International Journal of Knowledge-Based and Intelligent Engineering Systems
The aim of research into Knowledge-Based and Intelligent Engineering is to develop systems that replicate the analytical, problem solving and learning capabilities of the brain. These systems bring the benefits of knowledge and intelligence to the solution of complex problems. This international journal provides a forum for publishing the results of recent research into the applications of intelligent systems, and also the tools and techniques necessary for them. Authors are invited to submit original unpublished work that is not currently under consideration for publication elsewhere, on the following topics:
Generic Intelligent Tools, Techniques and Algorithms:
Knowledge-Based Systems, Expert Systems, Neural Networks, Fuzzy Techniques and Systems, Genetic Algorithms and Evolutionary Computing, Hybrid Intelligent Systems, Intelligent Agents and Multi-Agent Systems, Knowledge Discovery and Data Mining, Machine Learning, Cognitive Modelling, Knowledge Representation and Management, Planning, Spatial & Temporal Reasoning, Knowledge Acquisition.
Applications using Intelligent Techniques:
Industrial Control and Monitoring, Fault Diagnosis, Robotics, Image Processing, Machine & Computer Vision, Medical & Diagnostic Systems, Financial & Stock Market Monitoring and Prediction, Speech Processing and Synthesis, Natural Language Processing, Environmental Monitoring, Power Electronics & Drives, High Voltage Systems, Engine Control and Vehicle Applications, Intelligent Signal Processing and Wavelets, Intelligent Customer Support systems.
Emerging Intelligent Technologies:
Artificial Intelligence and the Internet, Information Agents on the Internet, Intelligent E-commerce/E-business and E-learning, Intelligent Information Retrieval, Intelligent Web Mining & Applications, Intelligent User Interfaces, Bioinformatics using Intelligent & Machine Learning Techniques, Intelligent Tutoring Systems, Virtual Reality & Multi-Media Intelligent Information Systems, Artificial Life, Biologically Inspired Computation.
Prof. B. Gabrys
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