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An Adaptive Neuro Fuzzy Inference System (ANFIS) is used for intelligent estimation of uncertainties.
This paper is dedicated to robustly compensate for the effects of modelling uncertainties and disturbances on the helicopter system, using intelligent estimation.
To this end, we take advantage of intelligent optimization algorithm in global searching and solving combinatorial optimization problems to guide the intelligent estimation.
From the simulation results, it is shown that the proposed intelligent estimation schemes can achieve better mean squared error (MSE) performance for channel and frequency offset estimation error than the conventional scheme.
An approach called Harmony [12] uses an intelligent estimation model of stale reads allowing elastically scale up or scale down of the number of replicas involved in read operations.
A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data.
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Satisfactory results opened the chance of building an intelligent motion estimation system that auto-adapted according to real-time, resource consumption, and accuracy requirements.
Get intelligent intelligence.
Finally, we provide some applications of our results in intelligent decision support systems, estimation and information fusion.
The findings are indicative of a good agreement between the estimation from intelligent models and the experimental data.
At each intelligent node, the local estimation is obtained based on its own measurement and those transmitted from its neighbors according to the sensor topology.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com