Artificial Intelligence: A Guide to Building Intelligent Systems

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17 Ιουλ 2012 (πριν από 5 χρόνια και 3 μήνες)

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How to Register:
*
Register Online: www.nicta.com.au/short_courses
*
Register using the form on the back of this page
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Teaching Arrangements:
The course will be conducted from 9.00 am to 5.00 pm
Morning tea, lunch and afternoon tea will be provided.
For further info please contact
Anne-Marie Eliseo +61 8 8343 8710
or email industryeducation@nicta.com.au
www.nicta.com.au/short_courses
Overview
The main objective of this course is to acquaint participants with
Computational Intelligence and Soft Computing and provide them with
working knowledge for building intelligent systems for solving practical
problems.
Participants not only benefit from understanding methods and
procedures involved in computational intelligence including fuzzy
modelling, artificial neural networks, hybrid neuro-fuzzy systems and
genetic algorithms, but also acquire access to the state-of-the-art in
soft computing.
Target Audience
Researchers, scientists and engineers who face challenging problems
and cannot solve them by using traditional approaches, everyone who
wants to understand the tremendous achievements in soft computing
and computational intelligence.
Brief Course Outline
1. Fuzzy Systems

Introduction, or what is fuzzy thinking

Fuzzy sets

Fuzzy rules and fuzzy inference

Building a fuzzy system

Summary and Exercises
2. Artificial Neural Networks

Introduction, or how the brain works

The perception

Supervised learning

Unsupervised learning

Summary and Exercises
3. Evolutionary Computation

Genetic algorithms

Case study: maintenance scheduling with genetic algorithms

8–10 August 2011

Prof. Michael Negnevitsky
University of Tasmania

Adelaide

AU$1980 (includes GST)
price includes text book
Artificial Intelligence:
A Guide to Building Intelligent Systems

Evolutionary strategies

Genetic tuning of fuzzy models

Summary and Exercises
4. Hybrid Intelligent Systems

Introduction, or how to combine German mechanics with Italian love

Neuro-fuzzy systems

ANFIS: Adaptive Neuro-Fuzzy inference system
5. Knowledge Engineering and Data Mining

What is knowledge engineering?

Will an expert system work for me?

Will a fuzzy expert system work for me?

Will neural networks work for me?

Will genetic algorithms work for me?

Will a hybrid intelligent system work for me?

Data mining and knowledge discovery

Summary and Exercises
Practical Approach using Matlab
The course includes practical, hands-on sessions where participants
are given the opportunity to apply in practice the theory they have
learnt.
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ABN 62 102 206 173
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FAX the completed form to +61 8 8343 8711 or EMAIL it to industryeducation@nicta.com.au
Cancellation Policy:
At least 4 weeks notice is required for full reimbursement. If cancellation is later than 4 weeks then the place can either be transferred to another person or the
registrant can be provided with a credit towards other NICTA training.
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Mawson Lakes SA 5095, Australia.
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How to register:

Fax this form to +61 8 8343 8711 or

Scan and email this form to industryeducation@nicta.com.au or

Online registration: www.nicta.com.au/short_courses
Method of Payment (please tick below):
www.nicta.com.au/short_courses
080811
Artificial Intelligence: A Guide to Building Intelligent Systems
8–10 August 2011 :: Fee: AU$1980 (includes GST) —price includes text book
Technology Park Conference Centre, Mawson Lakes South Australia
Course Presenter
Professor Michael Negnevitsky is the Chair
in Power Engineering and Computational
Intelligence and the a Director of the Centre
for Renewable Energy and Power Systems at
the University of Tasmania, Australia. He is
well known for his work in the field of artificial
intelligence applications. Negnevitsky was
an invited speaker at Hiroshima University,
Japan; The Center for Adaptive Systems at
Boston University, USA; Norwegian University
of Science and Technology;Rochester Institute
of Technology, USA; University of Colorado, USA
and delivered Sir Victor Burley Lecture at the
Joint Electrical Meeting (IEAust and IEE), Australia
The course has been delivered at Otto-von-Guericke-Universitat,
Magdeburg, Institut Elektronantriebstechnik, Magdeburg, Germany,
Hiroshima University Japan, Boston University USA, and Rochester
Institure of Techonlogy, USA
Negnevitsky has co-authored over 250 research publications including
numerous journal articles.
The lectures in this course are part of Professor Negnevitsky’s recent
book entitled
Artificial Intelligence: A Guide to Intelligent Systems
, 2nd
ed., Addison-Wesley, 2005