AIM
Measuring has gone from simple one variable measurement machines that produce data to integrated measurement systems that produce user oriented
information. These systems acquire and intelligently process and integrate multiple data measurements from multiple sources and, taking into
account and adapting to the context, produce usable information which, by intelligently communicating and interacting with other systems and
repositories, seamlessly contribute to some user perceived functionality. Obviously, to achieve this end, Computational Intelligence based
techniques and their application to measurement systems are a very important avenue of research.
This task force promotes all aspects related to the theory and the development of new intelligent measurement techniques and, in particular,
of novel developments and applications of computational intelligence based approaches to this field.
The topics include but are not limited to: intelligent measurement systems; accuracy and precision of neural and fuzzy components; intelligent
sensor fusion; intelligent monitoring and control systems; neural, evolutionary and fuzzy technologies for identification, prediction, and control
of complex dynamic systems; evolutionary monitoring and control; uncertainty estimation in complex measuring systems; neural, evolutionary and fuzzy
signal/image processing for industrial and environmental applications; hybrid systems; fuzzy evolutionary and neural components for embedded systems;
hardware implementation of neural, evolutionary and fuzzy systems for measurements; neural, fuzzy and genetic/evolutionary algorithms for system
optimization and calibration; neural and fuzzy diagnosis of components and systems; reliability, fault tolerance and testing of fuzzy and neural
components; neural and fuzzy techniques for quality measurement.