The International Conference on Intelligent Systems Design and Applications (ISDA) is a major annual international conference bringing 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. The first day will include tutorials and workshops, organized by leading experts in the field.

Proceedings are expected to be published by Springer Verlag in one of the series. Details will be available soon.

Papers maximum length is 10 pages.
- Papers must be formatted according to Springer format (Latex/word).

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

• Cognitive networking
• Protocol design, including cross-layer and opportunistic approaches.
• Delay tolerant networks
• Mobility management and seamless internetworking
• Key management and trust establishment in wireless networks
• MAC-layer design for ad hoc networks and WSNs
• Networked smartphone applications
• Opportunistic networking
• Power-aware architectures, algorithms, and protocols design
• QoS and Resource management
• Reliability, resiliency and fault tolerance techniques
• Resource management and wireless QoS provisioning
• Routing protocols, including unicast, multicast, broadcast, geocast
• Mobile computing and networking Mobility management
• Security and privacy issues in ad hoc networks
• -Smart grid
• -Vehicular networks and protocols
• -Coexistence of heterogeneous wireless networks.
• -Secure Mobile Agents and Mobile Code

K. Web Intelligence

L. Intelligent Software Engineering

• Autonomic and self-managed software  Requirements engineering
• Software evolution
• Automated software Testing and analysis
• Knowledge-based software engineering
• Software reuse
• Intelligent Software maintenance
• Service-oriented architectures
• Reengineering and reverse engineering
• Program comprehension and visualization
• Model-driven software engineering
• Intelligent Software design techniques
• Distributed, web-based and internet-scale SE
• Processes and workflow
• Software economics and metrics
• Patterns and frameworks 

Please follow the link for electronic submission: https://easychair.org/conferences/?conf=isda2021