ISNN2006 - Special Session on Hybrid Neurocomputing

[Ajith Abraham <abraham.ajith@gmail.com>]

Hybrid Neurocomputing in Finance Modeling and Forecastinghttp://cilab.ujn.edu.cn/isnn.htm
A special session at ISNN2006 – The Third International Symposium onNeural Networks, May 29-31, 2006, Chengdu, China

Session ChairsYuehui Chen (Jinan University, Shandong, Jinan, China)Ajith Abraham (Chung Ang University, Seoul, South Korea)
Scope and Call for Papers
The special session aims to bring together professionals and thescientific community in the fields of financial engineering and hybridneurocomputing in finance. Hybrid neurocomputing is a well-establishedparadigm, where new theories with a sound biological understandinghave been evolving. Hybrid architectures like evolutionary neuralnetworks, fuzzy neural networks, wavelet neural networks, flexibleneural tree, multiple neural networks, hierarchical neural networksand so on, are widely applied for real-world problem solving. Hybridneurocomputing techniques have the potential to impact many financialapplications, from portfolio selection to proprietary trading to riskmanagement.
The special session greatly encourages new ideas/papers, combining twoor more areas, such as evolutionary neural networks, fuzzy neuralnetworks, wavelet neural networks, flexible neural tree, neuralnetworks ensemble, multiple neural networks, hierarchical neuralnetworks, etc. to be submitted.
Topics of Interest include, but are not limited to applications andtheory dealing with any aspect of hybrid neurocomputing as:
Application Areas -  Artificial Stock Markets -  Behavioral Finance -  Experimental Economics -  Financial Engineering -  Financial Data Mining -  Trading Strategies -  Hedging Strategies -  Portfolio Management -  Derivative Pricing -  Term Structure Models -  Financial Time Series Forecasting and Analysis -  Neural Economics
Techniques -   Evolutionary neural networks -   Fuzzy neural networks -   Wavelet neural networks
 -   Flexible neural tree
 -   Ensemble of neural networks
 -   Multiple neural networks
 -   Hierarchical neural networks -   Input/feature selection and data mining for neural network training -   Neural networks learning algorithms -   Parallel algorithms for neural networks


Important DatesPaper submission (ISNN2006):                                            November 15, 2005Notification of acceptance (ISNN2006):                               December 15, 2005Final paper submission and authors' registration:                     January 15, 2006Paper submission (IJNS Special Issue):                                 June 30, 2006Notification of acceptance (IJNS Special Issue):                    December 31, 2006


Paper Submission
Please following the ISNN2006 paper submission web site at:http://www2.acae.cuhk.edu.hk/~isnn2006/submission.htm


Publication
The authors of accepted papers will have an opportunity to revisetheir papers and take consideration of the referees' comments andsuggestions. All papers accepted and presented at ISNN2006 will bepublished by Springer as multiple volumes of Lecture Notes in ComputerScience which are indexed by SCI-Expanded.


Contacts
Yuehui Chen (yhchen@ujn.edu.cn)
Ajith Abraham (ajith.abraham@ieee.org)


International Program Committee
Antony Satyadas, IBM Corporation, Cambridge, USA
Janusz Kacprzyk, Polish Academy of Sciences, Poland
Lakhmi Jain, University of South Australia, Australia
P. Saratchandran, Nanyang Technological University, Singapore
X. Yao, The University of Birmingham, U.K
Jun Wang, Chinese University of Hong Kong, Hong Kong
Costa Branco P J, Instituto Superior Technico, Portugal
Sung Bae Cho, Yonsei University, Korea
Yuehui Chen, Jinan University, China
Yasuhiko Dote, Muroran Institute of Technology, Japan
Matjaz Gams, Jozef Stefan Institute, Slovenia
Amit Konar, Jadavpur University, India
Derong Liu, University of Illinois at Chicago, USA
Witold Pedrycz, University of Alberta, Canada
Ronald Yager, Iona College, USA