or add more restrictions to the specific type of data. We may even return to the previous stage and experiment with alternative models if serious flaws are found in the approach.
(c) adaptive model, wherein the classification process starts from a global model which is retrained as a personalized model (Lu et al., 2012). Despite various modeling techniques, the classification algorithms posses the data labeling overhead either manually or automatically, therefore, the ...
It occurred to Zhang, who has a computer science background, that the AI could lend a hand and he developed the algorithm. "You have at least 100 elements at one single site, and the objects keep changing," said Zhang. "Only AI can calculate viable results via an inverse modeling." No...
Scaling-up dynamic elastic logs to pseudo-static elastic moduli of rocks using a wellbore stability analysis approach in the Marun oilfield, SW Iran Article Open access 17 August 2024 Stochastic lithofacies and petrophysical property modeling for fast history matching in heterogeneous clastic reservoir...
Modeling In this chapter, we propose the physical prototype of Spring-Ising Algorithm and how to apply Lagrange's equa- tions to iterate spin states by symplectic method. Spring-Ising Algorithm is inspired by physical phenomena, spring vibrations. The detail of physical prototype is introduced as ...
Based on the data-driven artificial intelligence algorithm Gradient Boosting Decision Tree (GBDT), this paper predicts the initial single-layer production by ... H Ma,W Zhao,Y Zhao,... - CMES-Computer Modeling in Engineering & Sciences 被引量: 0发表: 2023年 State of health estimation for ...
Anaraki MV, Achite M, Farzin S, Elshaboury N, Al-Ansari N, Elkhrachy I (2023a) Modeling of Monthly Rainfall–Runoff Using Various Machine Learning Techniques in Wadi Ouahrane Basin. Algeria Water 15:3576. https://doi.org/10.3390/w15203576 Article Google Scholar Anaraki MV, Kad...
A bi-level optimization model in data-intensive workflows is proposed.The upper-level and lower-level problems are data placement and task scheduling.Multitasking evolutionary algorithms on bi-level optimization model.Based on the modeling of the problem, an algorithm (IM-BLEA) is proposed.Simulation...
5.1.10Data modeling Frequency of published papers in six medical tasks can be shown inFig. 22. In each task, frequency ofdata miningapproach is given.Classification algorithmsappear as the most used in all tasks. Regression based algorithms are known as basic statistical techniques used to do va...
As shown in Fig. 15, the steps for solving an optimization problem are generally divided into mathematical modeling, algorithm designing, and solution analysis. First, common models for VNFPP are ordered from highest abstraction degree to lowest, which include the mathematical programming, probability...