Download Artificial Intelligence Applications

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The International Association of Science
and Technology for Development
Conference Program
February 11 – 13, 2008
Innsbruck, Austria
Artificial
Intelligence
AND
Applications
MACHINE LEARNING
as part of the 26th IASTED International Multi-Conference on APPLIED INFORMATICS
SPONSORS
The International Association of Science and Technology
for Development (IASTED)
• Technical Committee on Artificial Intelligence and
Expert Systems
World Modelling and Simulation Forum (WMSF)
LOCATION
Congress Innsbruck
Postfach 533, Rennweg 3
A-6021 Innsbruck, Austria
Tel: +43 512-59 360
Fax: +43 512-59 367
Artificial Intelligence and Applications
~AIA 2008~
SPONSORS
The International Association of Science and Technology for Development
(IASTED)
Technical Committee on Artificial Intelligence and Expert Systems
World Modelling and Simulation Forum (WMSF)
CONFERENCE CHAIR
Dr. Alex Gammerman – University of London, UK
PROGRAM COMMITTEE CO-CHAIRS
Prof. Xiaohui Liu – Brunel University, UK
Prof. Alexey Chervonenkis – Russian Academy of Science, Russia and
Computer Learning Research Centre, University of London, UK
KEYNOTE SPEAKER
Prof. Vladimir Vovk – University of London, UK
TUTORIAL SPEAKER
Dr. Boris Kovalerchuk – Imaging Lab at Central Washington University,
USA
PLEASE NOTE
Paper presentations are 15 minutes in length with an additional 5
minutes for questions.
Report to your Session Chair 15 minutes before the session is
scheduled to begin.
Presentations should be loaded onto the presentation laptop in the
appropriate room prior to your session.
End times of sessions vary depending on the number of papers
scheduled.
1
INTERNATIONAL PROGRAM COMMITTEE
M.M. Abd Allah – Minia University,
Egypt
G. Agre – Bulgarian Academy of
Sciences, Bulgaria
P. Aguiar – Unesp - Sao Paulo State
University, Brazil
J. Ahmad – Iqra University, Pakistan
S. Aitken – University of Edinburgh,
UK
M. Al-Tarawneh – University of
Newcastle Upon Tyne, UK
G. Angelova – Bulgarian Academy of
Sciences, Bulgaria
K. Araki – Hokkaido University,
Japan
A. Ayesh – De Montfort University,
UK
J.F. Baldwin – University of Bristol,
UK
N. Belacel – National Research
Council Canada, Canada
G. Beydoun – University of New
South Wales, Australia
M. bin Khalid – Universiti Teknologi
Malaysia, Malaysia
A. Bouzouane – University of Québec
at Chicoutimi, Canada
O. Castillo – Tijuana Institute of
Technology, Mexico
A.M.K. Cheng – University of
Houston-University Park, USA
S. Choi – Pohang University of
Science & Technology, Korea
H. Coelho – University of Lisbon,
Portugal
V. Colla – Superior School of
Sant'Anna, Italy
B. De Baets – Ghent University,
Belgium
A. Dourado – University of Coimbra,
Portugal
R.-J. Dzeng – National Chiao-Tung
University, Taiwan
N. Etani – Osaka University, Japan
R. Faglia – State University of Brescia,
Italy
J. Fan – University of Wollongong,
Australia
K. Fischer – DFKI GmbH, Germany
A.M. Florea – University "Politehnica"
of Bucharest, Romania
L. Garza Castañón – ITESM Campus
Monterrey, Mexico
M. Gaspari – University of Bologna,
Italy
C. Giraud-Carrier – Brigham Young
University, USA
F.C.A. Groen – University of
Amsterdam, The Netherlands
F. Gurgen – Bogazici University,
Turkey
K. Harbusch – University of KoblenzLandau, Germany
Y.-P. Huang – Tatung University,
Taiwan
C.-C. Hung – Southern Polytechnic
State University, USA
C.R. Huyck – Middlesex University,
