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20082023
most citedIdiotypic Immune Networks in Mobile Robot Control

85 citations · 220 across the 29 of their papers we have counts for

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Showing 2013Show all

10 papers · 1 filter

cs.RO2013★ 2 cited

Performance Measurement Under Increasing Environmental Uncertainty In The Context of Interval Type-2 Fuzzy Logic Based Robotic Sailing

Naisan Benatar, Uwe Aickelin, Jonathan M. Garibald

Performance measurement of robotic controllers based on fuzzy logic, operating under uncertainty, is a subject area which has been somewhat ignored in the current literature. In th…

cs.LG2013

Using Clustering to extract Personality Information from socio economic data

Alexandros Ladas, Uwe Aickelin, Jon Garibaldi +1

It has become apparent that models that have been applied widely in economics, including Machine Learning techniques and Data Mining methods, should take into consideration princip…

cs.RO2013

An investigation into the relationship between type-2 FOU size and environmental uncertainty in robotic control

Naisan Benatar, Uwe Aickelin, Jonathan M. Garibaldi

It has been suggested that, when faced with large amounts of uncertainty in situations of automated control, type-2 fuzzy logic based controllers will out-perform the simpler type-…

cs.LG2013

Comparing Data-mining Algorithms Developed for Longitudinal Observational Databases

Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin +3

Longitudinal observational databases have become a recent interest in the post marketing drug surveillance community due to their ability of presenting a new perspective for detect…

cs.LG2013

Discovering Sequential Patterns in a UK General Practice Database

Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin +3

The wealth of computerised medical information becoming readily available presents the opportunity to examine patterns of illnesses, therapies and responses. These patterns may be…

cs.LG2013

Examining the Classification Accuracy of TSVMs with ?Feature Selection in Comparison with the GLAD Algorithm

Hala Helmi, Jon M. Garibaldi, Uwe Aickelin

Gene expression data sets are used to classify and predict patient diagnostic categories. As we know, it is extremely difficult and expensive to obtain gene expression labelled exa…