ad hoc system.

ACM Classification Keywords: H. Information Systems: H.3 Information Storage and Retrieval: H.3.4 Systems and Software – Distributed systems. C. Computer Systems Organization: C.2 Computer-Communication? Networks: C.2.4 Distributed Systems – Distributed applications.

Link:

CONNECTIVITY CONTROL IN AD HOC SYSTEMS: A GRAPH GRAMMAR APPROACH

Alexander Mikov, Alexander Borisov

http://www.foibg.com/ijima/vol02/ijima02-01-p04.pdf

Abstract: Connections of detailed Petri N model and its component CN-net on the level of their structural and dynamic properties are investigated.

Keywords: component Petri net, components-places, components-transitions, languages of component net with components-places and component net with components-transitions.

ACM Classification Keywords: Petri net, language of Petri net, homomorphism, epimorphism, model, model verification.

Link:

COMPONENT MODELING: ON CONNECTIONS OF DETAILED PETRI MODEL AND COMPONENT MODEL OF PARALLEL DISTRIBUTED SYSTEM

Elena Lukyanova

http://www.foibg.com/ijima/vol02/ijima02-01-p02.pdf

Abstract: In this paper, we introduce an efficient improved tone mapping algorithm that can be used for displaying wide dynamic range (WDR) images on conventional display devices that are mainly of low dynamic range (LDR). That algorithm, which enhances the exponent-based tone mapping algorithm of Ofili et al., uses both local and global image information for improving the contrast and increasing the brightness of images. It also directly operates on the Bayer domain instead of the luminance/chrominance domain that is used by the vast majority of tone mapping algorithms. Experimental results performed on different WDR images show that we are able to get images that are more pleasant visually when compared to nine other tone mapping algorithms. These observations are also confirmed numerically through the use of the TMQI, an objective image quality measure.

Keywords: Wide dynamic range images, tone mapping, color filter array, contrast enhancement.

ACM Classification Keywords: A.0 General Literature - Conference Proceedings; I.4.3 Image Processing and Computer Vision – Enhancement

Link:

A JOINT GLOBAL AND LOCAL TONE MAPPING ALGORITHM FOR DISPLAYING WIDE DYNAMIC RANGE IMAGES

Alain Horé, Chika A. Ofili, and Orly Yadid-Pecht?, Fellow, IEEE

http://www.foibg.com/ijima/vol02/ijima02-01-p01.pdf

Abstract: Aspects of visual perception mechanism and pattern recognition methods are examined jointly. Latest results from neurophysiology in studying the visual system of living beings are discussed. Another view on coarse-to-fine approach for technical vision tasks is presented. On the basis of systemological analysis of neurophysiology sources a new hypothesis about visual neuron's functioning is proposed. This hypothesis explains the mechanism and takes into account receptive fields excitatory zones resizing during visual act.

Keywords: coarse-to-fine, neurons of visual system, intercellular processes, pattern recognition, image processing, variable resolution

ACM Classification Keywords: I.4.1 Digitization and Image Capture, I.5.1 Models

Link:

JOINT STUDY OF VISUAL PERCEPTION MECHANISM AND COMPUTER VISION SYSTEMS THAT USE COARSE-TO-FINE APPROACH FOR DATA PROCESSING

Anton Sharypanov, Alexandra Antoniouk, Vladimir Kalmykov

http://www.foibg.com/ijicp/vol01/ijicp01-03-p08.pdf

Abstract: During last decades grows the interest of investigators to the methods of using the third level features for increasing identification accuracy in automated fingerprint recognition systems. It was noticed that the poroscopical maps carry important information about fingerprint pores, namely, their number, sizes, coordinates etc. However, at creation of automated identification technique, there arises a problem in connection with impossibility of using directly the pixel-by-pixel comparison methods of corresponding images. In this paper, we propose technique for comparison of poroscopical maps, based on using investigated earlier structural proximity assessment measure, which was determined using the gradient field of images. The poroscopical map is determined using some known algorithms of image processing, namely binarization, segmentation etc. The results of poroscopical maps processing and comparative analysis of some items from the database of Hong Kong Polytechnical Institute are given. It is shown that the proposed technique for poroscopical maps processing can be used in AFRS for increasing the accuracy of fingerprint identification.

Keywords: Fingerprint, third level, pores, poroscopical map, gradient field, image proximity assessment.

ACM Classification Keywords: Image Processing and Computer Vision

Link:

NOVEL METHOD FOR ANALYSIS OF FINGERPRINT POROSCOPICAL MAPS

David Asatryan, Grigor Sazhumyan, Bagrat Sakanyan

http://www.foibg.com/ijicp/vol01/ijicp01-03-p07.pdf

Abstract: The work is devoted to methods and software tools of designing intelligent decision support systems (IDSS), which helps professionals (decision making persons) helping to diagnose complex problem situations on the example of complicated pathologies of view. Unlike traditional Bayesian belief networks, the proposed application of advanced multilevel (difficult-structured) networks, more convenient for complex research of the problem and providing expert data. Integration of Bayesian belief networks and Dempster-Shafer? method allows using at diagnostics both expert data, and numerical (probabilistic) data obtained in the result of measurements. The proposed approach is implemented in the prototype of the intelligent decision support system for diagnostics of difficult diseases of vision.