UK
R. Kamimura – Tokai University,
Japan
J. Kamruzzaman – Monash
University, Australia
S. Karamouzis – Texas A&M
University - Texarkana, USA
J. Kim – Dongguk University, Korea
S.-J. Kim – Kangnung National
University, Korea
M. Klusch – German Research Center
for Artificial Intelligence, Germany
J. Koehler – IBM, Switzerland
E. Konrad – Technical University of
Berlin, Germany
B. Kovalerchuk – Central Washington
University, USA
D. Kumlander – Tallinn University of
Technology, Estonia
2
V. Lakshmikantha – Bangalore
Institute of Technology, India
H. Langseth – Norwegian University
of Science and Technology, Norway
K.C. Lee – Sungkyunkwan
University, Korea
C. Li – Middle Tennessee State
University, USA
W.-M. Lippe – University of Münster,
Germany
B. Ludwig – University of ErlangenNürnberg, Germany
L. Magdalena – European Centre for
Soft Computing, Spain
A. Martín – University of Sevilla,
Spain
Y. Matsuyama – Waseda University,
Japan
A. Milani – University of Perugia,
Italy
A. Milella – Italian National Research
Council, Italy
I. Mitchell – Middlesex University,
UK
P.A. Mitkas – Aristotle University of
Thessaloniki, Greece
B. Mobasher – DePaul University,
USA
D.N. Monekosso – Kingston
University, UK
R. Morales-Menéndez – ITESM
Campus Monterrey, Mexico
E. Mosqueira Rey – University of
Coruña, Spain
M. Mostafa – Minia University, Egypt
A. Nijholt – University of Twente,
The Netherlands
F. Ogwu – University of Botswana,
Botswana
M. Ojeda-Aciego – University of
Malaga, Spain
M. Oprea – University of Ploiesti,
Romania
D. Portnoy – George Washington
University, USA
P. Remagnino – Kingston University,
UK
F. Ren – University of Tokushima,
Japan
R.R. Rosa – National Institute for
Space Research, Brazil
J.M. Rossiter – University of Bristol,
UK
S. Rubin – Space and Naval Warfare
Systems Center, USA
T. Sabol – Technical University of
Košice, Slovakia
R. Salomon – University of Rostock,
Germany
J. Sauer – University of Oldenburg,
Germany
E. Schikuta – University of Vienna,
Austria
L.B. Sheremetov – Mexican
Petroleum Institute, Mexico
M. Sigmund – Brno University of
Technology, Czech Republic
I. Skrypnyk – University of
Jyvaskyla, Finland
J.A. Starzyk – Ohio University, USA
H. Stoyan – University of ErlanganNuremberg, Germany
M. Sulzmann – National University
of Singapore, Singapore
J. Sun – Nova Southeastern
University, USA
R. Sundararajan – GE India
Technology Centre Pvt. Ltd., India
R. Tadeusiewicz – AGH University of
Science and Technology, Poland
C.M. Teng – Institute for Human and
Machine Cognition, USA
F.-C. Tien – National Taipei
University of Technology, Taiwan
P. Tino – University of Birmingham,
UK
P. Torasso – University of Torino,
Italy
G. Trajkovski – South University,
USA
D.P. Tsakiris – Foundation for
Research & Technology-Hellas,
Greece
3
Y. Tzitzikas – University of Crete,
Greece
Z.A. Vale – Superior Institute of
Engineering of Porto, Portugal
N.K. Valverde – National
Autonomous University of Mexico,
Mexico
S. Vranes – Mihailo Pupin Institute,
Serbia
P. Wang – Northeastern University,
USA
R.R. Yager – Iona College, USA
J.F. Zelasco – University of Buenos
Aires, Argentina
M. Zhang – Christopher Newport
University, USA
C. Zhou – Singapore Polytechnic,
Singapore
4
PROGRAM OVERVIEW
Monday, February 11, 2008
14:00
AIA Tutorial Presentation –
"Visual Analytics and Machine
Learning"
(Freiburg Room)
07:00 –
08:00
Registration
(3rd Floor Foyer)
08:00 –
08:30
Welcome Address
(Freiburg Room)
15:00 –
