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@INPROCEEDINGS{Abraham02P,
author = {Abraham, A.},
title = {``{O}ptimization of Evolutionary Neural Networks Using Hybrid Learning Algorithms''},
booktitle = {Proceedings of IJCNN 2002},
year = {2002},
pages = {2797-2802},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.16.7072&rep=rep1&type=pdf}
}
@ARTICLE{Abraham04J,
author = {Abraham, A.},
title = {``{M}eta-Learning Evolutionary Artificial Neural Networks''},
journal = {Neurocomputing},
year = {2003},
volume = {56},
pages = {1-38},
text = {Abraham A., Meta-Learning Evolutionary Artificial Neural Networks,
Neurocomputing Journal, Elsevier Science, Netherlands, 2003 (in press).},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.12.6334&rep=rep1&type=pdf}
}
@INCOLLECTION{AbrahamJain04C,
author = {Abraham, A. and Jain, L.},
title = {``{S}oft Computing Models for Network Intrusion Detection Systems''},
booktitle = {Soft Computing in Knowledge Discovery: Methods and Applications},
publisher = {Springer Verlag Germany},
year = {2004},
editor = {Saman Halgamuge and Lipo Wang},
chapter = {16},
url = {http://www.cs.bham.ac.uk/~wbl/biblio/cache/http___www.softcomputing.net_saman2.pdf}
}
@TECHREPORT{AbrahamNath00TR,
author = {Abraham, A. and Nath, B.},
title = {``{H}ybrid intelligent systems design: A review of a decade of research''},
institution = {School of Computing and Information Technology, Monash University,
Australia},
year = {2000},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.18.469&rep=rep1&type=pdf}
}
@INPROCEEDINGS{CheuQuekNg10P,
author = {Cheu, Eng Yeow and Quek, Chai and Ng, See Kiong},
title = {``{T}ime series forecasting with appetitive reward-based pseudo-outer-product fuzzy neural network''},
booktitle = {Neural Networks (IJCNN), The 2010 International Joint Conference
on},
year = {2010},
pages = {1 -8},
month = july,
doi = {10.1109/IJCNN.2010.5596738},
issn = {1098-7576},
keywords = {ARPOP-CRI;Aplysia;activity-dependent synaptic plasticity;appetitive
reward learning algorithm;appetitive reward-based pseudo-outer-product
fuzzy neural network;associative ambiguity correction-based neuro-fuzzy
network;cellular mechanisms;electrical stimulation;esophageal nerve;feeding
behavior;feeding motor circuitry;memory storage;molecular mechanisms;operant
memory;time series forecasting;behavioural sciences computing;biology
computing;cellular biophysics;forecasting theory;fuzzy neural nets;molecular
biophysics;time series;}
}
@INPROCEEDINGS{DasAngQuek10P,
author = {Das, R.T. and Kai Keng Ang and Chai Quek},
title = {``{A} synergy of econometrics and computational methods (GARCH-RNFS) for volatility forecasting''},
booktitle = {Evolutionary Computation (CEC), 2010 IEEE Congress on},
year = {2010},
pages = {1 -8},
month = july,
doi = {10.1109/CEC.2010.5586324},
keywords = {GARCH;RNFS;RPV;econometrics;generalized autoregressive conditional
heteroscedasticity;information extraction;intraday volatility indicator;neuro-fuzzy
system;realized power variation;rough-set theory;volatility forecasting;autoregressive
processes;econometrics;fuzzy set theory;rough set theory;}
}
@INPROCEEDINGS{GanjiAbadeh10P,
author = {Ganji, M.F. and Abadeh, M.S.},
title = {``{U}sing fuzzy ant colony optimization for diagnosis of diabetes disease''},
booktitle = {Electrical Engineering (ICEE), 2010 18th Iranian Conference on},
year = {2010},
pages = {501 -505},
month = may,