Keywords: intelligent system, decision support, diagnostics, problem situation, Bayesian belief network, Demster-Shafer? method.

ACM Classification Keywords: H.4.2 Information systems applications: Types of systems – Decision support; I.2.3 Artificial intelligence: Deduction and Theorem Proving – Uncertainty, "fuzzy," and probabilistic reasoning; I.2.4 Artificial intelligence: Knowledge Representation Formalisms and Methods – Bayesian belief network.

Link:

THE INTELLIGENT DECISION SUPPORT SYSTEM FOR DIAGNOSTIC OF DIFFICULT DISEASES OF VISION

Aleksandr Eremeev, Ruslan Khaziev, Irina Tcapenko, Marina Zueva

http://www.foibg.com/ijicp/vol01/ijicp01-03-p06.pdf

Abstract: The paper is devoted to the development of the new online handwritten mathematical expressions recognition system. The paper presents the recognition method to the handwritten symbols using fussy neural network NEFCLASS as a means for classification.

Keywords: online handwriting recognition, mathematical expressions, fuzzy logic, fuzzy neural networks, structural analysis, artificial neural network, genetic algorithm, conjugate gradient algorithm.

ACM Classification Keywords: I.5.2 Computing Methodologies - Pattern Recognition - Design Methodology - Pattern analysis. G.4 Mathematics of Computing – Mathematical Software - Algorithm design and analysis. I.5.1 Computing Methodologies - Pattern Recognition - Models - Structural.

Link:

Online Handwritten Mathematical Expressions Recognition System Using Fussy Neural Network

Edris Naderan

http://www.foibg.com/ijicp/vol01/ijicp01-03-p05.pdf

Abstract: The reasons for emerging OWL as a standard for ontology representation in the Semanic Web are discussed in the paper. OWL structre and possibilities for representing ontologies of transdisciplinary knowledge are outlined. Recommendations for using OWL at the interdisciplinary level are proposed.

Keywords: OWL, interdisciplinary research, ontology

ACM Classification Keywords: 1.2.4. Knowledge Representation Formalisms and Methods

Link:

OWL as a Standard Model for Transdisciplinary Knowledje Representation in Semantic Web

Andrey Mihailyuk

http://www.foibg.com/ijicp/vol01/ijicp01-03-p04.pdf

Abstract: The traditional approach (the comparison with a "reference" result) for evaluating quality of the technology to identify knowledge extracted from text arrays is badly applicable out of a need to create the reference answer for each specific set of electronic documents. In this paper we show that integral quantitative coefficients of recall, precision and F-measure can be used to assess effectiveness of linguistic technologies of knowledge identification in texts. Justifying the possibility of using the test collections method for the experimental validation of obtained efficiency coefficients, we propose the use of the approach based on mathematical statistics methods. The procedures of using sampling fraction of the indicator as a characteristic of evaluating the proportion of relevant documents in the general population are reviewed. The paper shows the argumentation to the fact that, in important practical cases of text collection samples, asymmetry of a confidence interval at the binomial distribution can be overcome by approximated transition to the normal distribution. We also propose the methods of determining the confidence interval for the indicator fraction that are based on Wilson approach, and the method of determining the required size of the relevant sample depending on the specified error and confidence probability as well.

Key worlds: evaluation of effectiveness, semistructured text information, test collections method, size sample

ACM Classification Keywords: H.3.3 .Information Search and Retrieval, I.2.4. Knowledge Representation Formalisms and Methods, G.3. Probability and statistics – Statistical computing

Link:

Solution of the Problem of Formal Evaluation of Effectiveness of the Technology Knowledge Identification in Semistructured Text Information

Nina Khairova, Nataliya Sharonova, Dmytro Uzlov

http://www.foibg.com/ijicp/vol01/ijicp01-03-p03.pdf

Abstract: The survey and analysis of new field in AI -computational intelligence (CI) is performed. The main components of CI- technologies, methods and applications are outlined, their interconnections are determined and analyzed. The interrelations between CI and soft-computing are established and discussed.

Keywords: computational intelligence, soft computing, neural networks, fuzzy logic, evolutionary modeling.

