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In this work we address the development and implementation of the analytic coarse-mesh finite-difference (ACMFD) method in a nodal neutron diffusion solver called ANDES.
As a spatial implementation of the Analytic Hierarchy Process (AHP), ASSESS has been used extensively for MCDA in a policy environment, but has not previously been described in peer-reviewed literature.
The study was conducted as part of a project to evaluate the implementation of the "Analytic Hierarchy Process" used by the public when choosing family physicians.
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Our numerical results indicate that our method compares very well with the best known implementations of the analytic FMM method for both the Laplacian and modified Laplacian kernels.
A computer implementation of the new analytic model confirms our hypothesis that the bias is systematically dependent on the electrode configuration.
As such, triple optimization of sensing, computing and communication tasks is required to facilitate the implementation of data analytics on the sensor devices.
Many researchers usually adopted the more sophisticated multi-attribute decision methodologies in the complex provider selection problem, and these types of implementation methodologies involved the analytic hierarchy process (AHP) [ 43, 44], the multi-objective programming [ 45], and the multi-attribute utility theory [ 46].
In contrast to this view, we have seen in the previous part of this paper, that the implementation of additional analytics capabilities contributes to extend the use of BI technologies, making the combination between knowledge management and data highly beneficial for decision-makers and players involved in the delivery of knowledge services.
Table 2 presents below a comparative example of the implementation of the use of knowledge-analytics by six of the leading cloud-based knowledge services providers (provider brands has been anonimized).
The rest of this paper is organised as follows: Section II describes the algorithms and technologies underpinning the proposed architecture along with related work in this Section III outlines the architecture and implementation of the proposed technical support analytics platform.
While the implementation of data analytics may be complex, the return on investments is significant.
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