15:30
Coffee Break
(Diesner Foyer)
08:30 –
10:30
Session 1 - Pattern Recognition
(Freiburg Room)
15:30
Tutorial Presentation Continued
Wednesday, February 13, 2008
Session 2 - Machine Learning
(New Orleans Room)
10:30 11:00
Coffee Break
(Diesner Foyer)
11:00 12:00
Keynote Address – “"Machine
Learning Without Stochastic
Assumptions"
(Freiburg Room)
14:00 15:00
Session 3 – Artificial Intelligence
and Applications I
(Freiburg Room)
Session 4 – Intelligent Data
Analysis
(Grenoble Room)
Session 5 – Genetic Algorithms
(New Orleans Room)
15:00 –
15:30
Coffee Break
(Diesner Foyer)
15:30
Sessions 3, 4, and 5 Continued
Tuesday, February 12, 2008
08:30
Session 6 – Artificial Intelligence
and Applications II
(Freiburg Room)
10:00 –
10:30
Coffee Break
(Social Diesner Foyer)
10:30
Session 6 Continued
5
08:30
Session 7 – Data Mining
(Freiburg Room)
10:30 –
11:00
Coffee Break
(Diesner Foyer)
11:00
Session 7 Continued
14:00 15:00
Session 8 - Neural Networks
(Freiburg Room)
15:00 –
15:30
Coffee Break
(Diesner Foyer)
15:30
Session 8 Continued
19:00
Dinner Banquet
(Dogana Hall)
MONDAY, FEBRUARY 11,
2008
595-109
A Problem in Data Variability on
Speaker Identification System
using Hidden Markov Model
A. Buono and
B. Kusumoputro (Indonesia)
07:00 – 08:00 REGISTRATION
IASTED Staff: J. Langer (Canada)
Location: 3rd Floor Foyer
08:30 – 10:30 - SESSION 2 –
MACHINE LEARNING
Chairs: H. Papadopoulos (Cyprus)
and A. Takeda (Japan)
Location: New Orleans Room
08:00 – 08:30 WELCOME
ADDRESS
Presenter: Dr. A. Gammerman (UK)
Location: Freiburg Room
595-022
A Comparative Study of Decision
Tree Approaches to Multi-Class
Support Vector Machines
P. Krauthausen and
A. Laubenheimer (Germany)
08:30 – 10:30 - SESSION 1 –
PATTERN RECONGNITION
Chair: D. Malouche (Tunisia)
Location: Freiburg Room
595-025
Estimating High Dimensional
Faithful Gaussian Graphical
Models by Low-Order
Conditioning
D. Malouche (Tunisia) and
S. Sevestre-Ghalila (France)
595-048
An Improved Support Vector
Machine With Soft DecisionMaking Boundary
B. Li, J. Hu, and K. Hirasawa (Japan)
595-042
Text Categorization of
Commercial Web Pages
E. Binaghi, M. Carullo, I. Gallo, and
M. Madaio (Italy)
595-053
A Modified Algorithm for
Nonconvex Support Vector
Classification
A. Takeda (Japan)
595-098
Analysis of the Neural Extended
Kalman Filter for Target Tracking
using Different Neural Network
Functions
S.C. Stubberud and
K.A. Kramer (USA)
595-054
A Novel Hierarchical Bayesian
HMM for Multi-Dimensional
Discrete Data
S. Motoi, Y. Nakada, T. Misu,
T. Matsumoto, and N. Yagi (Japan)
6
Markov
assumption
of
reinforcement learning. In this
talk I will review the area of
competitive on-line prediction,
which
avoids
making
any
stochastic assumptions but still
provides prediction algorithms
with
surprisingly
strong
performance guarantees. Instead
of assuming a statistical model
(such as iid or Markov) the theory
of competitive on-line prediction
uses a "soft model", which is a
benchmark class of prediction
strategies; the goal is to design
prediction algorithms competitive
with the best prediction strategies
in the benchmark class. I will
review
both
the
known
techniques
for
designing
competitive on-line prediction
algorithms (such as following the
perturbed leader, Bayes-type
aggregation, gradient descent,
defensive forecasting) and the
kinds of prediction tasks that can
be tackled with those techniques
(such as prediction with expert
advice, large benchmark classes,
limited feedback).