ACM Classification Keywords: I.2 Artificial Intelligence, I.2.11 Distributed Artificial Intelligence

Link:

System Analysis of Computational Intelligence Main Trends

Michael Zgurovsky, Yuriy Zaychenko

http://www.foibg.com/ijicp/vol01/ijicp01-03-p02.pdf

Abstract: This work aims at studying personal data analysis area, when confidentiality property of data is ensured. It is supposed that we are given partially critical social science data and prior to the submission of data to the public it is required to modify them so that confidential information is not disclosed, and that the analysis of these data did not differ from the analysis of raw data. Our work builds improved algorithms of class of classification and regression trees, which provide solution to the problem of generation of the so-called synthetic data. The new solution of generation takes into account the structure of the areas of privacy and is providing optimized tree replacement for synthetic data sets.

Keywords: classification, regression, data disclosure, synthetic data.

ACM Classification Keywords: H.1 Information Systems – Models and principles, I.2.0 Artificial intelligence.

Link:

Enhanced Cart Technologies in Partial Synthetic Data Generation

Levon Aslanyan, Vardan Topchyan

http://www.foibg.com/ijicp/vol01/ijicp01-03-p01.pdf

Abstract: The tissue type classification is presented using the neural networks. The multi-spectral images of uterine cervix were segmented using self-organizing Kohonen maps and k-means algorithm. Then, the classification of tissue types from computed segments was made using the cascade neural network, back propagating neural network, and RBF network. The basics of neural networks were briefly explained. The results were presented and analyzed, based on which, the conclusions were made.

Keywords: neural networks, decision making, intellectual systems, segmentation.

ACM Classification Keywords: I.2.1 Applications and Expert Systems - Medicine and science

Link:

THE ANALYSIS OF NEURAL NETWORKS’ PERFORMANCE FOR MEDICAL IMAGE CLASSIFICATION

Kateryna Malyshevska

http://www.foibg.com/ijicp/vol01/ijicp01-02-p11.pdf

Abstract: The article is devoted to the development of the new Automated Building Extraction system applied on High Resolution Satellite Imagery, which is based on an object-oriented approach and soft computing.

Keywords: building recognition, satellite imagery, neuro-fuzzy classifier NEFCLASS, genetic algorithm.

ACM Classification Keywords: 1.4.7 Computing Methodologies - Image Processing and Computer Vision – Feature Measurement - Size and shape. G.1.6 Mathematics of Computing – Numerical Analysis – OptimizationGradient? methods. I.4.8 Computing Methodologies - Image Processing and Computer Vision – Scene Analysis - Object recognition. I.5.1 Computing Methodologies - Pattern Recognition - Models - Neural nets.

Link:

Automated Building Extraction System Applied On High Resolution Satellite Imagery Using Fuzzy Neural Network

Svetlana Naderan

http://www.foibg.com/ijicp/vol01/ijicp01-02-p10.pdf

Abstract: New class of preconditioners for iterative algorithms of sparse linear systems solution built using basis matrix method and incomplete decomposition methodology has been proposed. Algorithms with static and dynamic restriction set along with additional refinement procedures have been presented. Results of developed algorithms' testing carried out on matrices from Tim Davis Matrix Collection have been given. Basing on received results, matrix classes, applying proposed preconditioners on which resulted in iterative algorithms speed-up and/or accuracy increase, have been identified

Keywords: linear systems, sparse matrices, poor conditioned matrices, preconditioners, basis matrix method.

ACM Classification Keywords: H.4.2 Information Systems Applications: Types of Systems: Decision Support.

Link:

BUILDING PRECONDITIONERS USING BASIS MATRIX METHOD

Volodymyr Kudin, Vsevolod Bohaienko

http://www.foibg.com/ijicp/vol01/ijicp01-02-p09.pdf

Abstract: The work proposes a method for estimating the stability index of alpha-stable distributions by using moments of fractional order. Provided numerical modeling has fully justified all of the results. Comparative analysis of the efficiency among the proposed method of estimating the stability index and widely used methods was performed. Proposal method is much simpler, far faster and substantially less memory required. Estimation of generalized Hurst exponent from time series of the ordinary Lévy process was performed. Multifractal fluctuation analysis method and evaluation based on stability index estimation were compared. The results of numerical modeling showed that proposed method for estimating the fractal properties of the ordinary Lévy process, based on stability index estimation via fractional order moments is a much more accurate.

Keywords: alpha-stable variables, stability index estimation, fractional order moments, multifractal stochastic processes, Hurst exponent, generalized Hurst exponent, ordinary Levy motion.

ACM Classification Keywords: G.3 Probability and statistics - Time series analysis, Stochastic processes, G.1 Numerical analysis, G.1.2 Approximation - Wavelets and fractals

Link:

ANALYSIS OF THE PROPERTIES OF ORDINARY LEVY MOTION BASED ON THE ESTIMATION OF STABILITY INDEX

Lyudmyla Kirichenko, Vadim Shergin

http://www.foibg.com/ijicp/vol01/ijicp01-02-p08.pdf