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Michael J. Watts
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Journal Articles
- 2012
- [j9]Albert Y. S. Lam, Michael J. Watts, Dongrui Wu, Pablo A. Estévez:
IEEE CIS Social Media: Have You Joined Our Online Community? [Society Briefs]. IEEE Comput. Intell. Mag. 7(1): 4-79 (2012) - 2009
- [j8]Michael J. Watts
:
A Decade of Kasabov's Evolving Connectionist Systems: A Review. IEEE Trans. Syst. Man Cybern. Part C 39(3): 253-269 (2009) - 2008
- [j7]Michael J. Watts, Susan P. Worner:
Using artificial neural networks to determine the relative contribution of abiotic factors influencing the establishment of insect pest species. Ecol. Informatics 3(1): 64-74 (2008) - [j6]Michael J. Watts, Susan P. Worner:
Comparing ensemble and cascaded neural networks that combine biotic and abiotic variables to predict insect species distribution. Ecol. Informatics 3(6): 354-366 (2008) - 2004
- [j5]Michael J. Watts:
Fuzzy Rule Extraction From Simple Evolving Connectionist Systems. Int. J. Comput. Intell. Appl. 4(3): 299-308 (2004) - 2003
- [j4]Samuel Moyle, Michael J. Watts:
Neural Nets Raise the Roof. IEEE Intell. Syst. 18(1): 8-10 (2003) - [j3]Akbar Ghobakhlou, Michael J. Watts
, Nikola K. Kasabov
:
Adaptive speech recognition with evolving connectionist systems. Inf. Sci. 156(1-2): 71-83 (2003) - 1998
- [j2]Nikola K. Kasabov, Robert Kozma, Michael J. Watts:
Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and Learning. Inf. Sci. 110(1-2): 61-79 (1998) - 1997
- [j1]Nikola K. Kasabov, Jaesoo Kim, Michael J. Watts, Andrew R. Gray
:
FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition. Inf. Sci. 101(3-4): 155-175 (1997)
Conference and Workshop Papers
- 2018
- [c17]Amir Hossein Moravejosharieh, Michael J. Watts, Yu Song:
Bandwidth Reservation Approach to Improve Quality of Service in Software-Defined Networking: A Performance Analysis. JCSSE 2018: 1-6 - 2016
- [c16]Michael J. Watts:
Sleep learning and Max-Min aggregation of Evolving Connectionist Systems. IJCNN 2016: 4325-4330 - 2014
- [c15]Michael J. Watts:
Evolving Connectionist Systems can predict outbreaks of the aphid Rhopalosiphum padi. IJCNN 2014: 646-650 - [c14]André Bianconi, Michael J. Watts, Yanbo Huang, Adriane Beatriz de Souza Serapião
, José Silvio Govone, X. Mi, Gustavo Habermann, Alessandro Ferrarini
:
Applying computational intelligence methods to modeling and predicting common bean germination rates. IJCNN 2014: 658-662 - 2008
- [c13]Michael J. Watts
, Susan P. Worner:
Predicting the Distribution of Fungal Crop Diseases from Abiotic and Biotic Factors Using Multi-Layer Perceptrons. ICONIP (1) 2008: 901-908 - [c12]David R. Pontin, Susan P. Worner, Michael J. Watts
:
Using Time Lagged Input Data to Improve Prediction of Stinging Jellyfish Occurrence at New Zealand Beaches by Multi-Layer Perceptrons. ICONIP (1) 2008: 909-916 - [c11]David R. Pontin, Michael J. Watts
, Susan P. Worner:
Using Multi-Layer Perceptrons to predict the presence of jellyfish of the genus Physalia at New Zealand beaches. IJCNN 2008: 1170-1175 - 2006
- [c10]Michael J. Watts, Susan P. Worner:
Null-Model Validation of MLP Input Contribution Analysis in Ecology. HIS 2006: 63 - [c9]Michael J. Watts, Susan P. Worner:
Using MLP to Determine Abiotic Factors In uencing the Establishment of Insect Pest Species. IJCNN 2006: 1840-1845 - [c8]Michael J. Watts:
Nominal-scale Evolving Connectionist Systems. IJCNN 2006: 2055-2059 - 2002
- [c7]Samuel Moyle, Michael J. Watts:
Fuzzy Neural Networks in a Palm Environment. AAAI/IAAI 2002: 1008-1009 - [c6]Michael J. Watts
, Louise Major
, Warren Tate:
Evolutionary optimisation of MLP for modelling protein synthesis termination signal efficiency. IEEE Congress on Evolutionary Computation 2002: 193-198 - [c5]Michael J. Watts
, Nikola K. Kasabov
:
Evolutionary optimisation of evolving connectionist systems. IEEE Congress on Evolutionary Computation 2002: 606-610 - 2001
- [c4]Michael J. Watts
, Nikola K. Kasabov:
Dynamic optimisation of evolving connectionist system training parameters by pseudo-evolution strategy. CEC 2001: 1335-1342 - 1998
- [c3]Michael J. Watts, Nikola K. Kasabov:
Genetic Algorithms for the Design of Fuzzy Neural Networks. ICONIP 1998: 793-796 - 1997
- [c2]Nikola K. Kasabov
, Michael J. Watts:
Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks. ICNN 1997: 2546-2549 - [c1]Nikola K. Kasabov, Robert Kozma, Richard Kilgour, Mark R. Laws, J. Taylor, Michael J. Watts, Andrew R. Gray:
A Methodology for Speech Data Analysis and a Framework for Adaptive Speech Recognition Using Fuzzy Neural Networks. ICONIP (2) 1997: 1055-1060
Coauthor Index
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