595-060
One-Class Classification Methods
via Automatic Counter-Example
Generation
A. Bánhalmi (Hungary)
595-177
Normalized Nonconformity
Measures for Regression
Conformal Prediction
H. Papadopoulos (Cyprus),
A. Gammerman, and V. Vovk (UK)
595-061
Impacts of Team Size on Role
Learning in Multiagent Systems
M. Saito (Japan)
10:30 – 11:00 COFFEE BREAK
Location: Diesner Foyer
11:00 – KEYNOTE ADDRESS –
“MACHINE LEARNING
WITHOUT STOCHASTIC
ASSUMPTIONS”
Presenter: Prof. Vladimir Vovk
Location: Freiburg Room
The
standard
theoretical
approaches to machine learning
depend on more or less restrictive
stochastic assumptions about the
data
generating
mechanism.
Prime examples are the iid
assumption of statistical learning
theory (the data items are
assumed
to
be
drawn
independently from the same
probability distribution) and the
Vladimir Vovk is Professor of
Computer Science at Royal
Holloway, University of London.
His research interests include
machine learning; predictive and
Kolmogorov
complexity,
randomness, and information; the
foundations of probability and
statistics. He has published
numerous research papers in
7
595-100
An Intelligent Hybrid Decision
Support Algorithm for Cutting
Tool Replacement in High
Performance Machining
Operations
J.V. Abellan, F. Romero, H.R. Siller,
C. Vila (Spain), and
R. Morales-Menendez (Mexico)
these fields and two books:
"Probability and finance: It's only
a game" (with Glenn Shafer,
Wiley, New York, 2001; Japanese
translation:
Iwanami
Shoten,
Tokyo, 2006) and "Algorithmic
learning in a random world" (with
Alex Gammerman and Glenn
Shafer, Springer, New York, 2005).
He is Fellow of the Royal
Statistical Society and Chartered
Fellow of the British Computer
Society.
595-128
Neural Networks Solutions of
Thermistor Problem Tuned by
Genetic Algorithms and Gradient
Descent Method
C. Wongsathan and
N. Suyaroj (Thailand)
14:00 – SESSION 3 –
ARTIFICIAL INTELLIGENCE
AND APPLICATIONS I
Chairs: D. Dunea (Romania)
and P. Caballero-Gil (Spain)
Location: Freiburg Room
595-133
A Cellular Automata based
Method for Predicting Binary
Sequences
P. Caballero-Gil and
A. Fúster-Sabater (Spain)
595-064
Real-Time Systems: Incomplete
Solution Approach for the
Maximum-Weighted Clique
Problem
D. Kumlander (Estonia)
595-138
Novel Labeling Strategies for
Hierarchical Representation of
Multidimensional Data Analysis
Results
J.-C. Lamirel, A.P. Ta, and
M. Attik (France)
595-087
Statistical Investigation on the
Day-of-the-Week Effect in
Emerging Stock Markets
V. Sakalauskas and
D. Kriksciuniene (Lithuania)
595-140
Classification of Burn Degrees in
Grinding by Neural Nets
M.M. Spadotto, P.R. Aguiar,
C.C.P. Souza, E.C. Bianchi, and
A.N. de Souza (Brazil)
8
14:00 – SESSION 4 –
INTELLIGENT DATA
ANALYSIS
Chair: B. Bakker (The Netherlands)
Location: Grenoble Room
595-143
A Comparison of an SOM and
ALEV for Data Reduction
Purposes in Transport Telematics
W. Toplak (Austria)
595-049
Improved Particle Swarm
Optimization Algorithm based on
Statistical Laws and Dynamic
Learning Factors
X.-j. Bi, G.-a. Liu, and J. Li (PRC)
595-156
An Application of Artificial
Neural Networks in
Environmental Pollution
Forecasting
E. Lungu, M. Oprea, and
