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The good property was achieved using the advanced numerical techniques: model reduction, homogenization theory, metamodeling, and the combined approximations.
Optimization techniques, model updating, design process and Monte Carlo simulations of structures with uncertain parameters are some examples in which several analyses of slightly modified systems occurs.
The available heterogeneous object modeling techniques model simple material-distributions only and just a few of them are capable of modeling heterogeneous objects with complex geometries.
Accordingly, a Fuzzy Analytic Network Process (ANP), one of the Multi-Criteria Decision Making (MCDM) techniques, model is developed to determine the most important factors among the four categories for the HIS adoption in the context of Malaysian public hospitals.
The three MULTICOM programs (Cheng, 2008) (MUProt, MC-CLUSTER and MC-REFINE) use multiple threading programs, multiple-template techniques, model clustering and template-free modeling.
However, since these techniques model the optimization of the composite network and the prediction tasks as separate objectives, the resulting composite network is not necessarily optimal for the follow-up protein function prediction.
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The project could help aid diagnoses of diseases, help with the testing of new drugs, and develop supercomputing techniques modeled on the brain.
The objective is gained here by combining two complementary modeling techniques: Model-driven Engineering (MDE) and Formal Methods.
We propose novel MO naive Bayes learning techniques modeled by a Harmony Search meta-heuristic algorithm.
Section 2 analyzes the techniques, models, authors and results that have addressed the problem or similar problems in recent epochs.
The introduction of new methods, techniques, models, systems, and processes in answering the needs of CICL must be practiced.
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