There arises a demand on the integration of recent knowledge management (KM), artificial intelligence technology with the conventional hydraulic algorithmic models in order to assist novice application users in selection and manipulation of various mathematical tools.
Due to the complexity of the numerical simulation of flow and/or water quality, there is an increasing demand for integration of recent knowledge management, artificial intelligence technology with the conventional hydraulic algorithmic models in order to assist novice application users in selection and manipulation of various mathematical tools.
Although this case is about enterprise information system project selection, it contributes to the study of ANP application in project selection in broader areas besides enterprise information system project.
Pore pressure prediction has an important application in proper selection of the casing points and a reliable mud weight.
The sDSP has a significant potential for application in material selection based on multiple objectives in the presence of uncertainty.
In the present paper, we extended the MULTIMOORA method using entropy weight based on Shannon information theory for application in materials selection.
Deliktas and Ustun (2015) consolidated the fuzzy MULTIMOORA approach and multi-choice conic goal programming for application in student selection problem.
Eventually, concluding remarks were cited to make a summary of our work and to present an overview of the developed MULTIMOORA method and its application in materials selection.
This article investigates the usage of the ellipsoid method for systems of linear inequalities to rank normal and non-normal fuzzy numbers of equal heights and its application in robot selection.
However, most of current researches focus on technical aspects from domain engineering and application engineering to improve reusability and system efficiency rather than application of optimization methods in CBSD management, especially application in component selection.
For GBS marker application in genomic selection, methods of imputing missing data points for unordered markers have been developed (Rutkoski et al. 2013).
