Improving the accuracy of static branch prediction using branch correlation
ASPLOS VI Proceedings of the sixth international conference on Architectural support for programming languages and operating systems
Analysis of branch prediction via data compression
Proceedings of the seventh international conference on Architectural support for programming languages and operating systems
Confidence estimation for speculation control
Proceedings of the 25th annual international symposium on Computer architecture
LeZi-update: an information-theoretic framework for personal mobility tracking in PCS networks
Wireless Networks - Selected Papers from Mobicom'99
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Prediction of indoor movements using bayesian networks
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
Controlling Uncertainty in Personal Positioning at Minimal Measurement Cost
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
Structured context prediction: a generic approach
DAIS'10 Proceedings of the 10th IFIP WG 6.1 international conference on Distributed Applications and Interoperable Systems
HABITS: a Bayesian filter approach to indoor tracking and location
International Journal of Bio-Inspired Computation
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Neural networks, Bayesian networks, Markov models, and state predictors are different methods to predict the next location. For all methods a lot of parameters must be set up which differ for each user. Therefore a complex configuration must be made before such a method can be used. A hybrid predictor can reduce the configuration overhead utilizing different prediction methods or configurations in parallel to yield different prediction results. A selector chooses the most appropriate prediction result from the result set of the base predictors. We propose and evaluate three principal hybrid predictor approaches – the warm-up predictor, the majority predictor, and the confidence predictor – with several variants. The hybrid predictors reached a higher prediction accuracy than the average of the prediction accuracies of the separately used predictors.