Kevin Swingler
Kevin Swingler
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Citované v
Applying neural networks: a practical guide
K Swingler
Morgan Kaufmann, 1996
Presymptomatic prediction of sepsis in intensive care unit patients
RA Lukaszewski, AM Yates, MC Jackson, K Swingler, JM Scherer, ...
Clinical and Vaccine Immunology 15 (7), 1089-1094, 2008
The development of a side effect risk assessment tool (ASyMS©-SERAT) for use in patients with breast cancer undergoing adjuvant chemotherapy
R Maguire, J Cowie, C Leadbetter, K McCall, K Swingler, L McCann, ...
Journal of Research in Nursing 14 (1), 27-40, 2009
Financial prediction: Some pointers, pitfalls and common errors
K Swingler
Neural Computing & Applications 4 (4), 192-197, 1996
Consensus on items and quantities of clinical equipment required to deal with a mass casualties big bang incident: a national Delphi study
EAS Duncan, K Colver, N Dougall, K Swingler, J Stephenson, ...
BMC emergency medicine 14 (1), 5, 2014
Learning and searching pseudo-Boolean surrogate functions from small samples
K Swingler
Evolutionary Computation 28 (2), 317-338, 2020
A semi-supervised corpus annotation for saudi sentiment analysis using twitter
A Alqarafi, A Adeel, A Hawalah, K Swingler, A Hussain
International Conference on Brain Inspired Cognitive Systems, 589-596, 2018
On the Capacity of Hopfield Neural Networks as EDAs for Solving Combinatorial Optimisation Problems.
K Swingler
IJCCI, 152-157, 2012
Producing a neural network for monitoring driver alertness from steering actions
K Swingler, LS Smith
Neural Computing & Applications 4 (2), 96-104, 1996
SUMS: A flexible approach to the teaching and learning of statistics
MV Swingler, P Bishop, KM Swingler
Psychology Learning & Teaching 8 (1), 39-45, 2009
Training and making calculations with mixed order hyper-networks
K Swingler, LS Smith
Neurocomputing 141, 65-75, 2014
A comparison of learning rules for mixed order hyper networks
K Swingler
Computational Intelligence (IJCCI), 2015 7th International Joint Conference …, 2015
An analysis of the local optima storage capacity of hopfield network based fitness function models
K Swingler, L Smith
Transactions on Computational Collective Intelligence XVII, 248-271, 2014
ASYMS-SERAT: a side-effect risk assessment tool to predict chemotherapy related toxicity in patients with cancer receiving chemotherapy
J Cowie, K Swingler, C Leadbetter, R Maguire, K McCall, N Kearney
HEALTHINF-International Conference on Health Informatics 2008, 225-230, 2008
Mixed Order Hyper-Networks for Function Approximation and Optimisation
K Swingler
University of Stirling, 2016
Opening the black box: analysing MLP functionality using walsh functions
K Swingler
Computational Intelligence, 303-323, 2016
Learning Spatial Relations with a Standard Convolutional Neural Network
K Swingler, M Bath
12th International Conference on Neural Computation Theory and Applications …, 2020
Structure discovery in mixed order hyper networks
K Swingler
Big Data Analytics 1 (1), 8, 2016
Local optima suppression search in mixed order hyper networks
K Swingler
Proc. UKCI 2015, 2015
A Walsh Analysis of Multilayer Perceptron Function.
K Swingler
IJCCI (NCTA), 5-14, 2014
Systém momentálne nemôže vykonať operáciu. Skúste to neskôr.
Články 1–20