Table Of ContentStudies in Computational Intelligence 530
László T. Kóczy
Claudiu R. Pozna
Janusz Kacprzyk Editors
Issues and
Challenges of
Intelligent Systems
and Computational
Intelligence
Studies in Computational Intelligence
Volume 530
Series editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
e-mail: [email protected]
For furthervolumes:
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About this Series
The series ‘‘Studies in Computational Intelligence’’ (SCI) publishes new devel-
opmentsandadvancesinthevariousareasofcomputationalintelligence—quickly
andwithahighquality.Theintentistocoverthetheory,applications,anddesign
methods of computational intelligence, as embedded in the fields of engineering,
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computational intelligence spanning the areas of neural networks, connectionist
systems, genetic algorithms, evolutionary computation, artificial intelligence,
cellular automata, self-organizing systems, soft computing, fuzzy systems, and
hybrid intelligent systems. Of particular value to both the contributors and the
readership are the short publication timeframe and the world-wide distribution,
which enable both wide and rapid dissemination of research output.
László T. Kóczy Claudiu R. Pozna
•
Janusz Kacprzyk
Editors
Issues and Challenges
of Intelligent Systems
and Computational
Intelligence
123
Editors
László T.Kóczy JanuszKacprzyk
Department of Automation Systems Research Institute
Széchenyi István University PolishAcademy ofSciences
Gy}or Warsaw
Hungary Poland
ClaudiuR. Pozna
Department of InformationTechnology
Széchenyi István University
Gy}or
Hungary
ISSN 1860-949X ISSN 1860-9503 (electronic)
ISBN 978-3-319-03205-4 ISBN 978-3-319-03206-1 (eBook)
DOI 10.1007/978-3-319-03206-1
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Preface
The broadly perceived area of intelligent systems has been for quite a long time
an object of intensive research in various areas of science and technology,
exemplified by computer science, logic, mathematics, data analysis, knowledge
engineering, IT/ICT, mechatronics, automation, and robotics, just to name a few
more technology-oriented fields.
Novel avenues ofresearchhave appeared, and new opportunities of real-world
applicationshavefollowedanintensivedevelopmentofcomputationalintelligence
and soft computing that have enjoyed a rapid growth of popularity in recent
decades.
Asitisalwaysthecaseinsuchaperiodofarapidgrowth,theflowofnewtools
and techniques clearly implies new challenges, both conceptual, algorithmic, and
implementation. This is also the case of our area. The scientific community
throughitsinvolvementandhardworktriestopromotetheareaandnewtoolsand
techniques. One of the necessary, and effective and efficient ways for reaching
such goals is to prepare comprehensive exposures to the area and its main
applicationsthroughtheeditingofvolumescontainingcontributionsofprominent
and active researchers and scholars. This has been the case with this volume, too.
In such initiatives, a group of people who are committed to reach the above-
mentioned goal to promote new directions in an area usually meets at some
important scientific gathering and, after fruitful discussions triggered by confer-
encecontributions,questionsfromtheaudience,etc.,theideaofsuchavolumeis
born. This was the case with this volume too. Its idea has appeared as a result of
very interesting presentations and vivid discussions at the Fifth Gy}or Symposium
and First Hungarian-Polish Joint Conference on Computational Intelligence held
inGy}or,Hungary,inSeptember,2012.Then,duetoahighinterestofthescientific
community and its willingness to contribute to this important volume, the editors
havebeenabletogatheraverygoodcollectionofrelevantandoriginalpapersby
prominent representatives of many areas, relevant both to the theory and practice
of intelligent systems, artificial intelligence, computational intelligence, soft
computing, and the like. The contributions have been divided into seven
parts presenting first more fundamental and theoretical contributions, and then
applications in relevant areas.
v
vi Preface
Part I is devoted to conceptual and analytic foundations of the theory offuzzy
systems, and contains two papers.
