Sunday 26 February 2012

engineering artificial application


A journal of IFAC, the International Federation of Automatic Control

Artificial Intelligence (AI) techniques are now being used by the practising engineer to solve a whole range of hitherto intractable problems. This journal provides an international forum for rapid publication of work describing the practical application of AI methods in all branches of engineering.
Focal points of the journal are:
• Applications of real-time intelligent automation, and their associated supporting methodologies and techniques.
• Architectures, algorithms and techniques for distributed AI systems.
• Decision-support systems.
• Aspects of reasoning: abductive, case-based, model-based, non-monotonic, incomplete, progressive and approximate reasoning.
• Other theoretical aspects, e.g. chaos theory and fractals.
• Knowledge processing, e.g. a priori and self-learning, knowledge elicitation and acquisition, knowledge representation, knowledge compaction, knowledge bases, expert systems, neural networks, fuzzy systems and genetic algorithms.
• Perception, e.g. image and signal processing, pattern recognition, vision systems, tactile systems, and speech recognition and synthesis.
• Aspects of software engineering, e.g. intelligent programming environments, the testing verification and validation of AI-based software, software and hardware architectures for the real-time use of AI techniques, safety and reliability.
• Fault detection, fault analysis and diagnostics.
• Industrial experiences in the application of the above techniques, e.g. case studies or bench-marking exercises.
Engineering Applications of Artificial Intelligence publishes
• Survey papers/tutorials.
• Contributed papers—detailed expositions of new research or applications.
• Brief papers—short discussions of new technical concepts or developments, or new applications of existing techniques.
• Case studies or software reviews—evaluative and descriptive reviews of existing available AI software systems, discussing the experience gained and lessons learnt from using or developing AI systems for engineering applications.IFAC EAAI Forum—problems arising from engineering practice, needing to be solved by somebody; solutions to problems discussed in this forum or elsewhere; critiques of a position or claim found in the literature.

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