Michael J. Watts - researchr profile publications

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Viewing Publication 1 - 25 from 25

2018

Bandwidth Reservation Approach to Improve Quality of Service in Software-Defined Networking: A Performance AnalysisAmir Hossein Moravejosharieh, Michael J. Watts, Yu Song. jcsse 2018: 1-6 [doi]

2016

Sleep learning and Max-Min aggregation of Evolving Connectionist SystemsMichael J. Watts. ijcnn 2016: 4325-4330 [doi]

2014

Applying computational intelligence methods to modeling and predicting common bean germination ratesA. Bianconi, Michael J. Watts, Y. Huang, A. B. S. Serapiao, J. S. Govone, X. Mi, G. Habermann, A. Ferrarini. ijcnn 2014: 658-662 [doi]

Evolving Connectionist Systems can predict outbreaks of the aphid Rhopalosiphum padiMichael J. Watts. ijcnn 2014: 646-650 [doi]

2012

IEEE CIS Social Media: Have You Joined Our Online Community? [Society Briefs]Albert Y. S. Lam, Michael J. Watts, Dongrui Wu, Pablo A. Estévez. cim, 7(1):4-79, 2012. [doi]

2009

A Decade of Kasabov s Evolving Connectionist Systems: A ReviewMichael J. Watts. tsmc, 39(3):253-269, 2009. [doi]

2008

Using Time Lagged Input Data to Improve Prediction of Stinging Jellyfish Occurrence at New Zealand Beaches by Multi-Layer PerceptronsDavid R. Pontin, Susan P. Worner, Michael J. Watts. iconip 2009: 909-916 [doi]

Using Multi-Layer Perceptrons to predict the presence of jellyfish of the genus Physalia at New Zealand beachesDavid R. Pontin, Michael J. Watts, Susan P. Worner. ijcnn 2008: 1170-1175 [doi]

Predicting the Distribution of Fungal Crop Diseases from Abiotic and Biotic Factors Using Multi-Layer PerceptronsMichael J. Watts, Susan P. Worner. iconip 2009: 901-908 [doi]

Comparing ensemble and cascaded neural networks that combine biotic and abiotic variables to predict insect species distributionMichael J. Watts, Susan P. Worner. ecoi, 3(6):354-366, 2008. [doi]

Using artificial neural networks to determine the relative contribution of abiotic factors influencing the establishment of insect pest speciesMichael J. Watts, Susan P. Worner. ecoi, 3(1):64-74, 2008. [doi]

2006

Nominal-scale Evolving Connectionist SystemsMichael J. Watts. ijcnn 2006: 2055-2059 [doi]

Null-Model Validation of MLP Input Contribution Analysis in EcologyMichael J. Watts, Susan P. Worner. his 2006: 63 [doi]

Using MLP to Determine Abiotic Factors In uencing the Establishment of Insect Pest SpeciesMichael J. Watts, Susan P. Worner. ijcnn 2006: 1840-1845 [doi]

2004

Fuzzy Rule Extraction From Simple Evolving Connectionist SystemsMichael J. Watts. ijcia, 4(3):299-308, 2004. [doi]

2003

Adaptive speech recognition with evolving connectionist systemsAkbar Ghobakhlou, Michael J. Watts, Nikola K. Kasabov. isci, 156(1-2):71-83, 2003. [doi]

Neural Nets Raise the RoofSamuel Moyle, Michael J. Watts. expert, 18(1):8-10, 2003. [doi]

2002

Fuzzy Neural Networks in a Palm EnvironmentSamuel Moyle, Michael J. Watts. AAAI 2002: 1008-1009

Evolutionary optimisation of evolving connectionist systemsMichael J. Watts, Nikola K. Kasabov. cec 2002: 606-610 [doi]

2001

Dynamic optimisation of evolving connectionist system training parameters by pseudo-evolution strategyMichael J. Watts, Nikola K. Kasabov. cec 2001: 1335-1342 [doi]

1998

Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and LearningNikola K. Kasabov, Robert Kozma, Michael J. Watts. isci, 110(1-2):61-79, 1998.

Genetic Algorithms for the Design of Fuzzy Neural NetworksMichael J. Watts, Nikola K. Kasabov. iconip 1998: 793-796

1997

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