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The highest ranked value, accepted as a result of the fusion, guarantees improved accuracy and robustness of the interval data fusion procedure outputs.
Also, in certain contexts, a reduced set of variables may be used depending on their usefulness for the data fusion procedure.
The rest of the paper is organized as follows: Section 2 delves into the system model of the considered encoded data fusion scenario, whereas Section 3 elaborates on the design of the iterative decoding and data fusion procedure.
This paper presents a multivariate data fusion procedure for design of dynamic soft sensors where suitably selected image features are combined with traditional process measurements to enhance the performance of data-driven soft sensors.
It is proposed in the paper the interval data fusion procedure intended for determination of an interval to be consistent with maximal number of given initial intervals (not necessary consistent among each other) and to be with maximal likelihood including a value x∗ that can serve as representative of all the given intervals.
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Thus, the data fusion procedures utilize data from 78 schools in Iceland with full information from the PISA and TALIS data sets.
The interval data fusion procedures can be widely applied in interlaboratory comparisons, prediction of fundamental constant values on the base of different measured values, conformity testing, enhancement of multisensor readings accuracy in sensor networks, etc.
In saying that, we must emphasise that our experiments have been conducted specifically to investigate the Authority Effect, and that rather different procedures are normally applied when data fusion procedures are used in operational virtual screening systems.
Performance of this methodology is evaluated over adjacent irrigated and rainfed fields, since mixed conditions are the most challenging for data fusion procedures, and in two different climatic regions: a semi-arid site in Bushland, TX and a temperate site in Mead, NE.
Subsequently, a new information fusion procedure is proposed to acquire data from computer vision algorithms and its results are used to carry out a robust recognition process.
The algebraic method is robust against the choice of initial conditions and partition of data sets in training and testing sets for estimation of the nonadditive set functions of the information fusion procedure.
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