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Motivated by the above recorded studies, in this paper, we propose a 'modified hybrid Picard-Mann' iteration process for iterative approximation of fixed points of total asymptotically nonexpansive mappings in (CAT 0)) spaces.
In this paper, we develop a new progressive and iterative approximation for least square fitting (LSPIA).
The progressive and iterative approximation (PIA) method is an efficient and intuitive method for data fitting.
Based on the covering linear programming (CLP), a fast iterative approximation scheme is designed to solve this newly formulated problem.
We implement an iterative approximation procedure based on this idea, and the procedure demonstrates the desirable anytime property in experiments.
Therefore, each stage focuses the search on a specific region, leading to an iterative approximation of the entire nondominated set.
Additionally, based on the load parameter, a method of fuel iterative approximation (FIA) is proposed to predict the LBO limit of the combustor.
In the present study, a method named Fuel Iterative Approximation (FIA) is proposed based on FV model for LBO limit predictions.
In practice, one has to solve the implicit algebraic equations using some iterative approximation method, in which case the resulting integration scheme is no longer symplectic.
Recently, for the sake of fitting scattered data points, an important method based on the PIA (progressive iterative approximation) property of the univariate NTP (normalized totally positive) bases has been effectively adopted.
Iterative approximation of fixed points of total nonexpansive mappings has also been studied by [12 15].
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