doi = {10.1109/IRANIANCEE.2010.5507019},
keywords = {FADD;Pima Indian Diabetes data set;data mining;diabetes;fuzzy ant
colony optimization;patient diagnosis;rule based classification systems;data
mining;diseases;fuzzy logic;medical diagnostic computing;optimisation;patient
diagnosis;pattern classification;}
}
@ARTICLE{GaoEr05J,
author = {Gao, Y. and Er, M.J.},
title = {``{NARMAX} time series model prediction: feedforward and recurrent fuzzy neural networks approaches''},
journal = {Fuzzy Sets and Systems},
year = {2005},
volume = {150},
pages = {331-350}
}
@INPROCEEDINGS{HoTungQuek10P,
author = {Weng Luen Ho and Whye Loon Tung and Chai Quek},
title = {``{A}n evolving Mamdani-Takagi-Sugeno based neural-fuzzy inference system with improved interpretability-accuracy''},
booktitle = {Fuzzy Systems (FUZZ), 2010 IEEE International Conference on},
year = {2010},
pages = {1 -8},
month = july,
doi = {10.1109/FUZZY.2010.5584831},
issn = {1098-7584},
keywords = {T-S fuzzy modeling approach;eMTSFIS model;evolving Mamdani-Takagi-Sugeno
neural fuzzy inference system;fuzzy rule structure;fuzzy rule-base
interpretability;life-long learning;localized parameter learning
approach;neural-fuzzy network architecture;fuzzy neural nets;fuzzy
reasoning;knowledge based systems;}
}
@ARTICLE{HongWhite09J,
author = {Hong, Yoon-Drok Timothy and White, Paul A.},
title = {``{H}ydrological modeling using a dynamic neuro-fuzzy system with on-line and local learning algorithm''},
journal = {Advances in Water Resources},
year = {2009},
volume = {32},
pages = {110-119},
owner = {a1207741},
timestamp = {2011.03.19},
url = {https://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VCF-4TRK0VC-3&_user=10&_coverDate=01%2F31%2F2009&_rdoc=1&_fmt=high&_orig=gateway&_origin=gateway&_sort=d&_docanchor=&view=c&_rerunOrigin=scholar.google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=01afd307fd30e72103a8a425b40f46ef&searchtype=a}
}
@INPROCEEDINGS{HuangPasquierChai08P,
author = {Huang, Haoming and Pasquier, Michael and Quek, Chai},
title = {``{A}pplication of a Hierarchical Coevolutionary Fuzzy System for Financial Prediction and Trading''},
booktitle = {Proceedings of IJCNN 2008},
year = {2008},
pages = {1252-1259}
}
@INPROCEEDINGS{MuraliSriskanthanNg03P,
author = {Murali, T. and Sriskanthan, N. and Ng, G.S.},
title = {``{C}omparative analysis of the two fuzzy neural systems {ANFIS} and {EFuNN} for the classification of handwritten digits''},
booktitle = {The Seventh IEEE International Symposium on Consumer Electronics,
Sydney, Australia, December 3-5, 2003},
year = {2003}
}
@ARTICLE{Ngetal06J,
author = {Ng, G.S. and Erdogan, S. and Shi, D. and Wahab, A.},
title = {``{I}nsight of fuzzy neural systems in the application of handwritten digits classification''},
journal = {International Journal of Image and Graphics},
year = {2006},
volume = {4},
pages = {511-532},
url = {http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=20070434049445CI}
}
@INPROCEEDINGS{NguyenQuek10P,
author = {Nguyen, Ngoc Nam and Quek, Chai},
title = {``{S}tock price prediction using Generic Self-Evolving Takagi-Sugeno-Kang (GSETSK) fuzzy neural network''},
booktitle = {Neural Networks (IJCNN), The 2010 International Joint Conference
on},
year = {2010},
pages = {1 -8},
month = july,
doi = {10.1109/IJCNN.2010.5596348},
issn = {1098-7576},
keywords = {GSETSK fuzzy neural network;GSETSK network;MSGC algorithm;fuzzy rule;generic