D. Dunea (Romania)
595-112
Optimizing Multiple
Pronunciation Dictionary based
on a Confusability Measure for
Non-Native Speech Recognition
M. Kim, Y.R. Oh, and
H.K. Kim (Korea)
595-065
Language Model Adaptation for
Medical Dictations by Automatic
Phonetics-Driven Transcript
Reconstruction
S. Petrik and F. Pernkopf (Austria)
595-162
Using Bayesian Belief Networks
for Credit Card Fraud Detection
L.E. Mukhanov (Russia)
595-158
Text Dependent Speaker
Verification System using
Discriminative Weighting Method
and Artificial Neural Networks
M.Z. Ibrahim, M. Khalid, and
R. Yusof (Malaysia)
595-163
Switching between Different State
Representations in Reinforcement
Learning
H. van Seijen, B. Bakker, and
L. Kester (The Netherlands)
595-168
Feature-based Cluster Validation
for High-Dimensional Data
R. Kassab and J.-C. Lamirel (France)
9
595-062
Iterated Mutation in an
Evolutionary Algorithm for
Sudoku
D.O. Hamnes and
B.A. Julstrom (USA)
595-120
Accurate Tool based on JPEG
Image Compression for Arabic
Handwritten Character Shape
Recognition
A.A. Aburas and
S.A. Rehiel (Malaysia)
595-097
Dependence Modeling Rule
Mining using Multi-Objective
Genetic Algorithms
G.M.Barbosa de Oliveira,
M.C.S. Takiguti,
L. Gustavo Almeida Martins (Brazil)
595-058
Weighted Class based Hybrid
Algorithm for Top-N
Recommender Systems
S. Ray and A. Mahanti (India)
14:00 – SESSION 5 – GENETIC
ALGORITHMS
Chairs: H.H. Ali (USA) and
I. Xydas (France)
Location: New Orleans Room
595-154
GA Search Method for Multiple
Evacuation Routes using the
Information of Hazard Map
M. Xie and Y. Kinoshita (Japan)
595-032
Using an Evolutionary Neural
Network for Web Intrusion
Detection
I. Xydas, G. Miaoulis (Greece),
P.-F. Bonnefoi, D. Plemenos, and
D. Ghazanfarpour (France)
595-159
Designing Particle Swarm
Optimization - Performance
Comparison of Two Temporally
Cumulative Fitness Functions in
EPSO
H. Zhang and M. Ishikawa (Japan)
595-056
Consideration of the Efficiency of
Layered Server-Client Topology
for Parallel Distributed GA on
Large Problem
K. Kojima, M. Ishigame, and
S. Makino (Japan)
595-802
A New Genetic Algorithm for
Resource Constrained Project
Scheduling
Y. Mohsenin and H.H. Ali (USA)
15:00 – 15:30 COFFEE BREAK
Location: Diesner Foyer
15:30 SESSIONS 3, 4, and 5
CONTINUED
10
TUESDAY,
FEBRUARY 12, 2008
595-147
Mining Balanced Patterns in Web
Access Data
E.H. de Graaf, J.N. Kok, and
W.A. Kosters (The Netherlands)
08:30 – SESSION 6 ARTIFICIAL INTELLIGENCE
AND APPLICATIONS II
Chair: R. Andonie (USA)
Location: Freiburg Room
595-169
Ontological Support for
Association Rule Mining
A. Bellandi, B. Furletti, V. Grossi,
and A. Romei (Italy)
595-021
A Refined Multisite Fungal
Protein Localizer
M. Nathan and G. Butler (Canada)
595-171
A Model Searching Method based
on Marginal Model Structures
S.-H. Kim and S. Lee (Korea)
595-190
Oncogenes Classification
Measured by Microarray using
Genetic Algorithms
L. Rodrigues do Amaral,
F.S. Espindola, G. Sadoyama, and
G.M. Barbosa de Oliveira (Brazil)
595-028
A Method of Positioning
Unknown Words in an Existing
Thesaurus based on an
Association Mechanism
S. Tsuchiya, N. Okumura,
H. Watabe, T. Kawaoka (Japan),
