Call for Papers
The International Conference on Intelligent Systems Design and Applications (ISDA) is a major annual international conference to bring together researchers, engineers, developers and practitioners from academia and industry working in all interdisciplinary areas of computational intelligence and system engineering to share their experience, and exchange and cross-fertilize their ideas. First day will be dedicated for tutorials and workshops, which are organized by leading experts in the field.

Proceedings

ISDA’11 proceedings will be published by Conference Publishing Services. It is mandatory at least an author registers for every paper that is included in the conference proceedings. Proceedings will be made available during the conference.

Topics


A. Intelligent Systems Architectures and Applications (but not limited to):

Artificial Neural Networks
Mathematical foundations of neural networks
Architectures and algorithms
Learning theory (supervised/ unsupervised/ reinforcement learning)
Knowledge based networks
Implementation issues of neural networks
Support Vector Machines
Neural network applications
Fuzzy Systems, fuzzy logic and possibility theory
Fuzzy expert systems
Fuzzy system design using evolutionary algorithms
Fuzzy system modeling and simulation
Fuzzy systems and applications
Evolutionary Algorithms
Genetic algorithms, evolution strategies, genetic programming and evolutionary programming
Learning Classifiers
Hybrid evolutionary algorithms
Evolutionary algorithms and applications
Fusion of neural network- fuzzy systems
Fusion of fuzzy systems- evolutionary algorithms
Fusion of neural network – evolutionary algorithms
Fusion of neural network- fuzzy systems- evolutionary algorithms
Intelligent agents (architectures, environments, adaptation/ learning and knowledge management)
Bayesian networks and probabilistic reasoning
Rough sets
Statistical learning techniques
Fusion of statistical methods and soft computing techniques
CAD systems
Intelligent optimization techniques
Intelligent techniques in Bioinformatics
B. Intelligent Image and Signal Processing (but not limited to):

Design and implementation of intelligent signal processing systems
Image, video and multidimensional signal processing
Multimedia signal processing
Speech processing
Features and classification
Texture analysis
Document analysis
Stereoscopic vision
Shape processing
Object recognition
Image and video retrieval
Image and video compression
C. Intelligent Internet Modeling (but not limited to):

Web intelligence
Search engines
Information retrieval (web mining)
Database querying
Ontology
XML mining
Intelligent networking between Web Sites
Network security, intrusion detection
Information aggregation and fusion
Interaction with intelligent agents
Intelligent agents and interfaces for personalization and adaptivity
Intelligent tutoring systems on the WWW
Adaptive hypermedia systems
Agents for digital cities, virtual communities and agent societies
D. Intelligent Data mining (but not limited to):

Discovering patterns in continuous data
Uncertainty management for data mining
Clustering algorithms and applications
Classification trees
Mining time series
Mining in a Mobile Environment
Statistical Considerations in Learning
XML Mining
Text Mining
Distributed Data Mining
E. Intelligent Business Systems (but not limited to):

e-learning, e-commerce, e-business, e-finance
Risk management
Derivatives pricing
Portfolio management and asset allocation
Stock market, forex market analysis, dynamics; simulation
Hedging, trading & arbitrage strategies
Financial modeling
Computational economics
Intelligent management
Multicriteria decision making
F. Intelligent Control and Automation (but not limited to):

Mathematical modeling and analysis of complex systems
Soft computing/computational intelligence in control systems
Knowledge based control systems
Adaptive control systems
Control applications in robotics, manufacturing, process control, industrial systems, automotive, vehicular systems, spacecraft and so on
G. Intelligent Agents (but not limited to):

Adaptation and learning
Agent architectures and communication languages
Communication, collaboration, and interaction of humans and agents
Conversational agents
Coordinating multiple agents
Designing agent systems – methodologies & software engineering
Evolution of agents
Knowledge acquisition and management
models of emotion, motivation, or personality
multi-agent communication, coordination, and collaboration
H. Intelligent Knowledge Management (but not limited to):

Application of knowledge representation techniques to semantic modeling
Development and management of heterogeneous knowledge bases
Automatic acquisition of data and knowledge bases (especially raw text)
Performance evaluation
Parallel database systems
Data and knowledge sharing
Cooperation in heterogeneous systems
Domain modeling and ontology-building
Concurrent engineering and computer integrated manufacturing
Digital Libraries
Multimedia Databases.
I. Innovative Information Security

J. Innovative Networking and Communication Techniques

K. Web Intelligence