V. A.Niskanen (‘‘Prospects for Truth Valuationin Fuzzy Extended Logic’’) is
concerned with an important problem of truth valuation in fuzzy logic, and its
related alternative ways to many-valued resolution at the meta-level. His analysis
is based on Zadeh’s fuzzy extended logic (FLe), and is performed on the meta--
level from the standpoint of philosophy of science.
D. Coufal (‘‘Coherence and Convexity of Euclidean Radial Implicative Fuzzy
Systems’’)discussesthecaseofrule-basedfuzzysystems,andconcentratesonone
oftheirimportantclasses,implicativefuzzysystems.Hismainconcernistoobtain
a class of necessary conditions for coherence of radial implicative fuzzy systems,
all that in an implicit form. The minimization of a certain function is employed.
Wecontinuewiththeanalysisofvariousaspectsoffuzzysetstheoryandfuzzy
logic in Part II in which emphasis is more on applications.
P.NowakandM.Romaniuk(‘‘CatastropheBondPricingwithFuzzyVolatility
Parameters’’) consider an important problem related to natural disasters and
catastrophes, which may imply huge losses to the individuals, communities,
regions,nations,andeventheworldasawhole.Theauthorsdealwiththeproblem
of catastrophe bonds that are issued to transfer the catastrophic risk to financial
markets. More specifically, they are concerned with the catastrophe bond pricing
using a combination of stochastic analysis and fuzzy sets theory. Notably, the
volatility of the interest rate and market price of risk are represented as fuzzy
numbers, and the Monte Carlo simulation approach is used.
A.BukovicsandL.T.Kóczy(‘‘EvaluatingConditionofBuildingsbyApplying
Fuzzy Signatures and R-fuzzy Operations’’) show a novel method for qualifying
andrankingresidentialbuildingsbasedonvariouspriorityaspectsandformaking
an optimum allocation of the material resources available for the renewal of the
buildings. Their model is based on many detailed technical-static expert reports
available to a stock of residential buildings in Budapest and stored in a database.
First, using fuzzy logic, a model for calculating a so-called status characteristic
value between 0 and 1 on the basis of the structures and status of the buildings is
developed using a fuzzy singleton signature model. Then, a hierarchy is devised
relatedtothestockofbuildingstobeemployedforsupportingdecisionmakingon
intervention on the buildings concerned. Specifically, membership values char-
acterizing the status of the load-bearing structures are defined on the basis of the
deteriorationofthestructures,andanewmethodisheredevelopedthattakesinto
accountotherparametersofthestructures,andtheimpactexertedonthequalityof
thestructure,too.Themethodisbasedontheuseof‘‘realfuzzyvalues’’(R-fuzzy
sets), an extension of the concept of classic fuzzy sets that allows also the
inversion offuzzy set connectives under certain circumstances.
F. Lilik and L. T. Kóczy (‘‘The Determination of the Bitrate on Twisted Pairs
by Mamdani Inference Method’’) are concerned with the problem of how to
predict the available maximal data transfer rate on dedicated telecommunication
connections. The authors first provide a critical review of some tools and tech-
niques, which are most often used for this purpose. Then, they present a method
Preface vii
based on the use of a Mamdani-type fuzzy reasoning system. A comprehensive
computational analysis of prediction results obtained for the evaluation of the
twisted-pair-basedlocalloopsofthetelecommunicationaccessnetworksbyusing
various methods is provided and a comparison with those obtained by using that
Mamdani-type fuzzy reasoning system is shown.
B.Kalmár,A.Kalmár,K.Balázs,andL.T.Kóczy(‘‘ConstructionSiteLayout
and Building Material Distribution Planning Using Hybrid Algorithms’’) discuss
some novel method for solving the layout problem for construction site and dis-
tribution planning of building materials. The layout problem considered is dealt
withbyapplyingcostsonthemovingofconstructionmaterialsacrossthesite,and
the goal is to develop an algorithm which is specialized in solving problems of
distributing building materials, exemplified by bricks, on a site by placing their
pallets at optimal spots, for each unit built from a given material to be within an
optimal reach. The authors describe first a solution of this problem for the engi-
neering practice and interpret the slow but accurate method of the so-called
Hungarian Algorithm, and then propose a memetic algorithm which is faster but
yields almost as accuratea solution. Conclusions are drawn about the usability of
this method.