F. Ren (Japan, PRC), and
S. Kuroiwa (Japan)
595-071
Asynchronous, Adaptive BCI
using Movement Imagination
Training and Rest-State Inference
S. Fazli, M. Danóczy, M. Kawanabe,
and F. Popescu (Germany)
595-043
Fast Object Tracking through the
Use of Artificial Neural Networks
D.T. Smith (USA)
595-081
Fuzzy ARTMAP with Feature
Weighting
R. Andonie (USA), A. Cataron, and
L.M. Sasu (Romania)
595-113
Designing a Discrepancy
Supporting Perception Module of
an Agent for Multimedia
Entertainment Applications
S.-J. Ji, J.-W. Kwon, and
J.-H. Park (Korea)
595-095
A Multi-Level Abstraction Model
for Competitive Learning Neural
Networks
R. Kassab and J.-C. Lamirel (France)
11
on machine learning, data mining,
and reasoning has become feasible
for a wide range of problems and
large data sets. Visual knowledge
discovery has been conducted
successfully for millennia. The
Pythagorean Theorem was proven
using visual means more than
2000 years ago. One of its ancient
visual proofs had only one word
attached to it "See". Diopahntus
invented iconic reasoning in
mathematics. However, visual
analytics
methods
such
as
"parallel coordinates" do not
address the specific needs for
processing multidimensional data
that are highly overlapped in the
visual space. This is especially
challenging
in
medical
applications tracked with binary
symptoms and in complex
dynamic optimization. Blending
machine learning with visual
analytics is a promising approach
in this area. This tutorial shows
how structural relations between
n-dimensional
objects
are
represented in 2-D and 3-D
instead of traditional attempts (in
parallel coordinates and other
methods) to visualize each
attribute value of n-dimensional
objects.
595-105
Extensions of the k Nearest
Neighbour Methods for
Classification Problems
Z. Voulgaris and
G.D. Magoulas (UK)
595-142
Multi-Objective Stochastic Design
of Robust PI Controllers for
Systems with Probabilistic
Uncertainty using Genetic
Algorithm
N. Nariman-zadeh, A. Hajiloo, and
A. Jamali (Iran)
10:00 – 10:30 COFFEE BREAK
Location: Diesner Foyer
10:30 SESSION 6 CONTINUED
14:00 – TUTORIAL
PRESENTATION – “"VISUAL
ANALYTICS AND MACHINE
LEARNING"
Presenter: B. Kovalerchuck (USA)
Location: Freiburg Room
Visual analytics is an emerging
research area. Visual analytics has
several important advantages
such as direct appeal to user
understanding, and ability to
show patterns that are extremely
difficult to express and discover
purely analytically. Currently,
with proliferation of visual
techniques
and
hardware
capabilities, visual analytics based
Dr. Boris Kovalerchuk is a
professor of Computer Science
and director of Imaging Lab at
Central Washington University,
USA. He is a co-author of two
books
"Visual
and
Spatial
12
analysis: Advances in Visual Data
Mining, Analysis, and Problem
Solving", Springer, 2005" and
"Data
Mining
in
Finance"
(Kluwer, 2000) as well as over 100
research papers. He is a recipient
of several major US federal
research grants in the area of this
tutorial. Dr. Kovalerchuk chaired
IASTED
Conference
on
Computational Intelligence (San
Francisco, 2006) and delivered
several tutorials and invited talks
at International Conferences.