self-evolving Takagi-Sugeno-Kang fuzzy neural network;human cognitive
process;multidimensional-scaling growing clustering;noise-tolerance
capability;online adaptive system;stock market price prediction;forecasting
theory;fuzzy neural nets;pattern clustering;pricing;stock markets;}
}
@INPROCEEDINGS{5393534,
author = {Pahariya, J.S. and Ravi, V. and Carr, M.},
title = {``{S}oftware cost estimation using computational intelligence techniques''},
booktitle = {Nature Biologically Inspired Computing, 2009. NaBIC 2009. World Congress
on},
year = {2009},
pages = {849 -854},
month = dec.,
doi = {10.1109/NABIC.2009.5393534},
keywords = {International Software Benchmarking Standards Group release 10 dataset;arithmetic
mean;computational intelligence techniques;counter propagation neural
network;data handling;dynamic evolving neuro-fuzzy inference system;genetic
programming;geometric mean;group method;harmonic mean;linear ensembles;multilayer
feedforward neural network;multiple linear regression;multivariate
adaptive regression splines;polynomial regression;radial basis function
neural network;recurrent architecture;regression tree;software cost
estimation;support vector regression;ten-fold cross validation;tree
net;data handling;fuzzy neural nets;fuzzy reasoning;genetic algorithms;geometry;radial
basis function networks;regression analysis;software cost estimation;splines
(mathematics);trees (mathematics);}
}
@INPROCEEDINGS{Pertselakisetal01P,
author = {Pertselakis, M. and Tsapatsoulis, N. and Kollias, S. and Stafylopatis, A.},
title = {``{A}n adaptive resource allocating neural fuzzy inference system''},
booktitle = {Proceedings of the IEEE Intelligent Systems Application to Power
Systems (ISAP'03), Lemnos, Greece, August 2003},
year = {2001},
url = {http://www.image.ece.ntua.gr/projects/oresteia/publications/papers/PerC01.pdf}
}
@ARTICLE{Petrovic-LazarevicCoghillAbraham04J,
author = {Petrovic-Lazarevic, S. and Coghill, K. and Abraham, A.},
title = {``{N}euro-fuzzy modelling in support of knowledge management in social regulation of access to cigarettes by minors''},
journal = {Knowledge-Based- Systems},
year = {2004},
volume = {17},
pages = {57-60},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.59.9855&rep=rep1&type=pdf}
}
@INPROCEEDINGS{PouzolsLendasse10P,
author = {Pouzols, F.M. and Lendasse, A.},
title = {``{E}volving fuzzy Optimally Pruned Extreme Learning Machine: A comparative analysis''},
booktitle = {Fuzzy Systems (FUZZ), 2010 IEEE International Conference on},
year = {2010},
pages = {1 -8},
month = july,
doi = {10.1109/FUZZY.2010.5584327},
issn = {1098-7584},
keywords = {OP-ELM methodology;evolving fuzzy optimally pruned extreme learning
machine;evolving neuro fuzzy system;extracting evolving fuzzy rulebases;fuzzy
Takagi-Sugeno systems;online sequential ELM method;random hidden
neurons;random projection based approach;single hidden layer feedforward
artificial neural networks;feedforward neural nets;fuzzy neural nets;learning
(artificial intelligence);}
}
@INPROCEEDINGS{PouzolsLendasse10P2,
author = {Pouzols, F.M. and Lendasse, A.},
title = {``{E}ffect of different detrending approaches on computational intelligence models of time serie''},
booktitle = {Neural Networks (IJCNN), The 2010 International Joint Conference
on},
year = {2010},
pages = {1 -8},
month = july,
doi = {10.1109/IJCNN.2010.5596314},
issn = {1098-7576},