PartIIIdiscussesvariousaspectsofartificialneuralnetworkswhicharewidely
used for systems modeling, classification, control, etc.
V. Kurková (‘‘Accuracy of Surrogate Solutions of Integral Equations by
Feedforward Networks’’) is devoted to a study of an important problem of using
feed-forward neural networks for surrogate modeling offunctional relationships.
Potential applications areas range from chemistry with surrogate models of
empiricalfunctionsassigningtocompositionsofchemicalsmeasuresofqualityof
catalysers produced by reactions of these chemicals, biology with surrogate
models of empirical functions classifying structures of the RNA, economics with
surrogate models of functions assigning credit ratings to companies, etc. The
author considers from a theoretical point of view surrogate solutions of the
Fredholmintegralequations,whichplayanimportantroleinmanyareas,byusing
feed-forward neural networks. The author proves the convergence of surrogate
solutions computable by those neural networks with increasing numbers of com-
putational units to theoretically optimal solutions, and provides upper bounds on
the rates of convergence. It is shown that the results hold for a variety of com-
putational units, notably the perceptron and Gaussian radial units.
P. Šarcˇevic´ (‘‘Vehicle Classification Using Neural Networks with a Single
Magnetic Detector’’) discusses principles of operation, advantages, and disad-
vantages for different vehicle detection technologies that are meant to provide
speed monitoring, traffic counting, presence detection, headway measurement,
vehicleclassification,andweigh-in-motiondata.Theauthorproposestheideaofa
new detection and classification method for a single magnetic sensor-based sys-
tem. An important feature of the new detection algorithm and the neural network
classifier are an easy implementation in a microcontroller-based system. An
analysis of results for various benchmark problems is given.
viii Preface
Part IV contains contributions covering two important areas of intelligent data
analysis which are crucial for broadly perceived intelligent systems, knowledge
engineering, etc., that is, classification and clustering, and image processing.
P. Kulczycki, M. Charytanowicz, P. A. Kowalski, and Sz. Łukasik
(‘‘Exemplary Applications of the Complete Gradient Clustering Algorithm in
Bioinformatics,ManagementandEngineering’’)discussvariousaspectsrelatedto
the applications and prospects of the complete gradient clustering algorithm, a
classic clustering procedure developed by Fukunaga and Hostetler. The authors
present its ready-to-be-used version by providing a full set of procedures for
definingallfunctionsandvaluesoftheparameters.Moreover,theyanalyzehowa
possible change in those values influences the number of clusters and the pro-
portion between their numbers in dense and sparse areas of data elements. The
authorsshowsomepossibleusesofthesepropertiesonsomepracticalproblemsin
theareasofbioinformatics,morespecificallythecategorizationofgrainsforseed
production, management, more specifically the design of a marketing support
strategy for a mobile phone operator, and engineering, more specifically the
synthesis of a fuzzy controller.
A.T.Duong,H.T.Phan,N.D.Le,andS.T.Tran(‘‘AHierarchicalApproach
for Handwritten Digit Recognition Using Sparse Autoencoder’’) are concerned
with handwritten digit recognition, a very important problem that is very relevant
for many practical applications, yet difficult, and which still presents a consider-
able challenge from a theoretical and implementation point of view. Approaches
basedonhigherlevelfeatureslearningalgorithmsareherepromisingandpopular
givingusuallybetterresultsthanjustusingrawintensityvalueswithclassification
algorithms. On the other hand, these approaches do not take the advantage of
specific characteristics of data. Therefore, the authors propose a new method to
learn higher level features from specific characteristics of data using a sparse
autoencoder.Themainideaoftheapproachproposedistodividethehandwritten
digits into subsets corresponding to specific characteristics. The experimental
results obtained show that the proposed method yields lower error rates and time
complexity than the original approach of a sparse autoencoder. Moreover, the
results obtained indicate that the more correlated are characteristics defined, the
better higher level features can be learned.