595-026
Multivariate Similarity-based
Conformity Measure (MSCM): An
Outlier Detection Measure for
Data Mining Applications
S.A. Badawy (Canada), A. Elragal,
and M. Gabr (Egypt)
15:00 – 15:30 COFFEE BREAK
Location: Diesner Foyer
595-037
Frequent Pattern Mining from
High-Dimensional Data using
Record Space Search
K. Mori and R. Orihara (Japan)
595-031
Generating Method of
Appropriate Greeting Sentences
for Conversation based on the
Situation
E. Yoshimura, S. Tsuchiya,
H. Watabe, and T. Kawaoka (Japan)
15:30 - TUTORIAL
PRESENTATION CONTINUED
595-051
Research Paper Title Evaluation
for Reaching New Audiences
Y. Nishihara, W. Sunayama, and
M. Yachida (Japan)
WEDNESDAY,
FEBRUARY 13, 2008
0:830 – SESSION 7 – DATA
MINING
Chairs: A. Elragal (Egypt) and
C. Malagón (Spain)
Location: Freiburg Room
595-066
Knowledge Discovery by Rough
Sets Mathematical Flow Graphs
and its Extension
D. Chitchareon and
P. Pattaraintakorn (Thailand)
595-052
Categorising Insurance Policy
Data with MLPs and SOMs
A. Shah and C. Huyck (UK)
595-084
Construction of a Knowledge
System which Includes
Association and Sensibility
Information
S. Ikemasu, T. Kanamori, Y. Kato,
and J. Takeno (Japan)
13
595-141
Game Engine Design using Data
Mining
K.S.Y. Chiu and K.C.C. Chan (PRC)
14:00 – SESSION 8 – NEURAL
NETWORKS
Chair: R. Kamimura (Japan)
Location: Freiburg Room
595-091
Data Mining Methods for
Malware Detection using
Instruction Sequences
M. Siddiqui, M.C. Wang, and
J. Lee (USA)
595-006
Fuzzy Automata and Neural
Associative Memories Compatible
with Principles of Quantum
Computation
G.G. Rigatos (Greece)
595-110
Learning Parameters of a Genetic
Algorithm Applied to Signal
Classification
A.J. Cantos and M. Santos (Spain)
595-045
Chaotic Neural Network with
Time Delay Term for Sequential
Patterns
K. Hirozawa and Y. Osana (Japan)
595-046
Improved Chaotic Associative
Memory for Successive Learning
T. Ikeya, T. Sazuka, A. Hagiwara,
and Y. Osana (Japan)
595-080
Pixel-by-Pixel Base
Representation in Image
Classification from Cherenkov
Telescopes
C. Malagón, J.A. Barrio, and
D. Nieto (Spain)
595-047
Kohonen Feature Map Associative
Memory with Refractoriness
based on Area Representation
T. Imabayashi and Y. Osana (Japan)
10:30 – 11:00 COFFEE BREAK
Location: Diesner Foyer
595-149
An Information-Theoretic
Approach to Feature Extraction in
Competitive Learning
R. Kamimura, T. Taniguchi, and
R. Kitajima (Japan)
11:00 SESSION 7 CONTINUED
595-150
Free Energy-based Competititve
Learning and Minimum
Information Production Learning
R. Kamimura (Japan)
14
*******************************
IASTED would like to thank you
for attending AIA 2008. Your
participation helped make this
international event a success, and
we look forward to seeing you at
upcoming IASTED events.
***************************************
595-172
Vehicle Integrated Stability
Control using Hybrid Fuzzy CMean Clustering-Adaptive Back
Propagation Scheme
M. Harly, I.N. Sutantra, and
H.P. Mauridhi (Indonesia)
595-184
Free Energy-based Competititve
Learning for Self-Organizing
Maps
R. Kamimura (Japan)
595-800
Multilayer Feed Forward Neural
Networks for Olive Trees
Identification
G.A. Azim (Saudi Arabia) and
M.K. Sousow (Syria)
15:00 – 15:30 COFFEE BREAK
Location: Diesner Foyer
15:30 SESSION 8 CONTINUED
19:30 – 23:00 DINNER
BANQUET
Location: Dogana Hall
15