Browsing by Subject "Artificial Neural Network"
Now showing items 1-9 of 9
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(1990)The objective of this research is to investigate the application of Artificial Neural Network techniques to the area of computer-aided design of electronic circuits. A major problem in this area is the analysis (especially ...
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(2019-11-13)Quantum computing and machine learning are both promising technologies that have seen rapid progress recently. However, the state of the art in these fields suggests it would be advantageous to combine both technologies ...
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(2014-04-28)Shape memory alloys are capable of delivering advantageous solutions to a wide range of engineering-based problems. Implementation of these solutions, however, is often complicated by the hysteretic, non-linear, thermomechanical ...
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(2013-08-08)This study presents different aspects on the use of deterministic methods including Artificial Neural Networks (ANNs), and linear and nonlinear regression, as well as probabilistic methods including Bayesian inference and ...
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(2017-05-10)Alternative resources play a vital role for water-sensitive infrastructures where consistent water supply is a challenge, and freshwater resources are limited. Greywater and A/C condensate are potentially new alternatives ...
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(2021-11-22)The Soil and Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN) have been widely used as rainfall-runoff models since the 1990s. The former is a more complex, physically-based model that went through ...
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(2021-12-13)Phase Change Materials (PCMs) have garnered significant attention over recent years due to their efficacy for thermal energy storage (TES) applications. High latent heat of PCMs enable enhanced storage densities which in ...
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(2011-02-22)Reflection cracking is one of the main distresses in hot-mix asphalt (HMA) overlays. It has been a serious concern since early in the 20th century. Since then, several models have been developed to predict the extent and ...
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(2020-07-27)Fast and reliable reservoir simulation is a key for the successful decision making in integrated reservoir studies. Large and complex multiphase reservoir models usually require expensive computational infrastructure. ...