A.TormásiandL.T.Kóczy(‘‘FuzzySingle-StrokeCharacterRecognizerwith
VariousRectangleFuzzyGrids’’)extendtheoreticalandimplementationresultson
their original FUBAR character recognition method with various fuzzy grid
parameters.Theaccuracyandefficiencyofthehandwrittensingle-strokecharacter
recognition algorithm with different sized rectangle (i.e., N 9 M) fuzzy grids are
investigated. The results obtained are then compared to other modified FUBAR
algorithms and known commercial and academic recognition methods. Possible
applications and further extensions are also discussed.
PartVcontainspapersonvariouskindsofproblems,solutions,andapplications
ontheuseofvariousparadigms,tools,andtechniquesfromthebroadlyperceived
areas of artificial and computational intelligence in robotics.
Preface ix
J. Kuti, P. Galambos, and P. Baranyi (‘‘Delay and Stiffness Dependent
Polytopic LPV Modeling of Impedance Controlled Robot Interaction’’) operate
within an important area of impedance/admittance control algorithms which are
considered as key technologies in human–robot interaction and other fields of
advanced robotics where complex physical interaction plays a crucial role. The
authors employ a tensor product (TP) model transformation-based method to
derive the delay and stiffness-dependent polytopic LPV representation of the
impedance-controlled physical interaction. The applied transformation method is
feasible with a bounded delay that is a nonlinear function of the environmental
stiffness.Therefore,theidealtransformationspaceisnonrectangularwhichmakes
ittobeimproperforthetensorproductmodeltransformation.Anovelmethodofa
dimensionless parameterization is proposed to define a rectangular grid upon
which the tensor product transformation can be applied. The resulted model form
is shown to be appropriate for the modern multiobjective LMI-based control
design techniques for impedance-controlled robot interaction.
K. Bolla, Zs. Cs. Johanyák, T. Kovács, and G. Fazekas (‘‘Local Center of
Gravity-basedGatheringAlgorithmforFatRobots’’)areconcernedwithgroupsof
the so-called fat (disc-like) mobile robots without global navigation, communi-
cationormemory,specificallytheirgatheringtheessenceofwhichistheassembly
of the scattered robots on the smallest possible area. They present a new and
effective and efficient algorithm for solving this task assuming an obstacle-free
plan, limited visibility, and synchronous operation. The key idea of the algorithm
is that in the case of each robot after detecting the visible neighboring robots, the
algorithm sets a target of the next step based on the center of gravity of the
encounteredvisiblerobots.Positiveexperienceandpromisingresultsofsimulation
for difficult problems are presented which equal or surpass those obtained by
previously published algorithms in all of the cases.
A. Ballagi, L. T. Kóczy, and C. Pozna (‘‘Intelligent Robot Cooperation with
FuzzyCommunication’’)dealwithanextremelyrelevantproblemofthedesignof
a decision-making engine of a robot which works in a collaborative team. The
challenges in this task are not only due to the complexity of the environment
uncertainty, dynamics and imprecision, but also due to the necessity of coordi-
nationoftheteamofrobotsthathastobeincludedinthedesignphase.Therobots
must be aware of other robots’ actions in order to cooperate and to successfully
achieve their common goal. In addition, decisions must be made in real-time and
under limited computational resources. The authors propose some novel algo-
rithms for action selection in ambiguous tasks where the communication oppor-
tunities amongthe robotsare very limited. Some promising simulation results are
presented.
T. T. Cocias, S. M. Grigorescu, and F. Moldoveanu (‘‘Indoor Pose Estimation
using 3D Scene Landmarks for Service Robotics’’) present a new markerless
approach for estimating the pose of a robot using only 3D visual information.
In contrast to many methods commonly used to solve this problem, the authors’
approach makes use of the 3D features to only determine a relative position
betweenthe imaged scene (forinstance,landmarks present onsite) and the robot.