keywords = {Gaussian process;computational intelligence model;dynamic evolving
neural-fuzzy inference system;empirical mode decomposition;first-differencing
approach;linear detrending approach;multilayer perceptron;nonlinear
detrending approach;optimally-pruned extreme learning machine;support
vector machines;time series;Gaussian processes;fuzzy neural nets;fuzzy
reasoning;learning (artificial intelligence);mathematics computing;multilayer
perceptrons;support vector machines;time series;},
url = {http://research.ics.tkk.fi/eiml/Publications/Publication173.pdf}
}
@INPROCEEDINGS{Ramos03P,
author = {Ramos, J.V.},
title = {``{E}volving {Takagi-Sugeno} Fuzzy Models for Data Mining''},
booktitle = {Proc. of the Workshop on Soft Computing and Complex Systems, SoftComplex'03,
Coimbra, Portugal, June 2003},
year = {2003},
pages = {144-154},
url = {http://cisuc.dei.uc.pt/isg/dlfile.php?fn=760_pub_ETSFM.pdf&get=1&idp=760&ext=}
}
@TECHREPORT{RamosDourado03TR,
author = {Ramos, J.V. and Dourado, A.},
title = {``{E}volving {Takagi-Sugeno} Fuzzy Models''},
institution = {Centre for Informatics and Systems Adaptive Computation Group},
year = {2003},
month = {September},
url = {http://cisuc.dei.uc.pt/dlfile.php?fn=760_pub_ETSFM.pdf&get=1&idp=760&ext=}
}
@ARTICLE{WattsWorner06J,
author = {Watts, M.J. and Worner, S.P.},
title = {``{C}omparison of a Self Organising Map and Simple Evolving Connectionist System for Predicting Insect Pest Establishment''},
journal = {International Journal of Information Technology},
year = {2006},
volume = {12},
pages = {35-42},
number = {6},
owner = {a1207741},
timestamp = {2010.03.31},
url = {http://www.icis.ntu.edu.sg/scs-ijit/1206/IJIT-1206_05.pdf}
}
@INPROCEEDINGS{Woodford01P,
author = {Woodford, B.J.},
title = {``{C}omparative analysis of the {EFuNN} and the {Support Vector Machine} models for the classification of horticulture data''},
booktitle = {Proceedings of the Fifth Biannual Conference on Artificial Neural
Networks and Expert Systems (ANNES2001)},
year = {2001},
url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.18.4285&rep=rep1&type=pdf}
}
@INPROCEEDINGS{XuhuaFeng10P,
author = {Shi Xuhua and Qian Feng},
title = {``{I}mmune Agent-Based Neural Networks Assembly for Soft-Sensor''},
booktitle = {Intelligent Systems and Applications (ISA), 2010 2nd International
Workshop on},
year = {2010},
pages = {1 -4},
month = may,
doi = {10.1109/IWISA.2010.5473737},
keywords = {IMMST-team system;RBF submodels;artificial immune agent;crude oil
tower;immune system;industrial process data;learning rules;neural
networks;pattern recognition;radial basis function networks;soft
sensor model;artificial immune systems;crude oil;learning (artificial
intelligence);manufacturing data processing;pattern clustering;radial
basis function networks;sensors;}
}
@INPROCEEDINGS{YamauchiSato07P,
author = {Yamauchi, K. and Sato, M.},
title = {``{I}ncremental Learning of Spatio-temporal Patterns with Model Selection''},
booktitle = {Proceedings of ICANN 2007},
year = {2007},
url = {http://www.springerlink.com/index/H82MG64405778620.pdf}
}
@INPROCEEDINGS{ZanchettinMinkuLudermir05P,
author = {Zanchettin, C. and Minku, F.L. and Ludermir, T.B.},
title = {``{D}esign of experiments in neuro-fuzzy systems''},
booktitle = {Hybrid Intelligent Systems, 2005. HIS '05. Fifth International Conference
on},
year = {2005},
pages = {6-9},
url = {http://www.computer.org/portal/web/csdl/doi/10.1109/ICHIS.2005.34}
}