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Guide Computational Intelligence: Methods and Techniques

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Condition Monitoring Using Computational Intelligence Methods

Temporal based Neural Networks can be also integrated in complex computer vision systems in order to identify some hard and dynamic patterns occurring in real environment such as human activities and behaviours. Getting heterogeneous devices and services to communicate and understand each other is problematic within pervasive computing environments.

An active area of research is through the use of light-weight service composition middleware's built to allow communication and coordination to allow the re-configuration and identification of services. This can be coupled with domain specific languages DSL that enable services to be easily created and to hide the complexity of the environment.

About the course

In past work, DSL's were used to program these pervasive environments, while more recently, DSL's are being investigated in the control of power consumption within smart homes. With a large number of services available within a pervasive environment, trust becomes an issue and work in to rule based provenance trust systems are currently being investigated. The CIA Research Group has expertise in analysis and use of methods from the field of computational intelligence, such as artificial neural networks, evolutionary algorithms and swarm intelligence to solve real-world problems from science and engineering.

The research group has also expertise in smart environments, ambient assistive technologies, pervasive computing, location aware systems, intelligent modelling, control and robotics.

The group also benefits from the Centre for Innovation and Technology Exploitation CITE , which helps regional companies explore the impact of using emerging technologies within their business environment. Professor Ahmad Lotfi Group leader. Selected publications from this group are listed below. For full list of publications please use Institutional Repository IRep.

Find out more here OK. Collaboration People Publications Projects. Overview Members of the research team will continue to apply computationally intelligent methods and techniques to real-world applications that can make a difference to lives and society.

Computational Intelligence and Applications Research Group (CIA) | Nottingham Trent University

Research activities within the CIA group addresses a number of problem domains and real-world applications and can be sub-categorised into the following themes: Ambient Intelligence AmI In environments based on ambient intelligence, it is intended to investigate prediction techniques using computational intelligence methods where the behaviours of users are predicted.

Text mining and Information Extraction IE The advance of computer technologies especially the internet and WWW has led to an explosion of digital data, a large proportion of which is text. Computational Optimisation Focuses on the development and application of heuristic search and optimisation methods.

Biologically-inspired Speaker Verification Voice biometrics is one of the least developed of all the biometric technologies. Temporal Issues in designing Fuzzy Systems During past years, fuzzy methodologies have emerged as one of the most suitable and efficient methods for designing and developing complex systems in environments characterised by high level of uncertainty and imprecision.

Computational Intelligence Creating Procedural Content for Games

Middleware, Domain Specific Languages and Trust Getting heterogeneous devices and services to communicate and understand each other is problematic within pervasive computing environments. Staff profiles Ahmad Lotfi. Publications Selected publications from this group are listed below. Acampora G.

12222 IEEE Symposium Series on Computational Intelligence

In press. Interoperable neuro-fuzzy services for emotion-aware ambient intelligence.

Caller behaviour classification using computational intelligence methods.

Acampora G, Vitiello A, Neurocomputing, , vol. A proposal of ubiquitous fuzzy computing for Ambient Intelligence. Acampora, G.


  1. Baudolino.
  2. Passar bra ihop;
  3. ISBN 13: 9783642095153.
  4. ISBN 13: 9783642095153.

Information Sciences, , 3 , pp. Diet assessment based on type-2 fuzzy ontology and fuzzy markup language. Lee, C. Y and Hagras, H. Electrocardiogram application based on heart rate variability ontology and fuzzy markup language.

Computational Intelligence in Aerospace Sciences

Wang, C. Lee, G. However, the aerospace community and the computational intelligence community have maintained a certain degree of separation: Many aerospace problems are still poorly known to the CI community and many CI methods are not well known by the aerospace community; with the always fast evolving CI techniques slowly diffusing in the aerospace community, often as blackboxes. This main objective of this task force is to foster the development of computational intelligence techniques and methods for the solution of space and aerospace problems and push the boundaries of mathematics and computer science to fully embrace the complexity and richness of our world.

Chair Prof. Contact Us Terms Of Use. Copyright by University of Strathclyde. Saraswathi , S. In general, a sample test power system without FACTs devices has generated more reactive power, decreased real power, more harmonics, small power factor and poor dynamic performance under line and load variations.

In order to improve the real power, compensating the reactive power, proficient power factor and excellent load voltage regulation in the sample test power system, an IPFC is designed. The D-Q technique is utilized here to derive the reference current of the converter and its D. C link capacitor voltage is regulated. Also, the reference voltage of the inverter is arrived by park transformation technique and its load voltage is controlled.